MLEw2p_optim: Weibull 2-parameter MLE calculation using the default Simplex...

In debias: Functions implementing MLE,its bias reduction for small samples and related issues

Description

MLEw2p_optim fits a set of data consisting of failures, or alternatively failures and suspensions, to the 2-parameter Weibull distribution.

Usage

 MLEw2p_optim(x, s=NULL, MRRfit=NULL)

Arguments

x	A vector of failure data.
s	An optional vector of suspension data.
MRRfit	An optional vector such as produced by MRRw2pxy having parameter order [1] Eta, [2] Beta. If not provided, this function will calculate a suitable estimate of Beta to initiate the optimization.

Details

This function will sort all input data while preserving failure and suspension information in paired vectors. The code is expository as it directly implements the call to optim, just as it is made via packages survival and fitdistrplus for the same purpose. The default optimization method is an implementation of the "Simplex" algorithm by Nelder and Mead (1965), which uses only function values and is robust but relatively slow.

Value

A vector containing results in the following order: Eta (scale), Beta (shape), Log-Likelihood)

References

CRAN packages fitdistrplus,survival and stats::optim.Rd

Examples

failures<-c(90,96,30,49,82)
suspensions<-c(100,45,10)
fit_result<-MLEw2p_optim(failures,suspensions)

debias documentation built on May 2, 2019, 4:49 p.m.