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

In reliaR: Package for some probability distributions.

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.

Details

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

Value

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

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) 

reliaR documentation built on May 1, 2019, 9:51 p.m.