goftype2: Computing goodness-of-fit (GOF) measures under progressive...
In bccp: Bias Correction under Censoring Plan

Description Usage Arguments Author(s) References Examples

The goodness-of-fit (GOF) measures consist of Anderson-Darling (AD), Cramer-von Misses (CVM), and log-likelihood statistics for progressive type-II censoring scheme.

1	goftype2(plan, param, mle, cdf, pdf)

`plan`	Censoring plan for progressive type-II censoring scheme. It must be given as a `data.frame` that includes number of failed items `X`, and vector of removed items `R`.
`param`	Vector of the of the family parameter's names.
`mle`	Vector of the maximum likelihood estimators.
`cdf`	Expression for the cumulative distribution function.
`pdf`	Expression for the probability density function.

Mahdi Teimouri

R. Pakyari and N. Balakrishnan 2012. A general purpose approximate goodness-of-fit for progressively Type-II censored data, IEEE Transaction on Reliability, 61, 238-244.

     n <- 20
     R <- c(5, rep(0, n-6) )
 param <- c("alpha","beta")
   mle <- c(2,6)
   pdf <- quote( alpha/beta*(x/beta)^(alpha-1)*exp( -(x/beta)^alpha ) )
   cdf <- quote( 1-exp( -(x/beta)^alpha ) )
    lb <- 0
    ub <- Inf
  plan <- rtype2(n = n, R = R, param = param, mle = mle, cdf = cdf, lb = lb, ub = ub)
goftype2(plan = plan, param = param, mle = mle, cdf = cdf, pdf = pdf)