{ "_id": "6a212bb8cd65a98ecbd23527", "Package": "mdatools", "Version": "0.15.0", "Title": "Multivariate Data Analysis for Chemometrics", "Date": "2026-03-06", "Authors@R": "person(\"Sergey\", \"Kucheryavskiy\", role = c(\"aut\", \"cre\"), email = \"svkucheryavski@gmail.com\", comment = c(ORCID = \"0000-0002-3145-7244\"))", "Description": "Projection based methods for preprocessing, exploring and\nanalysis of multivariate data used in chemometrics. S.\nKucheryavskiy (2020) .", "Encoding": "UTF-8", "License": "MIT + file LICENSE", "RoxygenNote": "7.3.3", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-04 07:35:20 UTC", "User": "root" }, "URL": "https://mda.tools", "BugReports": "https://github.com/svkucheryavski/mdatools/issues", "Repository": "https://svkucheryavski.r-universe.dev", "Date/Publication": "2026-03-06 11:20:01 UTC", "RemoteUrl": "https://github.com/svkucheryavski/mdatools", "RemoteRef": "HEAD", "RemoteSha": "b35fcbffdc1dfffcdd8ff8b72d2a5a240eebb56f", "Author": "Sergey Kucheryavskiy [aut, cre] (ORCID:\n)", "Maintainer": "Sergey Kucheryavskiy ", "MD5sum": "54ded365411c1f730df19e423d7aebd4", "_user": "svkucheryavski", "_type": "src", "_file": "mdatools_0.15.0.tar.gz", "_fileid": "d3bbf60995899202e89679ed1db5157a520e445d07ea9f22157eb45ea7d76063", "_filesize": 1681647, "_sha256": "d3bbf60995899202e89679ed1db5157a520e445d07ea9f22157eb45ea7d76063", "_created": "2026-06-04T07:35:20.000Z", "_published": "2026-06-04T07:39:36.723Z", "_distro": "noble", "_jobs": [ { "job": 79471581284, "time": 141, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "7405666476" }, { "job": 79471581356, "time": 176, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "7405676858" }, { "job": 79471581275, "time": 152, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "7405663747" }, { "job": 79471581302, "time": 197, "config": "macos-release-arm64", "r": "4.6.0", "check": "OK", "artifact": "7405673592" }, { "job": 79471171523, "time": 166, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "7405622216" }, { "job": 79471581308, "time": 94, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7405652562" }, { "job": 79471581281, "time": 117, "config": "windows-devel", "r": "4.7.0", "check": "OK", "artifact": "7405658700" }, { "job": 79471581303, "time": 172, "config": "windows-oldrel", "r": "4.5.3", "check": "OK", "artifact": "7405675894" }, { "job": 79471581287, "time": 106, "config": "windows-release", "r": "4.6.0", "check": "OK", "artifact": "7405655809" } ], "_buildurl": "https://github.com/r-universe/svkucheryavski/actions/runs/26937648059", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/svkucheryavski/mdatools", "_commit": { "id": "b35fcbffdc1dfffcdd8ff8b72d2a5a240eebb56f", "author": "Sergey Kucheryavskiy ", "committer": "Sergey Kucheryavskiy ", "message": "v. 0.15.0\n", "time": 1772796001 }, "_maintainer": { "name": "Sergey Kucheryavskiy", "email": "svkucheryavski@gmail.com", "login": "svkucheryavski", "linkedin": "in/sergeykucheryavskiy", "orcid": "0000-0002-3145-7244", "description": "I am working on tools and educational resources that make learning and using Chemometric methods easier and freely available to everyone", "uuid": 2104704 }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 3.5.0", "role": "Depends" }, { "package": "methods", "role": "Imports" }, { "package": "graphics", "role": "Imports" }, { "package": "grDevices", "role": "Imports" }, { "package": "stats", "role": "Imports" }, { "package": "spam", "role": "Imports" }, { "package": "pcv", "role": "Imports" }, { "package": "testthat", "role": "Suggests" } ], "_owner": "svkucheryavski", "_selfowned": true, "_usedby": 1, "_updates": [ { "week": "2026-10", "n": 1 } ], "_tags": [ { "name": "v0.15.0", "date": "2026-03-06" } ], "_stars": 41, "_contributors": [ { "user": "svkucheryavski", "count": 737, "uuid": 2104704 }, { "user": "gongyh", "count": 2, "uuid": 7972692 }, { "user": "svonallmen", "count": 2, "uuid": 68689173 } ], "_userbio": { "uuid": 2104704, "type": "user", "name": "Sergey Kucheryavskiy", "description": "I am working on tools and educational resources that make learning and using Chemometric methods easier and freely available to everyone" }, "_downloads": { "count": 1384, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/mdatools" }, "_mentions": 11, "_devurl": "https://github.com/svkucheryavski/mdatools", "_searchresults": 338, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/mdatools.html", "extra/NEWS.html", "extra/NEWS.txt", "extra/readme.html", "extra/readme.md", "manual.pdf" ], "_homeurl": "https://github.com/svkucheryavski/mdatools", "_realowner": "svkucheryavski", "_cranurl": true, "_releases": [ { "version": "0.5.1", "date": "2014-04-14" }, { "version": "0.5.3", "date": "2014-04-26" }, { "version": "0.6.0", "date": "2015-01-19" }, { "version": "0.7.0", "date": "2015-11-30" }, { "version": "0.8.2", "date": "2017-01-30" }, { "version": "0.9.1", "date": "2018-07-06" }, { "version": "0.9.4", "date": "2019-05-24" }, { "version": "0.10.1", "date": "2020-03-01" }, { "version": "0.10.3", "date": "2020-03-28" }, { "version": "0.11.0", "date": "2020-07-15" }, { "version": "0.11.1", "date": "2020-07-23" }, { "version": "0.11.2", "date": "2020-10-22" }, { "version": "0.11.3", "date": "2021-01-22" }, { "version": "0.11.4", "date": "2021-04-23" }, { "version": "0.11.5", "date": "2021-04-30" }, { "version": "0.12.0", "date": "2021-09-13" }, { "version": "0.13.0", "date": "2022-07-14" }, { "version": "0.13.1", "date": "2022-11-09" }, { "version": "0.14.0", "date": "2023-03-28" }, { "version": "0.14.1", "date": "2023-08-12" }, { "version": "0.14.2", "date": "2024-08-19" }, { "version": "0.15.0", "date": "2026-03-06" } ], "_exports": [ "arr2int", "asjson", "asvector", "capitalize", "categorize", "chisq.crit", "chisq.prob", "classmodel.processRefValues", "classres", "cleanLabels", "constraint", "constraintAngle", "constraintClosure", "constraintNonNegativity", "constraintNorm", "constraints.list", "constraintUnimod", "crossval", "crossval.regmodel", "dd.crit", "ddmoments.param", "ddrobust.param", "ddsimca", "ddsimca.readJSON", "ddsimcares", "ellipse", "employ.constraint", "employ.prep", "extractArray", "extractBlock", "extractPrep", "extractStringArray", "extractValue", "fprintf", "genhash", "getCalibrationData", "getConfusionMatrix", "getImplementedConstraints", "getImplementedPrepMethods", "getProbabilities", "getPureVariables", "getRegcoeffs", "getRes", "getSelectivityRatio", "getVariance.mcr", "getVIPScores", "hotelling.crit", "hotelling.prob", "imshow", "ipls", "jm.crit", "jm.prob", "ldecomp", "ldecomp.getLimitsCoordinates", "ldecomp.getLimParams", "ldecomp.getQLimits", "ldecomp.getT2Limits", "ldecomp.plotDistances", "ldecomp.plotResiduals", "mcr", "mcrals", "mcrals.cal", "mcrals.fcnnls", "mcrals.nnls", "mcrals.ols", "mcrpure", "mda.cbind", "mda.data2im", "mda.df2mat", "mda.exclcols", "mda.exclrows", "mda.getattr", "mda.getexclind", "mda.im2data", "mda.inclcols", "mda.inclrows", "mda.purge", "mda.purgeCols", "mda.purgeRows", "mda.rbind", "mda.setattr", "mda.setimbg", "mda.show", "mda.subset", "mda.t", "mdaplot", "mdaplot.getColors", "mdaplot.getXTickLabels", "mdaplot.getXTicks", "mdaplot.getYTickLabels", "mdaplot.getYTicks", "mdaplotg", "mdaplotg.getXLim", "mdaplotg.getYLim", "mdaplotyy", "pca", "pca.getB", "pca.mvreplace", "pca.readJSON", "pca.run", "pcares", "pinv", "plotAcceptance", "plotAliens", "plotBars", "plotBiplot", "plotConfidenceEllipse", "plotContributions", "plotConvexHull", "plotCooman", "plotCorr", "plotCumVariance", "plotDiscriminationPower", "plotDistances", "plotDistDoF", "plotEigenvalues", "plotErrorbars", "plotExtreme", "plotExtremes", "plotFoM", "plotFoMs", "plotHist", "plotHotellingEllipse", "plotLines", "plotLoadings", "plotMisclassified", "plotModelDistance", "plotModellingPower", "plotPerformance", "plotPointsShape", "plotPredictions", "plotProbabilities", "plotPurity", "plotPuritySpectra", "plotQDoF", "plotRegcoeffs", "plotResiduals", "plotRMSE", "plotRMSERatio", "plotScatter", "plotScores", "plotSelection", "plotSelectivityArea", "plotSelectivityRatio", "plotSensitivity", "plotseries", "plotSpecificity", "plotSpectra", "plotT2DoF", "plotVariance", "plotVIPScores", "plotWeights", "plotXCumVariance", "plotXLoadings", "plotXResiduals", "plotXScores", "plotXVariance", "plotXYLoadings", "plotXYResiduals", "plotXYScores", "plotYCumVariance", "plotYResiduals", "plotYVariance", "pls", "pls.getLimitsCoordinates", "pls.getZLimits", "pls.readJSON", "pls.run", "plsda", "plsdares", "plsres", "prep", "prep.alsbasecorr", "prep.apply", "prep.asjson", "prep.autoscale", "prep.center", "prep.emsc", "prep.fit", "prep.list", "prep.msc", "prep.norm", "prep.ref2km", "prep.savgol", "prep.scale", "prep.snv", "prep.spikes", "prep.transform", "prep.varsel", "prepCalData", "randtest", "readJSON", "regcoeffs", "regcoeffs.getStats", "regres", "regres.r2", "repmat", "selectCompNum", "selratio", "setDistanceLimits", "setParams", "showDistanceLimits", "showPredictions", "simca", "simcam", "simcamres", "simcares", "vipscores", "writeCSV", "writeJSON" ], "_datasets": [ { "name": "carbs", "title": "Raman spectra of carbonhydrates", "object": "carbs", "file": "carbs.RData", "class": [ "list" ], "fields": [], "table": false, "tojson": true }, { "name": "pellets", "title": "Image data", "object": "pellets", "file": "pellets.RData", "class": [ "array" ], "fields": [], "table": false, "tojson": true }, { "name": "people", "title": "People data", "object": "people", "file": "people.RData", "class": [ "matrix", "array" ], "fields": [ "Height", "Weight", "Hairleng", "Shoesize", "Age", "Income", "Beer", "Wine", "Sex", "Swim", "Region", "IQ" ], "rows": 32, "table": true, "tojson": true }, { "name": "simdata", "title": "Spectral data of polyaromatic hydrocarbons mixing", "object": "simdata", "file": "simdata.RData", "class": [ "list" ], "fields": [], "table": false, "tojson": true } ], "_help": [ { "page": "arr2int", "title": "Convert a vector of integers to a compact interval string", "topics": [ "arr2int" ] }, { "page": "as.data.frame.ddsimcares", "title": "Creates a data frame from DD-SIMCA classification results.", "topics": [ "as.data.frame.ddsimcares" ] }, { "page": "as.matrix.classres", "title": "as.matrix method for classification results", "topics": [ "as.matrix.classres" ] }, { "page": "as.matrix.ddsimcares", "title": "Creates a matrix from DD-SIMCA classification results.", "topics": [ "as.matrix.ddsimcares" ] }, { "page": "as.matrix.ldecomp", "title": "as.matrix method for ldecomp object", "topics": [ "as.matrix.ldecomp" ] }, { "page": "as.matrix.plsdares", "title": "as.matrix method for PLS-DA results", "topics": [ "as.matrix.plsdares" ] }, { "page": "as.matrix.plsres", "title": "as.matrix method for PLS results", "topics": [ "as.matrix.plsres" ] }, { "page": "as.matrix.regcoeffs", "title": "as.matrix method for regression coefficients class", "topics": [ "as.matrix.regcoeffs" ] }, { "page": "as.matrix.regres", "title": "as.matrix method for regression results", "topics": [ "as.matrix.regres" ] }, { "page": "as.matrix.simcamres", "title": "as.matrix method for SIMCAM results", "topics": [ "as.matrix.simcamres" ] }, { "page": "as.matrix.simcares", "title": "as.matrix method for SIMCA classification results", "topics": [ "as.matrix.simcares" ] }, { "page": "asjson", "title": "S3 implementation of asjson() method", "topics": [ "asjson" ] }, { "page": "asjson.ddsimca", "title": "Converts object with DD-SIMCA model to JSON string compatible with web-application.", "topics": [ "asjson.ddsimca" ] }, { "page": "asjson.pca", "title": "Converts object with PCA model to JSON string compatible with web-application.", "topics": [ "asjson.pca" ] }, { "page": "asjson.pls", "title": "Converts object with PLS model to JSON string compatible with web-application.", "topics": [ "asjson.pls" ] }, { "page": "asvector", "title": "S3 implementation of as.vector() method", "topics": [ "asvector" ] }, { "page": "asvector.pca", "title": "Converts object with PCA model to numeric vector compatible with web-application.", "topics": [ "asvector.pca" ] }, { "page": "asvector.pls", "title": "Converts object with PLS model to numeric vector compatible with web-application.", "topics": [ "asvector.pls" ] }, { "page": "capitalize", "title": "Capitalize text or vector with text values", "topics": [ "capitalize" ] }, { "page": "carbs", "title": "Raman spectra of carbonhydrates", "topics": [ "carbs" ] }, { "page": "categorize", "title": "Categorize PCA results", "topics": [ "categorize" ] }, { "page": "categorize.pca", "title": "Categorize PCA results based on orthogonal and score distances.", "topics": [ "categorize.pca" ] }, { "page": "categorize.pls", "title": "Categorize data rows based on PLS results and critical limits for total distance.", "topics": [ "categorize.pls" ] }, { "page": "chisq.crit", "title": "Calculates critical limits for distance values using Chi-square distribution", "topics": [ "chisq.crit" ] }, { "page": "chisq.prob", "title": "Calculate probabilities for distance values using Chi-square distribution", "topics": [ "chisq.prob" ] }, { "page": "clamp.dof", "title": "Round and clamp degrees of freedom to valid range [1, 250]", "topics": [ "clamp.dof" ] }, { "page": "classify", "title": "Creates classification outcomes for given PCA result objects and distance parameters.", "topics": [ "classify" ] }, { "page": "classify.plsda", "title": "PLS-DA classification", "topics": [ "classify.plsda" ] }, { "page": "classify.simca", "title": "SIMCA classification", "topics": [ "classify.simca" ] }, { "page": "classmodel.processRefValues", "title": "Check reference class values and convert it to a factor if necessary", "topics": [ "classmodel.processRefValues" ] }, { "page": "classres", "title": "Results of classification", "topics": [ "classres" ] }, { "page": "classres.getPerformance", "title": "Calculation of classification performance parameters", "topics": [ "classres.getPerformance" ] }, { "page": "cleanLabels", "title": "Clean text labels from extra elements so they are compatible with JSON", "topics": [ "cleanLabels" ] }, { "page": "confint.regcoeffs", "title": "Confidence intervals for regression coefficients", "topics": [ "confint.regcoeffs" ] }, { "page": "constraint", "title": "Class for MCR-ALS constraint", "topics": [ "constraint" ] }, { "page": "constraintAngle", "title": "Method for angle constraint", "topics": [ "constraintAngle" ] }, { "page": "constraintClosure", "title": "Method for closure constraint", "topics": [ "constraintClosure" ] }, { "page": "constraintNonNegativity", "title": "Method for non-negativity constraint", "topics": [ "constraintNonNegativity" ] }, { "page": "constraintNorm", "title": "Method for normalization constraint", "topics": [ "constraintNorm" ] }, { "page": "constraints.list", "title": "Shows information about all implemented constraints", "topics": [ "constraints.list" ] }, { "page": "constraintUnimod", "title": "Method for unimodality constraint", "topics": [ "constraintUnimod" ] }, { "page": "create_categories", "title": "Create a factor with categories (regular, extreme, outlier)", "topics": [ "create_categories" ] }, { "page": "crossval", "title": "Generate sequence of indices for cross-validation", "topics": [ "crossval" ] }, { "page": "crossval.getParams", "title": "Define parameters based on 'cv' value", "topics": [ "crossval.getParams" ] }, { "page": "crossval.regmodel", "title": "Cross-validation of a regression model", "topics": [ "crossval.regmodel" ] }, { "page": "crossval.simca", "title": "Cross-validation of a SIMCA model", "topics": [ "crossval.simca" ] }, { "page": "crossval.str", "title": "String with description of cross-validation method", "topics": [ "crossval.str" ] }, { "page": "dd.crit", "title": "Calculates critical limits for distance values using Data Driven moments approach", "topics": [ "dd.crit" ] }, { "page": "ddmoments.param", "title": "Calculates critical limits for distance values using Data Driven moments approach", "topics": [ "ddmoments.param" ] }, { "page": "ddrobust.param", "title": "Calculates critical limits for distance values using Data Driven robust approach", "topics": [ "ddrobust.param" ] }, { "page": "ddsimca", "title": "Data Driven SIMCA", "topics": [ "ddsimca" ] }, { "page": "ddsimca.fromjson", "title": "Converts JSON string created in mda.tools/ddsimca app to 'ddsimca' object", "topics": [ "ddsimca.fromjson" ] }, { "page": "ddsimca.readJSON", "title": "Reads DD-SIMCA model from JSON file made in web-application (mda.tools/ddsimca).", "topics": [ "ddsimca.readJSON" ] }, { "page": "ddsimcares", "title": "Results of DD-SIMCA one-class classification", "topics": [ "ddsimcares" ] }, { "page": "ellipse", "title": "Create ellipse on the current plot", "topics": [ "ellipse" ] }, { "page": "employ.constraint", "title": "Applies constraint to a dataset", "topics": [ "employ.constraint" ] }, { "page": "employ.prep", "title": "Applies a list with preprocessing methods to a dataset", "topics": [ "employ.prep" ] }, { "page": "extractArray", "title": "Extract numeric array from JSON string", "topics": [ "extractArray" ] }, { "page": "extractBlock", "title": "Extracts a JSON subset in main JSON structure", "topics": [ "extractBlock" ] }, { "page": "extractPrep", "title": "Extracts JSON related to preprocessing model", "topics": [ "extractPrep" ] }, { "page": "extractStringArray", "title": "Extract string array from JSON string", "topics": [ "extractStringArray" ] }, { "page": "extractValue", "title": "Extract single