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WeibullR (version 1.0.12)

Weibull Analysis for Reliability Engineering

Description

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) .

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Version

Install

install.packages('WeibullR')

Monthly Downloads

360

Version

1.0.12

License

GPL (>= 3)

Maintainer

Jacob T Ormerod

Last Published

November 25th, 2019

Functions in WeibullR (1.0.12)

Quick Fit, Median rank regression for weibull distribution in 3-parameters

Quick Fit, Median rank regression for log-normal distribution with third parameter optimization

Transform Probability Value to the Y-Axis of a "plot.wblr" Canvas

getPercentilePlottingPositions

Determination of percentile plotting positions for linear regression with many optional methods

Options list for wblr Objects

Alias for getPercentilePlottingPositions, sets data into the format required by lslr.

Quick Fit, Maximum Likelihood Estimate for 2-parameter weibull distributions

Quick Fit, Median rank regression for 2-parameter log-normal distributions

Pivotal 'Monte Carlo' re-sampling of least squares linear regression models

Quick Fit, Maximum Likelihood Estimation for weibull distribution in 3-parameters

WeibullR-package

Weibull-R : Weibull Analysis on R

Pivotal (Parametric Bootstrap) Rank Regression Bounds for the 3-Parameter Weibull

Quick Fit, Median rank regression for 2-parameter weibull distributions

S3 Likelihood Ratio Contour Maps From wblr Objects

Add Fit Distributions to wblr Objects

Add Confidence Interval Bounds to wblr Objects

S3 wblr Object Plotting on pretty canvax

Set life(time) data into the format required by mlefit

Create a wblr Object for Life Data Analysis

Maximum likelihood regression on Weibull and Lognormal distributions

Reduced Bias Adjustment for Weibull and Lognormal MLE

Log likelihood for Weibull and Lognormal fitted data including intervals

Fitting for Minimal Failure Datasets

Plotting of Likelihood Ratio Contours from wblr Objects

Determination of the square of the "Critical Correlation Coefficient" (CCC2).

Hirose and Ross beta unbias factors for Weibull MLE

Least squares linear regression with many optional methods

Fitting for Minimal Failure Datasets using likelihood optimization

Extract a Fit Summary from a wblr Object

Beta Binomial Bounds

Log Likelihood for log-normal fitted data, failures and suspensions only

Fisher Matrix bounds

Quick Fit, Maximum Likelihood Estimate for 3-parameter lognormal distributions

Determination of the percentile of r and r-squared, by correlation. Here designated "Abernethy's P-value"

Quick Fit, Maximum Likelihood Estimate for 2-parameter lognormal distributions

Likelihood Ratio Contour for Weibull and Lognormal Fitted Data

Log Likelihood for weibull fitted data, failures and suspensions only

Likelihood Ratio bounds