v.test: Kuiper test
In truncgof: GoF tests allowing for left truncated data

Description Usage Arguments Details Value References See Also Examples

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

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

`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`.

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-).

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

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

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.

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)

Loading required package: MASS

Attaching package: 'truncgof'

The following object is masked from 'package:stats':

    ks.test


	Kuiper Test

data:  xt
V = 0.62095, p-value = 1
alternative hypothesis: NA

treshold = 10, simulations: 100