Package: r6qualitytools 1.0.1.9000

Fabian Encarnacion

r6qualitytools: R6-Based Statistical Methods for Quality Science

A comprehensive suite of statistical tools for Quality Management, designed around the Define, Measure, Analyze, Improve, and Control (DMAIC) cycle used in Six Sigma methodology. Based on the discontinued CRAN package 'qualitytools', this package refactors its original design by incorporating 'R6' object-oriented programming for increased flexibility and performance. It replaces traditional graphics with modern, interactive visualizations using 'ggplot2' and 'plotly'. Built on 'tidyverse' principles, it simplifies data manipulation and visualization, offering an intuitive approach to quality science.

Authors:Andrea Barahona [aut], Fabian Encarnacion [aut, cre, cph], Miguel Flores [aut], Javier Tarrio-Saavedra [ctb], Salvador Naya [ctb]

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r6qualitytools.pdf |r6qualitytools.html✨
r6qualitytools/json (API)
NEWS

# Install 'r6qualitytools' in R:
install.packages('r6qualitytools', repos = c('https://fabianenc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/fabianenc/r6qualitytools/issues

On CRAN:

3.48 score 2 stars 3 scripts 254 downloads 72 exports 76 dependencies

Last updated 5 months agofrom:2f61dfd4e4. Checks:8 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 01 2025
R-4.5-winOKFeb 01 2025
R-4.5-macOKFeb 01 2025
R-4.5-linuxOKFeb 01 2025
R-4.4-winOKFeb 01 2025
R-4.4-macOKFeb 01 2025
R-4.3-winOKFeb 01 2025
R-4.3-macOKFeb 01 2025

Exports:adSimaliasTableas.data.frame_facDesignblockingcgcg_HistChartcg_RunChartcg_ToleranceChartcode2realconfoundscontourPlotcontourPlot3desirabilitydesirability.cdesOptdgamma3DistrDistrCollectiondistributiondlnorm3doeFactordotPlotdweibull3facDesignfacDesign.cFitDistrfracChoosefracDesigngageLingageLinDesigngageRRgageRR.cgageRRDesigninteractionPlotmixDesignmixDesign.cMSALinearitymvPlotnormalPlotoaChooseoptimumoverallparetoChartparetoPlotpbDesignpbDesign.cpbFactorpcrpgamma3plnorm3ppPlotprint_adtestpweibull3qgamma3qlnorm3qqPlotqweibull3randomizersmChoosersmDesignsimProcsnPlotstarDesignsteepAscentsteepAscent.csummaryFitstaguchiChoosetaguchiDesigntaguchiDesign.ctaguchiFactorwirePlotwirePlot3

Dependencies:askpassbase64encbslibcachemclicolorspacecpp11crosstalkcurldata.tabledigestdplyrEnvStatsevaluatefansifarverfastmapfontawesomefsgenericsggplot2gluegridExtragtablehighrhtmltoolshtmlwidgetshttrisobandjquerylibjsonliteknitrlabelinglaterlatticelazyevallifecyclemagrittrMASSMatrixmemoisemgcvmimemunsellnlmenortestopensslpatchworkpillarpkgconfigplotlypromisespurrrR6rappdirsRColorBrewerRcpprlangrmarkdownRsolnpsassscalesstringistringrsystibbletidyrtidyselecttinytextruncnormutf8vctrsviridisLitewithrxfunyaml

Readme and manuals

Help Manual

Help pageTopics
adSim: Bootstrap-based Anderson-Darling Test for UnivariateadSim
aliasTable: Display an alias tablealiasTable
as.data.frame_facDesign: Coerce to a data.frameas.data.frame_facDesign
blocking: Blockingblocking
cg: Function to calculate and visualize the gage capability.cg
cg_HistChartcg_HistChart
cg_RunChartcg_RunChart
cg_ToleranceChartcg_ToleranceChart
code2real: Codingcode2real
confounds: Confounded Effectsconfounds
contourPlot: Contour PlotcontourPlot
contourPlot3: Ternary plotcontourPlot3
desirability: Desirability Function.desirability
desirability-class: Class `desirability`desirability.c
desOpt-class: Class `desOpt`desOpt
dgamma3: The gamma Distribution (3 Parameter)dgamma3
Distr-class: Class `Distr`Distr
DistrCollection-class: Class `DistrCollection`DistrCollection
distribution: Distributiondistribution
dlnorm3: The Lognormal Distribution (3 Parameter)dlnorm3
doeFactor-class: Class `doeFactor`doeFactor
dotPlot: Function to create a dot plotdotPlot
dweibull3: The Weibull Distribution (3 Parameter)dweibull3
facDesignfacDesign
facDesign-class: Class `facDesign`facDesign.c
FitDistr: Maximum-likelihood Fitting of Univariate DistributionsFitDistr
fracChoose: Choosing a fractional or full factorial design from a table.fracChoose
fracDesignfracDesign
gageLin: Function to visualize and calucalte the linearity of a gage.gageLin
gageLinDesign: Function to create a object of class MSALinearity.gageLinDesign
gageRR: Gage R&R - Gage Repeatability and ReproducibilitygageRR
gageRR-class: Class `gageRR`gageRR.c
gageRRDesign: Gage R&R - Gage Repeatability and ReproducibilitygageRRDesign
interactionPlotinteractionPlot
mixDesign: Mixture DesignsmixDesign
mixDesign-class: Class `mixDesign`mixDesign.c
MSALinearity-class: Class `MSALinearity`MSALinearity
mvPlot: Function to create a multi-variable plotmvPlot
normalPlot: Normal plotnormalPlot
oaChoose: Taguchi DesignsoaChoose
optimum: Optimal factor settingsoptimum
overall: Overall Desirability.overall
paretoChart: Pareto ChartparetoChart
paretoPlotparetoPlot
pbDesign: Plackett-Burman DesignspbDesign
pbDesignpbDesign.c
pbFactorpbFactor
pcr: Process Capability Indicespcr
pgamma3: The gamma Distribution (3 Parameter)pgamma3
plnorm3: The Lognormal Distribution (3 Parameter)plnorm3
ppPlot: Probability Plots for various distributionsppPlot
print_adtest: Test Statisticsprint_adtest
pweibull3: The Weibull Distribution (3 Parameter)pweibull3
qgamma3: The gamma Distribution (3 Parameter)qgamma3
qlnorm3: The Lognormal Distribution (3 Parameter)qlnorm3
qqPlot: Quantile-Quantile Plots for various distributionsqqPlot
qweibull3: The Weibull Distribution (3 Parameter)qweibull3
randomize: Randomizationrandomize
rsmChoose: Choosing a response surface design from a tablersmChoose
rsmDesign: Generate a response surface design.rsmDesign
simProc: Simulated ProcesssimProc
snPlot: Signal-to-Noise-Ratio PlotssnPlot
starDesign: Axial DesignstarDesign
steepAscent: Steepest AscentsteepAscent
steepAscent-class: Class `steepAscent`steepAscent.c
summaryFits: Fit SummarysummaryFits
taguchiChoose: Taguchi DesignstaguchiChoose
taguchiDesign: Taguchi DesignstaguchiDesign
taguchiDesigntaguchiDesign.c
taguchiFactortaguchiFactor
wirePlot: 3D PlotwirePlot
wirePlot3: function to create a ternary plot (3D wire plot)wirePlot3