reliaR (version 0.01)

ks.exp.power: Test of Kolmogorov-Smirnov for the Exponential Power(EP) distribution

Description

The function ks.exp.power() gives the values for the KS test assuming an Exponential Power distribution with shape parameter alpha and scale parameter lambda. In addition, optionally, this function allows one to show a comparative graph between the empirical and theoretical cdfs for a specified data set.

Usage

ks.exp.power(x, alpha.est, lambda.est,  alternative = c("less", "two.sided", "greater"), plot = FALSE, ...)

Arguments

x

vector of observations.

alpha.est

estimate of the parameter alpha

lambda.est

estimate of the parameter lambda

alternative

indicates the alternative hypothesis and must be one of "two.sided" (default), "less", or "greater".

plot

Logical; if TRUE, the cdf plot is provided.

...

additional arguments to be passed to the underlying plot function.

Value

The function ks.exp.power() carries out the KS test for the EP.

Details

The Kolmogorov-Smirnov test is a goodness-of-fit technique based on the maximum distance between the empirical and theoretical cdfs.

References

Smith, R.M. and Bain, L.J. (1975). An exponential power life-test distribution, Communications in Statistics - Simulation and Computation, Vol. 4(5), 469-481.

See Also

pp.exp.power for PP plot and qq.exp.power for QQ plot

Examples

## Load data sets
data(sys2)
## Maximum Likelihood(ML) Estimates of alpha & lambda for the data(sys2)
## alpha.est = 0.905868898, lambda.est =  0.001531423

ks.exp.power(sys2, 0.905868898, 0.001531423, alternative = "two.sided", plot = TRUE)