weibayes: Fitting for Minimal Failure Datasets

In WeibullR: Weibull Analysis for Reliability Engineering

Fitting for Minimal Failure Datasets

Description

A simplistic fitting method also called "1-parameter Weibull" based on a "prior" known beta value.

Usage

weibayes(x, s=NULL, beta)

Arguments

x	Either a vector of class "numeric" or "integer" with (life-)time observations, or a dataframe containing at least $time and $event columns and optionally a $qty column.
s	An optional vector of suspension data.
beta	A weibull shape parameter based on prior like kind study.

Details

This function implements a very simplistic relationship defined by two lines of R code:
t_eta<-(times^beta)/nfail
out_val<-sum(t_eta)^(1/beta)
Note: for a single failure dataset, with beta = 1, the return is simply the sum of the failure time value plus sum of all suspension times. Should no failures exist, then the nfail will be set to 1 for a pessimistic solution.

Value

Returns the Weibull scale, Eta, paramater value.

Examples

fail<-5
susp<-rweibull(10, 1, 10)
eta<-weibayes(fail, susp, beta=1)

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