v.test {truncgof}R Documentation

Kuiper test

Description

Kuiper test providing a comparison of a fitted distribution with the empirical distribution.

Usage

v.test(x, distn, fit, H = NA, sim = 100, tol = 1e-04, estfun = NA)

Arguments

x a numeric vector of data values
distn character string naming the null distribution
fit list of distribution parameters
H a treshold value
sim maximum number of szenarios in the Monte-Carlo simulation
tol if the difference of two subsequent p-value calculations is lower than tol the Monte-Carlo simulation stops
estfun an function as character string or NA (default). See mctest.

Details

The Kolmogorov-Smirnov test compares the null distribution with the empirical distribution of the observed data, where left truncated data samples are allowed. The test statistic (see ks.test) is given by KS = max(KS+, KS-).

Value

A list with class "mchtest" containing the following components

statistic the value of the Kuiper statistic
treshold the treshold value
p.value the p-value of the test
data.name a character string giving the name of the data
method the character string "Kuiper test"
sim.no number of simulated szenarios in the Monte-Carlo simulation

References

Chernobay, A., Rachev, S., Fabozzi, F. (2005), Composites goodness-of-fit tests for left-truncated loss samples, Tech. rep., University of Calivornia Santa Barbara

See Also

ks.test, ad.test, adup.test for other supremum class tests and ad2.test, ad2up.test, w2.test for quadratic class tests. For more details see mctest.

Examples

set.seed(123)
treshold <- 10
xc  <- rlnorm(100, 2, 2)     # complete sample
xt <- xc[xc >= treshold]     # left truncated sample
v.test(xt, "plnorm", list(meanlog = 2, sdlog = 2), H = 10)

[Package truncgof version 0.5-2 Index]