Package: WeibullR 1.2.1

WeibullR: Weibull Analysis for Reliability Engineering

Life data analysis in the graphical tradition of Waloddi Weibull. Methods derived from Robert B. Abernethy (2008, ISBN 0-965306-3-2), Wayne Nelson (1982, ISBN: 9780471094586), William Q. Meeker and Lois A. Escobar (1998, ISBN: 1-471-14328-6), John I. McCool, (2012, ISBN: 9781118217986).

Authors:David Silkworth [aut], Jurgen Symynck [aut], Jacob Ormerod [cre], OpenReliability.org [cph]

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WeibullR.pdf |WeibullR.html✨
WeibullR/json (API)

# Install 'WeibullR' in R:
install.packages('WeibullR', repos = c('https://jto888.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.49 score 4 packages 51 scripts 541 downloads 37 exports 2 dependencies

Last updated 2 years agofrom:06fef9b6fb. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 01 2024
R-4.5-win-x86_64NOTENov 01 2024
R-4.5-linux-x86_64NOTENov 01 2024
R-4.4-win-x86_64NOTENov 01 2024
R-4.4-mac-x86_64NOTENov 01 2024
R-4.4-mac-aarch64NOTENov 01 2024
R-4.3-win-x86_64NOTENov 01 2024
R-4.3-mac-x86_64NOTENov 01 2024
R-4.3-mac-aarch64NOTENov 01 2024

Exports:AbPvalBBBcontour.wblrFMboundsgetCCC2getPercentilePlottingPositionsgetPPPhrbuLLlnLLwLRboundslslrMLEcontourmlefitmleframeMLEln2pMLEln3pMLEw2pMLEw3pMRRln2pMRRln3pMRRw2pMRRw3poptions.wblrp2ypivotal.rrplot_contourplot.wblrrbawblrwblr.confwblr.fitwblrLoglikeweibayesweibayes.mlexboundsxfit

Dependencies:RcppRcppArmadillo

Readme and manuals

Help Manual

Help pageTopics
Weibull-R : Weibull Analysis on RWeibullR-package
Determination of the percentile of r and r-squared, by correlation. Here designated "Abernethy's P-value"AbPval
Beta Binomial BoundsBBB
S3 Likelihood Ratio Contour Maps From 'wblr' Objectscontour.wblr
Fisher Matrix boundsFMbounds
Determination of the square of the "Critical Correlation Coefficient" (CCC2).getCCC2
Determination of percentile plotting positions for linear regression with many optional methodsgetPercentilePlottingPositions
Alias for 'getPercentilePlottingPositions', sets data into the format required by lslr.getPPP
Hirose and Ross beta unbias factors for Weibull MLEhrbu
Log Likelihood for log-normal fitted data, failures and suspensions onlyLLln
Log Likelihood for weibull fitted data, failures and suspensions onlyLLw
Likelihood Ratio boundsLRbounds
Least squares linear regression with many optional methodslslr
Likelihood Ratio Contour for Weibull and Lognormal Fitted DataMLEcontour
Maximum likelihood regression on Weibull and Lognormal distributionsmlefit
Set life(time) data into the format required by mlefitmleframe
Quick Fit, Maximum Likelihood Estimate for 2-parameter lognormal distributionsMLEln2p
Quick Fit, Maximum Likelihood Estimate for 3-parameter lognormal distributionsMLEln3p
Quick Fit, Maximum Likelihood Estimate for 2-parameter weibull distributionsMLEw2p
Quick Fit, Maximum Likelihood Estimation for weibull distribution in 3-parametersMLEw3p
Quick Fit, Median rank regression for 2-parameter log-normal distributionsMRRln2p
Quick Fit, Median rank regression for log-normal distribution with third parameter optimizationMRRln3p
Quick Fit, Median rank regression for 2-parameter weibull distributionsMRRw2p
Quick Fit, Median rank regression for weibull distribution in 3-parametersMRRw3p
Options list for 'wblr' Objectsoptions.wblr
Transform Probability Value to the Y-Axis of a '"plot.wblr"' Canvasp2y
Pivotal 'Monte Carlo' re-sampling of least squares linear regression modelspivotal.rr
Plotting of Likelihood Ratio Contours from 'wblr' Objectsplot_contour
S3 'wblr' Object Plotting on pretty canvaxplot.wblr
Reduced Bias Adjustment for Weibull and Lognormal MLErba
Create a 'wblr' Object for Life Data Analysiswblr
Add Confidence Interval Bounds to 'wblr' Objectswblr.conf
Add Fit Distributions to 'wblr' Objectswblr.fit
Log likelihood for Weibull and Lognormal fitted data including intervalswblrLoglike
Fitting for Minimal Failure Datasetsweibayes
Fitting for Minimal Failure Datasets using likelihood optimizationweibayes.mle
Extract a bounds dataframe from a 'wblr' Objectxbounds
Extract a Fit Summary from a 'wblr' Objectxfit