ADcens {GofCens}

Anderson-Darling test for complete and right-censored data

Description

ADcens computes the Anderson-Darling test statistic and p-value for complete and right-censored data against eight possible distributions using bootstrapping.

Usage

ADcens(times, cens = rep(1, length(times)),
       distr = c("exponential", "gumbel", "weibull", "normal",
                 "lognormal", "logistic", "loglogistic", "beta"),
       betaLimits = c(0, 1), igumb = c(10, 10), degs = 3, BS = 999,
       params = list(shape = NULL, shape2 = NULL,
                     location = NULL, scale = NULL), 
       prnt = TRUE, outp = "list", tol = 1e-04)

Arguments

times

Numeric vector of times until the event of interest.

cens

Status indicator (1, exact time; 0, right-censored time). If not provided, all times are assumed to be exact.

distr

A string specifying the name of the distribution to be studied. The possible distributions are the exponential ("exponential"), the Weibull ("weibull"), the Gumbel ("gumbel"), the normal ("normal"), the lognormal ("lognormal"), the logistic ("logistic"), the loglogistic ("loglogistic"), and the beta ("beta") distribution.

betaLimits

Two-components vector with the lower and upper bounds of the Beta distribution. This argument is only required, if the beta distribution is considered.

igumb

Two-components vector with the initial values for the estimation of the Gumbel distribution parameters.

degs

Integer indicating the number of decimal places of the numeric results of the output.

BS

Number of bootstrap samples.

params

List specifying the parameters of the theoretical distribution. By default, parameters are set to NULL and estimated with the maximum likelihood method. This argument is only considered, if all parameters of the studied distribution are specified.

outp

Indicator of how the output will be displayed. The possible formats are list and table.

prnt

Logical to indicate if the estimations of the Anderson-Darling statistic and p-value should be printed. Default is TRUE.

tol

Precision of survival times.

Details

When dealing with complete data, we recommend to use the function ad.test of the goftest package.

The parameter estimation is acomplished with the fitdistcens function of the fitdistrplus package.

The precision of the survival times is important mainly in the data generation step of the bootstrap samples.

Value

If prnt = TRUE, a list containing the following components:

Distribution

Null distribution.

AD

Value of Anderson-Darling statistic.

p-value

Estimated p-value.

Parameters

List with the maximum likelihood estimates of the parameters of the distribution under study.

The list is also returned invisibly.

Warning

If the amount of data is large, the execution time of the function can be elevated. The parameter BS can limit the number of random censored samples generated and reduce the execution time.

Author(s)

K. Langohr, M. Besalú, M. Francisco, G. Gómez.

References

G. Marsaglia and J. Marsaglia. Evaluating the Aderson-Darling Distrinution. In: Journal os Statistical Software, Articles, 9 (2) (2004), 1-5.

See Also

Function ad.test (Package goftest) for complete data and function gofcens for statistics and p-value of th Kolmogorov-Smirnov, Cramér von-Mises and Anderson-Darling together for right-censored data.

Examples

# Complete data
set.seed(123)
ADcens(times = rweibull(100, 12, scale = 4), distr = "weibull",
       BS = 199)

## Not run: 
# Censored data
library(survival)
colonsamp <- colon[sample(nrow(colon), 100), ]
ADcens(colonsamp$time, colonsamp$status, distr = "normal")

## End(Not run)