wblr.fit: Add Fit Distributions to 'wblr' Objects

In WeibullR: Weibull Analysis for Reliability Engineering

Add Fit Distributions to wblr Objects

Description

This function fits probability distributions to wblr objects.

Usage

wblr.fit(x, modify.by.t0=FALSE, ...)

Arguments

x	Object of class "wblr".
modify.by.t0	A logical value to signifying whether to revise object data by subtraction of the "t0" (translation) parameter of a 3-parameter fit. A value of TRUE generates a linearized view of the fit on its base distribution canvas. It is recommended that the resulting object have an altered name perhaps adding a ".3p" suffix to the original wblr object to preserve original data.
...	Options for fitting the (life-)time observations, and for plotting the results.

Details

This function calculates fits for the (life-)time observations in the wblr object and adds them to the object alongside any pre-existing fits.

Fitting options are passed with the dist and method.fit arguments:

dist

A character string with the target distribution for fitting. Possible values are "weibull", "weibull2p", "weibull3p" (three parameter Weibull), "lognormal" , "lognormal2p"or "lognormal3p".

Defaults to "weibull".

in.legend

Logical value controlling the inclusion of various elements in the legend.

If in.legend=FALSE is passed, the resulting fit calculations will be omitted from the legend, leaving only observation summary data.

Defaults to TRUE.

method.fit

A vector of class "character" with fitting options.

Defaults to "rr-xony".

• "rr": Rank Regression (RR). Depending on the method for calculating probability plot positions chosen during the creation of the wblr object (see option pp and function wblr), this can either be "exact median rank regression" or "Benard's approximate median rank regression". If this method is used then it is mandatory to additionally specify either X-on-Y or Y-on-X regression.

• "xony","yonx": Differentiate between X-on-Y and Y-on-X regression, respectively. For rank regression in lifetime analysis, it is best practice to use the X values ((life-)time observations) as the response variables whose horizontal distance to the fit line must be minimized, and the Y values (unreliabilities) as the explanatory variable.

• "mle": Maximum Likelihood Estimation (MLE), using many functions of the debias package.

• "mle-rba": Maximum Likelihood Estimation with Reduced Bias Adjustment as popularized by Abernethy based on the median bias of MLE fitted distributions.

• "mle-unbias": Maximum Likelihood Estimation with bias adjustment as popularized by Reliasoft software based on the mean bias of MLE fitted distributions.

Additionally, one can pass any options available from options.wblr, such as col or is.plot.legend. The graphical options will be used when plotting the (life-)time observations using plot.wblr. Subsequent calls to wblr.conf will inherit these options.

Currently, there is no graceful error recovery after attempting to fit lifetime data including negative time observations, for example wblr.fit(wblr(-5:10)).

Value

The function returns its argument object x, extended with the calculated fit and the optional graphical and calculation arguments as provided to the function.

References

William Q. Meeker and Luis A. Escobar, (1998) "Statistical Methods for Reliability Data", Wiley-Interscience, New York

Robert B. Abernethy, (2008) "The New Weibull Handbook, Fifth Edition"

John I. McCool, (2012) "Using the Weibull Distribution: Reliability, Modeling and Inference"

Marie Laure Delignette-Muller, Christophe Dutang (2015). "fitdistrplus: An R Package for Fitting Distributions". Journal of Statistical Software, 64(4), 1-34. URL http://www.jstatsoft.org/v64/i04/.

WeibullR documentation built on June 26, 2022, 1:06 a.m.