value from JSON string", "topics": [ "extractValue" ] }, { "page": "fprintf", "title": "Imitation of fprintf() function", "topics": [ "fprintf" ] }, { "page": "genhash", "title": "Generates unique pseudo-hash number based on current time and date", "topics": [ "genhash" ] }, { "page": "getCalibrationData", "title": "Calibration data", "topics": [ "getCalibrationData" ] }, { "page": "getCalibrationData.pca", "title": "Returns matrix with original calibration data", "topics": [ "getCalibrationData.pca" ] }, { "page": "getCalibrationData.simcam", "title": "Get calibration data", "topics": [ "getCalibrationData.simcam" ] }, { "page": "getConfidenceEllipse", "title": "Compute confidence ellipse for a set of points", "topics": [ "getConfidenceEllipse" ] }, { "page": "getConfusionMatrix", "title": "Confusion matrix for classification results", "topics": [ "getConfusionMatrix" ] }, { "page": "getConfusionMatrix.classres", "title": "Confusion matrix for classification results", "topics": [ "getConfusionMatrix.classres" ] }, { "page": "getConvexHull", "title": "Compute coordinates of a closed convex hull for data points", "topics": [ "getConvexHull" ] }, { "page": "getDataLabels", "title": "Create a vector with labels for plot series", "topics": [ "getDataLabels" ] }, { "page": "getImplementedConstraints", "title": "Shows a list with implemented constraints", "topics": [ "getImplementedConstraints" ] }, { "page": "getImplementedPrepMethods", "title": "Shows a list with implemented preprocessing methods", "topics": [ "getImplementedPrepMethods" ] }, { "page": "getLabelsAsIndices", "title": "Create labels as column or row indices", "topics": [ "getLabelsAsIndices" ] }, { "page": "getLabelsAsValues", "title": "Create labels from data values", "topics": [ "getLabelsAsValues" ] }, { "page": "getMainTitle", "title": "Get main title", "topics": [ "getMainTitle" ] }, { "page": "getPlotColors", "title": "Define colors for plot series", "topics": [ "getPlotColors" ] }, { "page": "getProbabilities", "title": "Get class belonging probability", "topics": [ "getProbabilities" ] }, { "page": "getProbabilities.pca", "title": "Probabilities for residual distances", "topics": [ "getProbabilities.pca" ] }, { "page": "getProbabilities.simca", "title": "Probabilities of class belonging for PCA/SIMCA results", "topics": [ "getProbabilities.simca" ] }, { "page": "getPureVariables", "title": "Identifies pure variables", "topics": [ "getPureVariables" ] }, { "page": "getRegcoeffs", "title": "Get regression coefficients", "topics": [ "getRegcoeffs" ] }, { "page": "getRegcoeffs.regmodel", "title": "Regression coefficients for PLS model", "topics": [ "getRegcoeffs.regmodel" ] }, { "page": "getRes", "title": "Return list with valid results", "topics": [ "getRes" ] }, { "page": "getSelectedComponents", "title": "Get selected components", "topics": [ "getSelectedComponents" ] }, { "page": "getSelectivityRatio", "title": "Selectivity ratio", "topics": [ "getSelectivityRatio" ] }, { "page": "getSelectivityRatio.pls", "title": "Selectivity ratio for PLS model", "topics": [ "getSelectivityRatio.pls" ] }, { "page": "getVariance.mcr", "title": "Compute explained variance for MCR case", "topics": [ "getVariance.mcr" ] }, { "page": "getVIPScores", "title": "VIP scores", "topics": [ "getVIPScores" ] }, { "page": "getVIPScores.pls", "title": "VIP scores for PLS model", "topics": [ "getVIPScores.pls" ] }, { "page": "hotelling.crit", "title": "Calculate critical limits for distance values using Hotelling T2 distribution", "topics": [ "hotelling.crit" ] }, { "page": "hotelling.prob", "title": "Calculate probabilities for distance values and given parameters using Hotelling T2 distribution", "topics": [ "hotelling.prob" ] }, { "page": "imshow", "title": "show image data as an image", "topics": [ "imshow" ] }, { "page": "ipls", "title": "Variable selection with interval PLS", "topics": [ "ipls" ] }, { "page": "ipls.backward", "title": "Runs the backward iPLS algorithm", "topics": [ "ipls.backward" ] }, { "page": "ipls.forward", "title": "Runs the forward iPLS algorithm", "topics": [ "ipls.forward" ] }, { "page": "jm.crit", "title": "Calculate critical limits for distance values using Jackson-Mudholkar approach", "topics": [ "jm.crit" ] }, { "page": "jm.prob", "title": "Calculate probabilities for distance values and given parameters using Hotelling T2 distribution", "topics": [ "jm.prob" ] }, { "page": "ldecomp", "title": "Class for storing and visualising linear decomposition of dataset (X = TP' + E)", "topics": [ "ldecomp" ] }, { "page": "ldecomp.getDistances", "title": "Compute score and residual distances", "topics": [ "ldecomp.getDistances" ] }, { "page": "ldecomp.getLimitsCoordinates", "title": "Compute coordinates of lines or curves with critical limits", "topics": [ "ldecomp.getLimitsCoordinates" ] }, { "page": "ldecomp.getLimParams", "title": "Compute parameters for critical limits based on calibration results", "topics": [ "ldecomp.getLimParams" ] }, { "page": "ldecomp.getQLimits", "title": "Compute critical limits for orthogonal distances (Q)", "topics": [ "ldecomp.getQLimits" ] }, { "page": "ldecomp.getT2Limits", "title": "Compute critical limits for score distances (T2)", "topics": [ "ldecomp.getT2Limits" ] }, { "page": "ldecomp.getVariances", "title": "Compute explained variance", "topics": [ "ldecomp.getVariances" ] }, { "page": "ldecomp.plotDistances", "title": "Distance plot for a set of ldecomp objects", "topics": [ "ldecomp.plotDistances" ] }, { "page": "ldecomp.plotResiduals", "title": "Residuals distance plot for a set of ldecomp objects (legacy, use 'ldecomp.plotDistances' instead).", "topics": [ "ldecomp.plotResiduals" ] }, { "page": "mcr", "title": "General class for Multivariate Curve Resolution model", "topics": [ "mcr" ] }, { "page": "mcrals", "title": "Multivariate curve resolution using Alternating Least Squares", "topics": [ "mcrals" ] }, { "page": "mcrals.cal", "title": "MCR-ALS calibration", "topics": [ "mcrals.cal" ] }, { "page": "mcrals.fcnnls", "title": "Fast combinatorial non-negative least squares", "topics": [ "mcrals.fcnnls" ] }, { "page": "mcrals.nnls", "title": "Non-negative least squares", "topics": [ "mcrals.nnls" ] }, { "page": "mcrals.ols", "title": "Ordinary least squares", "topics": [ "mcrals.ols" ] }, { "page": "mcrpure", "title": "Multivariate curve resolution based on pure variables", "topics": [ "mcrpure" ] }, { "page": "mda.cbind", "title": "A wrapper for cbind() method with proper set of attributes", "topics": [ "mda.cbind" ] }, { "page": "mda.data2im", "title": "Convert data matrix to an image", "topics": [ "mda.data2im" ] }, { "page": "mda.df2mat", "title": "Convert data frame to a matrix", "topics": [ "mda.df2mat" ] }, { "page": "mda.exclcols", "title": "Exclude/hide columns in a dataset", "topics": [ "mda.exclcols" ] }, { "page": "mda.exclrows", "title": "Exclude/hide rows in a dataset", "topics": [ "mda.exclrows" ] }, { "page": "mda.getattr", "title": "Get data attributes", "topics": [ "mda.getattr" ] }, { "page": "mda.getexclind", "title": "Get indices of excluded rows or columns", "topics": [ "mda.getexclind" ] }, { "page": "mda.im2data", "title": "Convert image to data matrix", "topics": [ "mda.im2data" ] }, { "page": "mda.inclcols", "title": "Include/unhide the excluded columns", "topics": [ "mda.inclcols" ] }, { "page": "mda.inclrows", "title": "include/unhide the excluded rows", "topics": [ "mda.inclrows" ] }, { "page": "mda.purge", "title": "Removes excluded (hidden) rows and columns from data", "topics": [ "mda.purge" ] }, { "page": "mda.purgeCols", "title": "Removes excluded (hidden) columns from data", "topics": [ "mda.purgeCols" ] }, { "page": "mda.purgeRows", "title": "Removes excluded (hidden) rows from data", "topics": [ "mda.purgeRows" ] }, { "page": "mda.rbind", "title": "A wrapper for rbind() method with proper set of attributes", "topics": [ "mda.rbind" ] }, { "page": "mda.setattr", "title": "Set data attributes", "topics": [ "mda.setattr" ] }, { "page": "mda.setimbg", "title": "Remove background pixels from image data", "topics": [ "mda.setimbg" ] }, { "page": "mda.show", "title": "Wrapper for show() method", "topics": [ "mda.show" ] }, { "page": "mda.subset", "title": "A wrapper for subset() method with proper set of attributes", "topics": [ "mda.subset" ] }, { "page": "mda.t", "title": "A wrapper for t() method with proper set of attributes", "topics": [ "mda.t" ] }, { "page": "mdaplot", "title": "Plotting function for a single set of objects", "topics": [ "mdaplot" ] }, { "page": "mdaplot.areColors", "title": "Check color values", "topics": [ "mdaplot.areColors" ] }, { "page": "mdaplot.formatValues", "title": "Format vector with numeric values", "topics": [ "mdaplot.formatValues" ] }, { "page": "mdaplot.getColors", "title": "Color