rppvalue: P-values for the Test of the Probability of Ruin

In bootruin: A Bootstrap Test for the Probability of Ruin in the Classical Risk Process

Description

This function provides p-values for the test of the probability of ruin using one of two different methods.

Usage

rppvalue(x, method = c("bootstrap", "normal"), x.boot)

Arguments

x	The observed values of the test statistic as numeric vector or matrix, see Details.
method	A character string determining the method used.
x.boot	The bootstrap replications that x should be compared with, see Details.

Details

This function is not intended to be used by itself, but rather in combination with rpteststat. Hence, ideally, both x and x.boot stem from a call of the latter.

If method = "bootstrap", then bootstrap p-values are computed. The values of x are compared to those of x.boot. The number of rows of x.boot has to match the number of columns of x (or its length if it is a vector). For most applications, however, x will be a single number and x.boot will be the bootstrap replications of x

For method = "normal" the p-values are computed using the asymptotic normal approximation of the test statistic. x can be a vector, a matrix or an array of numerics.

The elements of x are interpreted as statistics of separate, independent tests, and adjusting the p-values for multiple comparison may be necessary.

Value

A numeric (vector, matrix or array) with the same dimension as x.

Note

If method = "normal", the argument x.boot is not used and a warning is issued if it is still provided.

References

Baumgartner, B. and Gatto, R. (2010) A Bootstrap Test for the Probability of Ruin in the Compound Poisson Risk Process. ASTIN Bulletin, 40(1), pp. 241–255.

See Also

See rpteststat for the computation of the test statistics, ruinprob for computating the probability of ruin, and rpjack for the computation of the standard errors.

p.adjust from the package stats provides methods to adjust p-values for multiple testing.

bootruin documentation built on May 2, 2019, 10:23 a.m.