gof.bootstrap {EDFtest} R Documentation

## Generic GOF tests based on EDF using bootstrap

### Description

This function takes in an i.i.d. random sample, use MLE to estimate parameters of the assumed distribution, compute probability integral transforms, and computes Cramér-von Mises, Anderson-Darling and Watson statistics and their P-values using bootstrap method.

### Usage

gof.uniform.bootstrap(x, M = 10000)

gof.normal.bootstrap(x, M = 10000)

gof.gamma.bootstrap(x, M = 10000)

gof.logistic.bootstrap(x, M = 10000)

gof.laplace.bootstrap(x, M = 10000)

gof.weibull.bootstrap(x, M = 10000)

gof.extremevalue.bootstrap(x, M = 10000)

gof.exp.bootstrap(x, M = 10000)


### Arguments

 x A random sample. M Number of bootstrap, 10000 by default.

### Value

Cramér-von Mises, Anderson-Darling and Watson statistics and their P-values.

gof.sandwich for general distributions using Sandwich estimation of covariance function; gof for generic functions using imhof function.

### Examples

x0=runif(n=100,min=-1,max=1)
gof.uniform.bootstrap(x0,M=100)

x1=rnorm(n=100,mean=0,sd=1)
gof.normal.bootstrap(x1,M=100)

x2=rgamma(n=100,shape=1,scale=1)
gof.gamma.bootstrap(x2,M=100)

x3=rlogis(n=100,location=0,scale=1)
gof.logistic.bootstrap(x3,M=100)

x4= rmutil::rlaplace(n=100,m=0,s=1)
gof.laplace.bootstrap(x4,M=100)

x5=rweibull(n=100,shape=1,scale=1)
gof.weibull.bootstrap(x5,M=100)
x5_log=log(x5)
gof.extremevalue.bootstrap(x5_log,M=100)

x6=rexp(n=100,rate=1/2)
gof.exp.bootstrap(x6,M=100)


[Package EDFtest version 0.1.0 Index]