values for plot elements", "topics": [ "mdaplot.getColors" ] }, { "page": "mdaplot.getXAxisLim", "title": "Calculate limits for x-axis.", "topics": [ "mdaplot.getXAxisLim" ] }, { "page": "mdaplot.getXTickLabels", "title": "Prepare xticklabels for plot", "topics": [ "mdaplot.getXTickLabels" ] }, { "page": "mdaplot.getXTicks", "title": "Prepare xticks for plot", "topics": [ "mdaplot.getXTicks" ] }, { "page": "mdaplot.getYAxisLim", "title": "Calculate limits for y-axis.", "topics": [ "mdaplot.getYAxisLim" ] }, { "page": "mdaplot.getYTickLabels", "title": "Prepare yticklabels for plot", "topics": [ "mdaplot.getYTickLabels" ] }, { "page": "mdaplot.getYTicks", "title": "Prepare yticks for plot", "topics": [ "mdaplot.getYTicks" ] }, { "page": "mdaplot.plotAxes", "title": "Create axes plane", "topics": [ "mdaplot.plotAxes" ] }, { "page": "mdaplot.prepareColors", "title": "Prepare colors based on palette and opacity value", "topics": [ "mdaplot.prepareColors" ] }, { "page": "mdaplot.showColorbar", "title": "Plot colorbar", "topics": [ "mdaplot.showColorbar" ] }, { "page": "mdaplot.showLines", "title": "Plot lines", "topics": [ "mdaplot.showLines" ] }, { "page": "mdaplotg", "title": "Plotting function for several plot series", "topics": [ "mdaplotg" ] }, { "page": "mdaplotg.getLegend", "title": "Create and return vector with legend values", "topics": [ "mdaplotg.getLegend" ] }, { "page": "mdaplotg.getXLim", "title": "Compute x-axis limits for mdaplotg", "topics": [ "mdaplotg.getXLim" ] }, { "page": "mdaplotg.getYLim", "title": "Compute y-axis limits for mdaplotg", "topics": [ "mdaplotg.getYLim" ] }, { "page": "mdaplotg.prepareData", "title": "Prepare data for mdaplotg", "topics": [ "mdaplotg.prepareData" ] }, { "page": "mdaplotg.processParam", "title": "Check mdaplotg parameters and replicate them if necessary", "topics": [ "mdaplotg.processParam" ] }, { "page": "mdaplotg.showLegend", "title": "Show legend for mdaplotg", "topics": [ "mdaplotg.showLegend" ] }, { "page": "mdaplotyy", "title": "Create line plot with double y-axis", "topics": [ "mdaplotyy" ] }, { "page": "mdatools", "title": "Package for Multivariate Data Analysis (Chemometrics)", "topics": [ "mdatools" ] }, { "page": "paste1", "title": "Paste values together with no separator and collapse into a single string", "topics": [ "paste1" ] }, { "page": "pca", "title": "Principal Component Analysis", "topics": [ "pca" ] }, { "page": "pca.cal", "title": "PCA model calibration", "topics": [ "pca.cal" ] }, { "page": "pca.fromjson", "title": "Converts JSON string created in mda.tools/pca app to 'pca' object", "topics": [ "pca.fromjson" ] }, { "page": "pca.getB", "title": "Low-dimensional approximation of data matrix X", "topics": [ "pca.getB" ] }, { "page": "pca.mvreplace", "title": "Replace missing values in data", "topics": [ "pca.mvreplace" ] }, { "page": "pca.nipals", "title": "NIPALS based PCA algorithm", "topics": [ "pca.nipals" ] }, { "page": "pca.readJSON", "title": "Reads PCA model from JSON file made in web-application (mda.tools/pca).", "topics": [ "pca.readJSON" ] }, { "page": "pca.run", "title": "Runs one of the selected PCA methods", "topics": [ "pca.run" ] }, { "page": "pca.svd", "title": "Singular Values Decomposition based PCA algorithm", "topics": [ "pca.svd" ] }, { "page": "pca.syncResAliases", "title": "Sync calres/testres aliases with the canonical res[[\"cal\"]]/res[[\"test\"]] fields.", "topics": [ "pca.syncResAliases" ] }, { "page": "pcares", "title": "Results of PCA decomposition", "topics": [ "pcares" ] }, { "page": "pellets", "title": "Image data", "topics": [ "pellets" ] }, { "page": "people", "title": "People data", "topics": [ "people" ] }, { "page": "pinv", "title": "Pseudo-inverse matrix", "topics": [ "pinv" ] }, { "page": "plot.classres", "title": "Plot function for classification results", "topics": [ "plot.classres" ] }, { "page": "plot.ddsimca", "title": "Model overview plot for DD-SIMCA", "topics": [ "plot.ddsimca" ] }, { "page": "plot.ddsimcares", "title": "Plot method for DD-SIMCA results.", "topics": [ "plot.ddsimcares" ] }, { "page": "plot.ipls", "title": "Overview plot for iPLS results", "topics": [ "plot.ipls" ] }, { "page": "plot.mcr", "title": "Plot summary for MCR model", "topics": [ "plot.mcr" ] }, { "page": "plot.pca", "title": "Model overview plot for PCA", "topics": [ "plot.pca" ] }, { "page": "plot.pcares", "title": "Plot method for PCA results object", "topics": [ "plot.pcares" ] }, { "page": "plot.pls", "title": "Model overview plot for PLS", "topics": [ "plot.pls" ] }, { "page": "plot.plsda", "title": "Model overview plot for PLS-DA", "topics": [ "plot.plsda" ] }, { "page": "plot.plsdares", "title": "Overview plot for PLS-DA results", "topics": [ "plot.plsdares" ] }, { "page": "plot.plsres", "title": "Overview plot for PLS results", "topics": [ "plot.plsres" ] }, { "page": "plot.randtest", "title": "Plot for randomization test results", "topics": [ "plot.randtest" ] }, { "page": "plot.regcoeffs", "title": "Regression coefficients plot", "topics": [ "plot.regcoeffs" ] }, { "page": "plot.regres", "title": "Plot method for regression results", "topics": [ "plot.regres" ] }, { "page": "plot.simca", "title": "Model overview plot for SIMCA", "topics": [ "plot.simca" ] }, { "page": "plot.simcam", "title": "Model overview plot for SIMCAM", "topics": [ "plot.simcam" ] }, { "page": "plot.simcamres", "title": "Model overview plot for SIMCAM results", "topics": [ "plot.simcamres" ] }, { "page": "plotAcceptance", "title": "Acceptance plot for DDSIMCA model and results (generic function)", "topics": [ "plotAcceptance" ] }, { "page": "plotAcceptance.ddsimca", "title": "Acceptance plot for DD-SIMCA model.", "topics": [ "plotAcceptance.ddsimca" ] }, { "page": "plotAcceptance.ddsimcares", "title": "Acceptance plot for DD-SIMCA results object.", "topics": [ "plotAcceptance.ddsimcares" ] }, { "page": "plotAliens", "title": "Aliens plot for DD-SIMCA results (generic function)", "topics": [ "plotAliens" ] }, { "page": "plotAliens.ddsimcares", "title": "Aliens plot for DD-SIMCA results.", "topics": [ "plotAliens.ddsimcares" ] }, { "page": "plotBars", "title": "Show plot series as bars", "topics": [ "plotBars" ] }, { "page": "plotBiplot", "title": "Biplot", "topics": [ "plotBiplot" ] }, { "page": "plotBiplot.pca", "title": "PCA biplot", "topics": [ "plotBiplot.pca" ] }, { "page": "plotConfidenceEllipse", "title": "Add confidence ellipse for groups of points on scatter plot", "topics": [ "plotConfidenceEllipse" ] }, { "page": "plotContributions", "title": "Plot resolved contributions", "topics": [ "plotContributions" ] }, { "page": "plotContributions.mcr", "title": "Show plot with resolved contributions", "topics": [ "plotContributions.mcr" ] }, { "page": "plotConvexHull", "title": "Add convex hull for groups of points on scatter plot", "topics": [ "plotConvexHull" ] }, { "page": "plotCooman", "title": "Cooman's plot", "topics": [ "plotCooman" ] }, { "page": "plotCooman.simcam", "title": "Cooman's plot for SIMCAM model", "topics": [ "plotCooman.simcam" ] }, { "page": "plotCooman.simcamres", "title": "Cooman's plot for SIMCAM results", "topics": [ "plotCooman.simcamres" ] }, { "page": "plotCorr", "title": "Correlation plot", "topics": [ "plotCorr" ] }, { "page": "plotCorr.randtest", "title": "Correlation plot for randomization test results", "topics": [ "plotCorr.randtest" ] }, { "page": "plotCumVariance", "title": "Variance plot", "topics": [ "plotCumVariance" ] }, { "page": "plotCumVariance.ldecomp", "title": "Cumulative explained variance plot", "topics": [ "plotCumVariance.ldecomp" ] }, { "page": "plotCumVariance.mcr", "title": "Show plot with cumulative explained variance", "topics": [ "plotCumVariance.mcr" ] }, { "page": "plotCumVariance.pca", "title": "Cumulative explained variance plot for PCA model", "topics": [ "plotCumVariance.pca" ] }, { "page": "plotDensity", "title": "Show plot series as density plot (using hex binning)", "topics": [ "plotDensity" ] }, { "page": "plotDiscriminationPower", "title": "Discrimination power plot", "topics": [ "plotDiscriminationPower" ] }, { "page": "plotDiscriminationPower.simcam", "title": "Discrimination power plot for SIMCAM model", "topics": [ "plotDiscriminationPower.simcam" ] }, { "page": "plotDistances", "title": "Distance plot for model and results (generic function)", "topics": [ "plotDistances" ] }, { "page": "plotDistances.ddsimca", "title": "Show with distance values (score, orthogonal or full) vs object indices for calibration and PV-set results.", "topics": [ "plotDistances.ddsimca" ] }, { "page": "plotDistances.ddsimcares", "title": "Show with distance values (score, orthogonal or full) vs object indices for DD-SIMCA results.", "topics": [ "plotDistances.ddsimcares" ] }, { "page": "plotDistances.ldecomp", "title": "Distance plot", "topics": [ "plotDistances.ldecomp" ] }, { "page": "plotDistances.pca", "title": "Distance plot for PCA model", "topics": [ "plotDistances.pca" ] }, { "page": "plotDistDoF", "title": "Degrees of freedom plot for both distances", "topics": [ "plotDistDoF" ] }, { "page": "plotEigenvalues", "title": "Eigenvalues plot", "topics": [ "plotEigenvalues" ] }, { "page": "plotEigenvalues.pca", "title": "Eigenvalues plot for PCA model", "topics": [ "plotEigenvalues.pca" ] }, { "page": "plotErrorbars", "title": "Show plot series as error bars", "topics": [ "plotErrorbars" ] }, { "page": "plotExtreme", "title": "Shows extreme plot for PCA and DD-SIMCA models", "topics": [ "plotExtreme" ] }, { "page": "plotExtreme.ddsimca", "title": "A shortcut to 'plotExtremes.ddsimca'.", "topics": [ "plotExtreme.ddsimca" ] }, { "page": "plotExtreme.ddsimcares", "title": "Extremes plot (shortcut to 'plotExtremes.ddsimcares').", "topics": [ "plotExtreme.ddsimcares" ] }, { "page": "plotExtreme.pca", "title": "A shortcut to `'plotExtremes.pca'.", "topics": [ "plotExtreme.pca" ] }, { "page": "plotExtremes", "title": "Shows extreme plot for PCA and DD-SIMCA models", "topics": [ "plotExtremes" ] }, { "page": "plotExtremes.ddsimca", "title": "Extreme plot", "topics": [ "plotExtremes.ddsimca" ] }, { "page": "plotExtremes.ddsimcares", "title": "Extremes plot.", "topics": [ "plotExtremes.ddsimcares" ] }, { "page": "plotExtremes.pca", "title": "Extreme plot", "topics": [ "plotExtremes.pca" ] }, { "page": "plotFoM", "title": "Show plot with figure of merit vs. number of components (generic function).", "topics": [ "plotFoM" ] }, { "page": "plotFoM.ddsimcares", "title": "Figure of merit plot.", "topics": [ "plotFoM.ddsimcares" ] }, { "page": "plotFoMs", "title": "Show plot with several figures of merit vs. number of components (generic function).", "topics": [ "plotFoMs" ] }, { "page": "plotFoMs.ddsimcares", "title": "Figures of merit plot (multiple FoMs).", "topics": [ "plotFoMs.ddsimcares" ] }, { "page": "plotHist", "title": "Statistic histogram", "topics": [ "plotHist" ] }, { "page": "plotHist.randtest", "title": "Histogram plot for randomization test results", "topics": [ "plotHist.randtest" ] }, { "page": "plotHotellingEllipse", "title": "Hotelling ellipse", "topics": [ "plotHotellingEllipse" ] }, { "page": "plotLines", "title": "Show plot series as set of lines", "topics": [ "plotLines" ] }, { "page": "plotLoadings", "title": "Loadings plot", "topics": [ "plotLoadings" ] }, { "page": "plotLoadings.pca", "title": "Loadings plot for PCA model", "topics": [ "plotLoadings.pca" ] }, { "page": "plotMisclassified", "title": "Misclassification ratio plot", "topics": [ "plotMisclassified" ] }, { "page": "plotMisclassified.classmodel", "title": "Misclassified ratio plot for classification model", "topics": [ "plotMisclassified.classmodel" ] }, { "page": "plotMisclassified.classres", "title": "Misclassified ratio plot for classification results", "topics": [ "plotMisclassified.classres" ] }, { "page": "plotModelDistance", "title": "Model distance plot", "topics": [ "plotModelDistance" ] }, { "page": "plotModelDistance.simcam", "title": "Model distance plot for SIMCAM model", "topics": [ "plotModelDistance.simcam" ] }, { "page": "plotModellingPower", "title": "Modelling power plot", "topics": [ "plotModellingPower" ] }, { "page": "plotPerformance", "title": "Classification performance plot", "topics": [ "plotPerformance" ] }, { "page": "plotPerformance.classmodel", "title": "Performance plot for classification model", "topics": [ "plotPerformance.classmodel" ] }, { "page": "plotPerformance.classres", "title": "Performance plot for classification results", "topics": [ "plotPerformance.classres" ] }, { "page": "plotPointsShape", "title": "Add confidence ellipse or convex hull for group of points", "topics": [ "plotPointsShape" ] }, { "page": "plotPredictions", "title": "Predictions plot", "topics": [ "plotPredictions" ] }, { "page": "plotPredictions.classmodel", "title": "Predictions plot for classification model", "topics": [ "plotPredictions.classmodel" ] }, { "page": "plotPredictions.classres", "title": "Prediction plot for classification results", "topics": [ "plotPredictions.classres" ] }, { "page": "plotPredictions.regmodel", "title": "Predictions plot for regression model", "topics": [ "plotPredictions.regmodel" ] }, { "page": "plotPredictions.regres", "title": "Predictions plot for regression results", "topics": [ "plotPredictions.regres" ] }, { "page": "plotPredictions.simcam", "title": "Predictions plot for SIMCAM model", "topics": [ "plotPredictions.simcam" ] }, { "page": "plotPredictions.simcamres", "title": "Prediction plot for SIMCAM results", "topics": [ "plotPredictions.simcamres" ] }, { "page": "plotProbabilities", "title": "Plot for class belonging probability", "topics": [ "plotProbabilities" ] }, { "page": "plotProbabilities.classres", "title": "Plot for class belonging probability", "topics": [ "plotProbabilities.classres" ] }, { "page": "plotPurity", "title": "Plot purity values", "topics": [ "plotPurity" ] }, { "page": "plotPurity.mcrpure", "title": "Purity values plot", "topics": [ "plotPurity.mcrpure" ] }, { "page": "plotPuritySpectra", "title": "Plot purity spectra", "topics": [ "plotPuritySpectra" ] }, { "page": "plotPuritySpectra.mcrpure", "title": "Purity spectra plot", "topics": [ "plotPuritySpectra.mcrpure" ] }, { "page": "plotQDoF", "title": "Degrees of freedom plot for orthogonal distance (Nq)", "topics": [ "plotQDoF" ] }, { "page": "plotRegcoeffs", "title": "Regression coefficients plot", "topics": [ "plotRegcoeffs" ] }, { "page": "plotRegcoeffs.regmodel", "title": "Regression coefficient plot for regression model", "topics": [ "plotRegcoeffs.regmodel" ] }, { "page": "plotRegressionLine", "title": "Add regression line for data points", "topics": [ "plotRegressionLine" ] }, { "page": "plotResiduals", "title": "Residuals plot", "topics": [ "plotResiduals" ] }, { "page": "plotResiduals.ldecomp", "title": "Residuals distance plot for a set of ldecomp objects (legacy, use 'plotDistances.ldecomp' instead).", "topics": [ "plotResiduals.ldecomp" ] }, { "page": "plotResiduals.pca", "title": "Residuals distance plot for PCA model (legacy, use 'plotResiduals' instead).", "topics": [ "plotResiduals.pca" ] }, { "page": "plotResiduals.regres", "title": "Residuals plot for regression results", "topics": [ "plotResiduals.regres" ] }, { "page": "plotRMSE", "title": "RMSE plot", "topics": [ "plotRMSE" ] }, { "page": "plotRMSE.ipls", "title": "RMSE development plot", "topics": [ "plotRMSE.ipls" ] }, { "page": "plotRMSE.regmodel", "title": "RMSE plot for regression model", "topics": [ "plotRMSE.regmodel" ] }, { "page": "plotRMSE.regres", "title": "RMSE plot for regression results", "topics": [ "plotRMSE.regres" ] }, { "page": "plotRMSERatio", "title": "Plot for ratio RMSEC/RMSECV vs RMSECV", "topics": [ "plotRMSERatio" ] }, { "page": "plotRMSERatio.regmodel", "title": "RMSECV/RMSEC ratio plot for regression model", "topics": [ "plotRMSERatio.regmodel" ] }, { "page": "plotScatter", "title": "Show plot series as set of points", "topics": [ "plotScatter" ] }, { "page": "plotScores", "title": "Scores plot", "topics": [ "plotScores" ] }, { "page": "plotScores.ldecomp", "title": "Scores plot", "topics": [ "plotScores.ldecomp" ] }, { "page": "plotScores.pca", "title": "Scores plot for PCA model", "topics": [ "plotScores.pca" ] }, { "page": "plotSelection", "title": "Selected intervals plot", "topics": [ "plotSelection" ] }, { "page": "plotSelection.ipls", "title": "iPLS performance plot", "topics": [ "plotSelection.ipls" ] }, { "page": "plotSelectivityArea", "title": "Selectivity vs sensitivity plot for DD-SIMCA results (generic function)", "topics": [ "plotSelectivityArea" ] }, { "page": "plotSelectivityArea.ddsimcares", "title": "Selectivity area plot (similar to ROC curve).", "topics": [ "plotSelectivityArea.ddsimcares" ] }, { "page": "plotSelectivityRatio", "title": "Selectivity ratio plot", "topics": [ "plotSelectivityRatio" ] }, { "page": "plotSelectivityRatio.pls", "title": "Selectivity ratio plot for PLS model", "topics": [ "plotSelectivityRatio.pls" ] }, { "page": "plotSensitivity", "title": "Sensitivity plot", "topics": [ "plotSensitivity" ] }, { "page": "plotSensitivity.classmodel", "title": "Sensitivity plot for classification model", "topics": [ "plotSensitivity.classmodel" ] }, { "page": "plotSensitivity.classres", "title": "Sensitivity plot for classification results", "topics": [ "plotSensitivity.classres" ] }, { "page": "plotSensitivity.ddsimca", "title": "Sensitivity plot.", "topics": [ "plotSensitivity.ddsimca" ] }, { "page": "plotSensitivity.ddsimcares", "title": "Sensitivity