ks.gen.exp: Test of Kolmogorov-Smirnov for the Generalized...

In reliaR: Package for some probability distributions.

Description

The function ks.gen.exp() gives the values for the KS test assuming an GE 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.gen.exp(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.gen.exp() carries out the KS test for the GE.

References

Gupta, R. D. and Kundu, D. (2001). Exponentiated exponential family; an alternative to gamma and Weibull distributions. Biometrical Journal, 43(1), 117 - 130.

Gupta, R. D. and Kundu, D. (1999). Generalized exponential distributions. Australian and New Zealand Journal of Statistics, 41(2), 173 - 188.

See Also

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

Examples

## Load data sets
data(bearings)
## Estimates of alpha & lambda using 'maxLik' package
## alpha.est = 5.28321139, lambda.est = 0.03229609
ks.gen.exp(bearings, 5.28321139, 0.03229609, alternative = "two.sided", plot = TRUE)

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