plot.", "topics": [ "plotSensitivity.ddsimcares" ] }, { "page": "plotseries", "title": "Create plot series object based on data, plot type and parameters", "topics": [ "plotseries" ] }, { "page": "plotSpecificity", "title": "Specificity plot", "topics": [ "plotSpecificity" ] }, { "page": "plotSpecificity.classmodel", "title": "Specificity plot for classification model", "topics": [ "plotSpecificity.classmodel" ] }, { "page": "plotSpecificity.classres", "title": "Specificity plot for classification results", "topics": [ "plotSpecificity.classres" ] }, { "page": "plotSpectra", "title": "Plot resolved spectra", "topics": [ "plotSpectra" ] }, { "page": "plotSpectra.mcr", "title": "Show plot with resolved spectra", "topics": [ "plotSpectra.mcr" ] }, { "page": "plotT2DoF", "title": "Degrees of freedom plot for score distance (Nh)", "topics": [ "plotT2DoF" ] }, { "page": "plotVariance", "title": "Variance plot", "topics": [ "plotVariance" ] }, { "page": "plotVariance.ldecomp", "title": "Explained variance plot", "topics": [ "plotVariance.ldecomp" ] }, { "page": "plotVariance.mcr", "title": "Show plot with explained variance", "topics": [ "plotVariance.mcr" ] }, { "page": "plotVariance.pca", "title": "Explained variance plot for PCA model", "topics": [ "plotVariance.pca" ] }, { "page": "plotVariance.pls", "title": "Variance plot for PLS", "topics": [ "plotVariance.pls" ] }, { "page": "plotVariance.plsres", "title": "Explained X variance plot for PLS results", "topics": [ "plotVariance.plsres" ] }, { "page": "plotVIPScores", "title": "VIP scores plot", "topics": [ "plotVIPScores" ] }, { "page": "plotVIPScores.pls", "title": "VIP scores plot for PLS model", "topics": [ "plotVIPScores.pls" ] }, { "page": "plotWeights", "title": "Plot for PLS weights", "topics": [ "plotWeights" ] }, { "page": "plotWeights.pls", "title": "Weights plot for PLS", "topics": [ "plotWeights.pls" ] }, { "page": "plotXCumVariance", "title": "X cumulative variance plot", "topics": [ "plotXCumVariance" ] }, { "page": "plotXCumVariance.pls", "title": "Cumulative explained X variance plot for PLS", "topics": [ "plotXCumVariance.pls" ] }, { "page": "plotXCumVariance.plsres", "title": "Explained cumulative X variance plot for PLS results", "topics": [ "plotXCumVariance.plsres" ] }, { "page": "plotXLoadings", "title": "X loadings plot", "topics": [ "plotXLoadings" ] }, { "page": "plotXLoadings.pls", "title": "X loadings plot for PLS", "topics": [ "plotXLoadings.pls" ] }, { "page": "plotXResiduals", "title": "X residuals plot", "topics": [ "plotXResiduals" ] }, { "page": "plotXResiduals.pls", "title": "Residual distance plot for decomposition of X data", "topics": [ "plotXResiduals.pls" ] }, { "page": "plotXResiduals.plsres", "title": "X residuals plot for PLS results", "topics": [ "plotXResiduals.plsres" ] }, { "page": "plotXScores", "title": "X scores plot", "topics": [ "plotXScores" ] }, { "page": "plotXScores.pls", "title": "X scores plot for PLS", "topics": [ "plotXScores.pls" ] }, { "page": "plotXScores.plsres", "title": "X scores plot for PLS results", "topics": [ "plotXScores.plsres" ] }, { "page": "plotXVariance", "title": "X variance plot", "topics": [ "plotXVariance" ] }, { "page": "plotXVariance.pls", "title": "Explained X variance plot for PLS", "topics": [ "plotXVariance.pls" ] }, { "page": "plotXVariance.plsres", "title": "Explained X variance plot for PLS results", "topics": [ "plotXVariance.plsres" ] }, { "page": "plotXYLoadings", "title": "XY loadings plot", "topics": [ "plotXYLoadings" ] }, { "page": "plotXYLoadings.pls", "title": "XY loadings plot for PLS", "topics": [ "plotXYLoadings.pls" ] }, { "page": "plotXYResiduals", "title": "Plot for XY-residuals", "topics": [ "plotXYResiduals" ] }, { "page": "plotXYResiduals.pls", "title": "Residual XY-distance plot", "topics": [ "plotXYResiduals.pls" ] }, { "page": "plotXYResiduals.plsres", "title": "Residual distance plot", "topics": [ "plotXYResiduals.plsres" ] }, { "page": "plotXYScores", "title": "XY scores plot", "topics": [ "plotXYScores" ] }, { "page": "plotXYScores.pls", "title": "XY scores plot for PLS", "topics": [ "plotXYScores.pls" ] }, { "page": "plotXYScores.plsres", "title": "XY scores plot for PLS results", "topics": [ "plotXYScores.plsres" ] }, { "page": "plotYCumVariance", "title": "Y cumulative variance plot", "topics": [ "plotYCumVariance" ] }, { "page": "plotYCumVariance.pls", "title": "Cumulative explained Y variance plot for PLS", "topics": [ "plotYCumVariance.pls" ] }, { "page": "plotYCumVariance.plsres", "title": "Explained cumulative Y variance plot for PLS results", "topics": [ "plotYCumVariance.plsres" ] }, { "page": "plotYResiduals", "title": "Y residuals plot", "topics": [ "plotYResiduals" ] }, { "page": "plotYResiduals.plsres", "title": "Y residuals plot for PLS results", "topics": [ "plotYResiduals.plsres" ] }, { "page": "plotYResiduals.regmodel", "title": "Y residuals plot for regression model", "topics": [ "plotYResiduals.regmodel" ] }, { "page": "plotYVariance", "title": "Y variance plot", "topics": [ "plotYVariance" ] }, { "page": "plotYVariance.pls", "title": "Explained Y variance plot for PLS", "topics": [ "plotYVariance.pls" ] }, { "page": "plotYVariance.plsres", "title": "Explained Y variance plot for PLS results", "topics": [ "plotYVariance.plsres" ] }, { "page": "pls", "title": "Partial Least Squares regression", "topics": [ "pls" ] }, { "page": "pls.cal", "title": "PLS model calibration", "topics": [ "pls.cal" ] }, { "page": "pls.fromjson", "title": "Converts JSON string created in mda.tools/pls app to 'pls' object", "topics": [ "pls.fromjson" ] }, { "page": "pls.getLimitsCoordinates", "title": "Compute coordinates of lines or curves with critical limits", "topics": [ "pls.getLimitsCoordinates" ] }, { "page": "pls.getpredictions", "title": "Compute predictions for response values", "topics": [ "pls.getpredictions" ] }, { "page": "pls.getxdecomp", "title": "Compute object with decomposition of x-values", "topics": [ "pls.getxdecomp" ] }, { "page": "pls.getxscores", "title": "Compute matrix with X-scores", "topics": [ "pls.getxscores" ] }, { "page": "pls.getydecomp", "title": "Compute object with decomposition of y-values", "topics": [ "pls.getydecomp" ] }, { "page": "pls.getyscores", "title": "Compute and orthogonalize matrix with Y-scores", "topics": [ "pls.getyscores" ] }, { "page": "pls.getZLimits", "title": "Compute critical limits for orthogonal distances (Q)", "topics": [ "pls.getZLimits" ] }, { "page": "pls.readJSON", "title": "Reads PLS model from JSON file made in web-application (mda.tools/pls).", "topics": [ "pls.readJSON" ] }, { "page": "pls.run", "title": "Runs selected PLS algorithm", "topics": [ "pls.run" ] }, { "page": "pls.simpls", "title": "SIMPLS algorithm", "topics": [ "pls.simpls" ] }, { "page": "pls.syncResAliases", "title": "Sync result aliases (calres, cvres, testres) from canonical res list", "topics": [ "pls.syncResAliases" ] }, { "page": "plsda", "title": "Partial Least Squares Discriminant Analysis", "topics": [ "plsda" ] }, { "page": "plsdares", "title": "PLS-DA results", "topics": [ "plsdares" ] }, { "page": "plsres", "title": "PLS results", "topics": [ "plsres" ] }, { "page": "predict.ddsimca", "title": "DD-SIMCA predictions", "topics": [ "predict.ddsimca" ] }, { "page": "predict.mcrals", "title": "MCR ALS predictions", "topics": [ "predict.mcrals" ] }, { "page": "predict.mcrpure", "title": "MCR predictions", "topics": [ "predict.mcrpure" ] }, { "page": "predict.pca", "title": "PCA predictions", "topics": [ "predict.pca" ] }, { "page": "predict.pls", "title": "PLS predictions", "topics": [ "predict.pls" ] }, { "page": "predict.plsda", "title": "PLS-DA predictions", "topics": [ "predict.plsda" ] }, { "page": "predict.simca", "title": "SIMCA predictions", "topics": [ "predict.simca" ] }, { "page": "predict.simcam", "title": "SIMCA multiple classes predictions", "topics": [ "predict.simcam" ] }, { "page": "prep", "title": "Class for preprocessing object/item.", "topics": [ "prep" ] }, { "page": "prep.alsbasecorr", "title": "Baseline correction using asymmetric least squares", "topics": [ "prep.alsbasecorr" ] }, { "page": "prep.alsbasecorr.asjson", "title": "Converts preprocessing item from 'prep.alsbasecorr' method to JSON elements", "topics": [ "prep.alsbasecorr.asjson" ] }, { "page": "prep.alsbasecorr.fromjson", "title": "Converts JSON elements to preprocessing item for 'prep.alsbasecorr' method", "topics": [ "prep.alsbasecorr.fromjson" ] }, { "page": "prep.apply", "title": "Applies a list with preprocessing methods to a dataset", "topics": [ "prep.apply" ] }, { "page": "prep.asjson", "title": "Converts preprocessing model to JSON elements.", "topics": [ "prep.asjson" ] }, { "page": "prep.autoscale", "title": "Autoscale values", "topics": [ "prep.autoscale" ] }, { "page": "prep.center", "title": "Centering data columns.", "topics": [ "prep.center" ] }, { "page": "prep.center.asjson", "title": "Converts preprocessing item from 'prep.center' method to JSON elements", "topics": [ "prep.center.asjson" ] }, { "page": "prep.center.fromjson", "title": "Converts JSON elements to preprocessing item for 'prep.center' method", "topics": [ "prep.center.fromjson" ] }, { "page": "prep.center.params", "title": "Precomputes parameters for centering", "topics": [ "prep.center.params" ] }, { "page": "prep.emsc", "title": "Applies Extended Multiplicative Scatter Correction to data rows", "topics": [ "prep.emsc" ] }, { "page": "prep.emsc.asjson", "title": "Converts preprocessing item from 'prep.emsc' method to JSON elements", "topics": [ "prep.emsc.asjson" ] }, { "page": "prep.emsc.fromjson", "title": "Converts JSON elements to preprocessing item for 'prep.emsc' method", "topics": [ "prep.emsc.fromjson" ] }, { "page": "prep.emsc.params", "title": "Precomputes parameters for EMSC", "topics": [ "prep.emsc.params" ] }, { "page": "prep.fit", "title": "Fits preprocessing model", "topics": [ "prep.fit" ] }, { "page": "prep.fromjson", "title": "Converts JSON string to preprocessing model", "topics": [ "prep.fromjson" ] }, { "page": "prep.generic", "title": "Generic function for preprocessing", "topics": [ "prep.generic" ] }, { "page": "prep.list", "title": "Shows information about all implemented preprocessing methods.", "topics": [ "prep.list" ] }, { "page": "prep.msc", "title": "Multiplicative Scatter Correction transformation", "topics": [ "prep.msc" ] }, { "page": "prep.norm", "title": "Normalization", "topics": [ "prep.norm" ] }, { "page": "prep.norm.asjson", "title": "Converts preprocessing item from 'prep.norm' method to JSON elements", "topics": [ "prep.norm.asjson" ] }, { "page": "prep.norm.fromjson", "title": "Converts JSON elements to preprocessing item for 'prep.norm' method", "topics": [ "prep.norm.fromjson" ] }, { "page": "prep.norm.params", "title": "Precomputes parameters for normalization", "topics": [ "prep.norm.params" ] }, { "page": "prep.ref2km", "title": "Kubelka-Munk transformation", "topics": [ "prep.ref2km" ] }, { "page": "prep.savgol", "title": "Savitzky-Golay filter", "topics": [ "prep.savgol" ] }, { "page": "prep.savgol.asjson", "title": "Converts preprocessing item from 'prep.savgol' method to JSON elements", "topics": [ "prep.savgol.asjson" ] }, { "page": "prep.savgol.fromjson", "title": "Converts JSON elements to preprocessing item for 'prep.savgol' method", "topics": [ "prep.savgol.fromjson" ] }, { "page": "prep.savgol.params", "title": "Precomputes parameters for Savitzky-Golay", "topics": [ "prep.savgol.params" ] }, { "page": "prep.scale", "title": "Scaling data columns.", "topics": [ "prep.scale" ] }, { "page": "prep.scale.asjson", "title": "Converts preprocessing item from 'prep.scale' method to JSON elements", "topics": [ "prep.scale.asjson" ] }, { "page": "prep.scale.fromjson", "title": "Converts JSON elements to preprocessing item for 'prep.scale' method", "topics": [ "prep.scale.fromjson" ] }, { "page": "prep.scale.params", "title": "Precomputes parameters for scaling", "topics": [ "prep.scale.params" ] }, { "page": "prep.snv", "title": "Standard Normal Variate transformation", "topics": [ "prep.snv" ] }, { "page": "prep.spikes", "title": "Remove spikes from Raman spectra", "topics": [ "prep.spikes" ] }, { "page": "prep.spikes.asjson", "title": "Converts preprocessing item from 'prep.spikes' method to JSON elements", "topics": [ "prep.spikes.asjson" ] }, { "page": "prep.spikes.fromjson", "title": "Converts JSON elements to preprocessing item for 'prep.spikes' method", "topics": [ "prep.spikes.fromjson" ] }, { "page": "prep.transform", "title": "Transformation", "topics": [ "prep.transform" ] }, { "page": "prep.varsel", "title": "Variable selection", "topics": [ "prep.varsel" ] }, { "page": "prep.varsel.asjson", "title": "Converts preprocessing item from 'prep.varsel' method to JSON elements", "topics": [ "prep.varsel.asjson" ] }, { "page": "prep.varsel.fromjson", "title": "Converts JSON elements to preprocessing item for 'prep.varsel' method", "topics": [ "prep.varsel.fromjson" ] }, { "page": "preparePlotData", "title": "Take dataset and prepare them for plot", "topics": [ "preparePlotData" ] }, { "page": "prepCalData", "title": "Prepares calibration data", "topics": [ "prepCalData" ] }, { "page": "print.classres", "title": "Print information about classification result object", "topics": [ "print.classres" ] }, { "page": "print.ddsimca", "title": "Print method for DD-SIMCA model object", "topics": [ "print.ddsimca" ] }, { "page": "print.ddsimcares", "title": "Print method for DD-SIMCA results", "topics": [ "print.ddsimcares" ] }, { "page": "print.ipls", "title": "Print method for iPLS", "topics": [ "print.ipls" ] }, { "page": "print.ldecomp", "title": "Print method for linear decomposition", "topics": [ "print.ldecomp" ] }, { "page": "print.mcrals", "title": "Print method for mcrals object", "topics": [ "print.mcrals" ] }, { "page": "print.mcrpure", "title": "Print method for mcrpure object", "topics": [ "print.mcrpure" ] }, { "page": "print.pca", "title": "Print method for PCA model object", "topics": [ "print.pca" ] }, { "page": "print.pcares", "title": "Print method for PCA results object", "topics": [ "print.pcares" ] }, { "page": "print.pls", "title": "Print method for PLS model object", "topics": [ "print.pls" ] }, { "page": "print.plsda", "title": "Print method for PLS-DA model object", "topics": [ "print.plsda" ] }, { "page": "print.plsdares", "title": "Print method for PLS-DA results object", "topics": [ "print.plsdares" ] }, { "page": "print.plsres", "title": "print method for PLS results object", "topics": [ "print.plsres" ] }, { "page": "print.prepmodel", "title": "Print the information about methods in the preprocessing model.", "topics": [ "print.prepmodel" ] }, { "page": "print.randtest", "title": "Print method for randtest object", "topics": [ "print.randtest" ] }, { "page": "print.regcoeffs", "title": "print method for regression coefficients class", "topics": [ "print.regcoeffs" ] }, { "page": "print.regmodel", "title": "Print method for regression model object", "topics": [ "print.regmodel" ] }, { "page": "print.regres", "title": "print method for regression results object", "topics": [ "print.regres" ] }, { "page": "print.simca", "title": "Print method for SIMCA model object", "topics": [ "print.simca" ] }, { "page": "print.simcam", "title": "Print method for SIMCAM model object", "topics": [ "print.simcam" ] }, { "page": "print.simcamres", "title": "Print method for SIMCAM results object", "topics": [ "print.simcamres" ] }, { "page": "print.simcares", "title": "Print method for SIMCA results object", "topics": [ "print.simcares" ] }, { "page": "processLimType", "title": "Make correction to limit types names.", "topics": [ "processLimType" ] }, { "page": "processMembers", "title": "Computes classification outcomes for target class members.", "topics": [ "processMembers" ] }, { "page": "processStrangers", "title": "Computes classification outcomes for members of non-target classes.", "topics": [ "processStrangers" ] }, { "page": "randtest", "title": "Randomization test for PLS regression", "topics": [ "randtest" ] }, { "page": "readJSON", "title": "Reads models from JSON file made in web-application (mda.tools).", "topics": [ "readJSON" ] }, { "page": "regcoeffs", "title": "Regression coefficients", "topics": [ "regcoeffs" ] }, { "page": "regcoeffs.getStats", "title": "Distribution statistics for regression coefficients", "topics": [ "regcoeffs.getStats" ] }, { "page": "regres", "title": "Regression results", "topics": [ "regres" ] }, { "page": "regres.bias", "title": "Prediction bias", "topics": [ "regres.bias" ] }, { "page": "regres.err", "title": "Error of prediction", "topics": [ "regres.err" ] }, { "page": "regres.r2", "title": "Determination coefficient", "topics": [ "regres.r2" ] }, { "page": "regres.rmse", "title": "RMSE", "topics": [ "regres.rmse" ] }, { "page": "regres.slope", "title": "Slope", "topics": [ "regres.slope" ] }, { "page": "regress.addattrs", "title": "Add names and attributes to matrix with statistics", "topics": [ "regress.addattrs" ] }, { "page": "repmat", "title": "Replicate matrix x", "topics": [ "repmat" ] }, { "page": "selectCompNum", "title": "Select optimal number of components for a model", "topics": [ "selectCompNum" ] }, { "page": "selectCompNum.pca", "title": "Select optimal number of components for PCA model", "topics": [ "selectCompNum.pca" ] }, { "page": "selectCompNum.pls", "title": "Select optimal number of components for PLS model", "topics": [ "selectCompNum.pls" ] }, { "page": "selratio", "title": "Selectivity ratio calculation", "topics": [ "selratio" ] }, { "page": "setDistanceLimits", "title": "Set residual distance limits", "topics": [ "setDistanceLimits" ] }, { "page": "setDistanceLimits.pca", "title": "Compute and set statistical limits for Q and T2 residual distances.", "topics": [ "setDistanceLimits.pca" ] }, { "page": "setDistanceLimits.pls", "title": "Compute and set statistical limits for residual distances.", "topics": [ "setDistanceLimits.pls" ] }, { "page": "setParams", "title": "Set model parameters other than number of components (generic function)", "topics": [ "setParams" ] }, { "page": "setParams.ddsimca", "title": "Set default parameters for the DD-SIMCA model.", "topics": [ "setParams.ddsimca" ] }, { "page": "showDistanceLimits", "title": "Show residual distance limits", "topics": [ "showDistanceLimits" ] }, { "page": "showLabels", "title": "Show labels on plot", "topics": [ "showLabels" ] }, { "page": "showPredictions", "title": "Predictions", "topics": [ "showPredictions" ] }, { "page": "showPredictions.classres", "title": "Show predicted class values", "topics": [ "showPredictions.classres" ] }, { "page": "simca", "title": "SIMCA one-class classification", "topics": [ "simca" ] }, { "page": "simcam", "title": "SIMCA multiclass classification", "topics": [ "simcam" ] }, { "page": "simcam.getPerformanceStats", "title": "Performance statistics for SIMCAM model", "topics": [ "simcam.getPerformanceStats" ] }, { "page": "simcamres", "title": "Results of SIMCA multiclass classification", "topics": [ "simcamres" ] }, { "page": "simcares", "title": "Results of SIMCA one-class classification", "topics": [ "simcares" ] }, { "page": "simdata", "title": "Spectral data of polyaromatic hydrocarbons mixing", "topics": [ "simdata" ] }, { "page": "splitExcludedData", "title": "Split the excluded part of data", "topics": [ "splitExcludedData" ] }, { "page": "splitPlotData", "title": "Split dataset to x and y values depending on plot type", "topics": [ "splitPlotData" ] }, { "page": "summary.classres", "title": "Summary statistics about classification result object", "topics": [ "summary.classres" ] }, { "page": "summary.ddsimca", "title": "Summary method for DD-SIMCA model object", "topics": [ "summary.ddsimca" ] }, { "page": "summary.ddsimcares", "title": "Summary method for DD-SIMCA results.", "topics": [ "summary.ddsimcares" ] }, { "page": "summary.ipls", "title": "Summary for iPLS results", "topics": [ "summary.ipls" ] }, { "page": "summary.ldecomp", "title": "Summary statistics for linear decomposition", "topics": [ "summary.ldecomp" ] }, { "page": "summary.mcrals", "title": "Summary method for mcrals object", "topics": [ "summary.mcrals" ] }, { "page": "summary.mcrpure", "title": "Summary method for mcrpure object", "topics": [ "summary.mcrpure" ] }, { "page": "summary.pca", "title": "Summary method for PCA model object", "topics": [ "summary.pca" ] }, { "page": "summary.pcares", "title": "Summary method for PCA results object", "topics": [ "summary.pcares" ] }, { "page": "summary.pls", "title": "Summary method for PLS model object", "topics": [ "summary.pls" ] }, { "page": "summary.plsda", "title": "Summary method for PLS-DA model object", "topics": [ "summary.plsda" ] }, { "page": "summary.plsdares", "title": "Summary method for PLS-DA results object", "topics": [ "summary.plsdares" ] }, { "page": "summary.plsres", "title": "summary method for PLS results object", "topics": [ "summary.plsres" ] }, { "page": "summary.prepmodel", "title": "Show summary of the preprocessing model.", "topics": [ "summary.prepmodel" ] }, { "page": "summary.randtest", "title": "Summary method for randtest object", "topics": [ "summary.randtest" ] }, { "page": "summary.regcoeffs", "title": "Summary method for regcoeffs object", "topics": [ "summary.regcoeffs" ] }, { "page": "summary.regmodel", "title": "Summary method for regression model object", "topics": [ "summary.regmodel" ] }, { "page": "summary.regres", "title": "summary method for regression results object", "topics": [ "summary.regres" ] }, { "page": "summary.simca", "title": "Summary method for SIMCA model object", "topics": [ "summary.simca" ] }, { "page": "summary.simcam", "title": "Summary method for SIMCAM model object", "topics": [ "summary.simcam" ] }, { "page": "summary.simcamres", "title": "Summary method for SIMCAM results object", "topics": [ "summary.simcamres" ] }, { "page": "summary.simcares", "title": "Summary method for SIMCA results object", "topics": [ "summary.simcares" ] }, { "page": "unmix.mcrpure", "title": "Unmix spectral data using pure variables estimated before", "topics": [ "unmix.mcrpure" ] }, { "page": "vipscores", "title": "VIP scores for PLS model", "topics": [ "vipscores" ] }, { "page": "writeCSV", "title": "Method to write outcomes of any result object to CSV file", "topics": [ "writeCSV" ] }, { "page": "writeCSV.ddsimcares", "title": "Save DD-SIMCA results to CSV file", "topics": [ "writeCSV.ddsimcares" ] }, { "page": "writeCSV.pcares", "title": "Save PCA results to CSV file", "topics": [ "writeCSV.pcares" ] }, { "page": "writeCSV.plsres", "title": "Save PLS results to CSV file", "topics": [ "writeCSV.plsres" ] }, { "page": "writeJSON", "title": "Save model as JSON file", "topics": [ "writeJSON" ] }, { "page": "writeJSON.ddsimca", "title": "Saves DD-SIMCA model as JSON file compatible with web-application (https://mda.tools/ddsimca).", "topics": [ "writeJSON.ddsimca" ] }, { "page": "writeJSON.pca", "title": "Saves PCA model as JSON file compatible with web-application (https://mda.tools/pca).", "topics": [ "writeJSON.pca" ] }, { "page": "writeJSON.pls", "title": "Saves PLS model as JSON file compatible with web-application (https://mda.tools/pls).", "topics": [ "writeJSON.pls" ] }, { "page": "writeJSON.prepmodel", "title": "Saves preprocessing model to JSON file which can be loaded to web-application (mda.tools/prep).", "topics": [ "writeJSON.prepmodel" ] } ], "_readme": "https://github.com/svkucheryavski/mdatools/raw/HEAD/README.md", "_rundeps": [ "dotCall64", "pcv", "Rcpp", "spam" ], "_score": 7.759957901837792, "_indexed": true, "_nocasepkg": "mdatools", "_universes": [ "svkucheryavski" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "0.15.0", "date": "2026-06-04T07:37:38.000Z", "distro": "noble", "commit": "b35fcbffdc1dfffcdd8ff8b72d2a5a240eebb56f", "fileid": "e1ed3b8bd1f3ba18bffdabf05a37d6721a74060c599127de99f9cb8b5cdb39ff", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/svkucheryavski/actions/runs/26937648059" }, { "r": "4.6.0", "os": "linux", "version": "0.15.0", "date": "2026-06-04T07:38:13.000Z", "distro": "noble", "commit": "b35fcbffdc1dfffcdd8ff8b72d2a5a240eebb56f", "fileid": "e145f581dcb98b6a8d995ab2e348a96bf21da9fc69c4356046f53ba93c4d4235", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/svkucheryavski/actions/runs/26937648059" }, { "r": "4.5.3", "os": "mac", "version": "0.15.0", "date": "2026-06-04T07:37:47.000Z", "commit": "b35fcbffdc1dfffcdd8ff8b72d2a5a240eebb56f", "fileid": "298039bb3ee92f1d8441d301b05f92c6196265d65e166813660951f1fe293a2f", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/svkucheryavski/actions/runs/26937648059" }, { "r": "4.6.0", "os": "mac", "version": "0.15.0", "date": "2026-06-04T07:38:06.000Z", "commit": "b35fcbffdc1dfffcdd8ff8b72d2a5a240eebb56f", "fileid": "013b2f73154934f9d47532607cca6ab08dd58d43af0259ed29450d921e971ea3", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/svkucheryavski/actions/runs/26937648059" }, { "r": "4.6.0", "os": "wasm", "version": "0.15.0", "date": "2026-06-04T07:37:36.000Z", "commit": "b35fcbffdc1dfffcdd8ff8b72d2a5a240eebb56f", "fileid": "de66bfa2f269ed7c0b03dbf611cf5b367a7ea2fe1bb4fd37c17b8d696aa77c4d", "status": "success", "buildurl": "https://github.com/r-universe/svkucheryavski/actions/runs/26937648059" }, { "r": "4.7.0", "os": "win", "version": "0.15.0", "date": "2026-06-04T07:36:52.000Z", "commit": "b35fcbffdc1dfffcdd8ff8b72d2a5a240eebb56f", "fileid": "26f9f694f48934b7506dcbcbeae72021c8b402ce849064740850cbfc2e1bef06", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/svkucheryavski/actions/runs/26937648059" }, { "r": "4.5.3", "os": "win", "version": "0.15.0", "date": "2026-06-04T07:37:30.000Z", "commit": "b35fcbffdc1dfffcdd8ff8b72d2a5a240eebb56f", "fileid": "27c70ba588ba029391fe7bc044978d0cae24454f6ac229380646d423df830ee4", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/svkucheryavski/actions/runs/26937648059" }, { "r": "4.6.0", "os": "win", "version": "0.15.0", "date": "2026-06-04T07:36:47.000Z", "commit": "b35fcbffdc1dfffcdd8ff8b72d2a5a240eebb56f", "fileid": "8f3d4c33602ee6efad95221bb988543097ff17f2dfaaef06dab3c70a69c195b4", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/svkucheryavski/actions/runs/26937648059" } ] }