reliaR (version 0.01)

ks.expo.logistic: Test of Kolmogorov-Smirnov for the Exponentiated Logistic (EL) distribution

Description

The function ks.expo.logistic() gives the values for the KS test assuming a Exponentiated Logistic(EL) with shape parameter alpha and scale parameter beta. 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.expo.logistic(x, alpha.est, beta.est,  alternative = c("less", "two.sided", "greater"), plot = FALSE, ...)

Arguments

x

vector of observations.

alpha.est

estimate of the parameter alpha

beta.est

estimate of the parameter beta

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

ks.expo.logistic() carries out the KS test for the Exponentiated Logistic(EL)

Details

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

References

Ali, M.M., Pal, M. and Woo, J. (2007). Some Exponentiated Distributions, The Korean Communications in Statistics, 14(1), 93-109.

Shirke, D.T., Kumbhar, R.R. and Kundu, D. (2005). Tolerance intervals for exponentiated scale family of distributions, Journal of Applied Statistics, 32, 1067-1074

See Also

pp.expo.logistic for PP plot and qq.expo.logistic for QQ plot

Examples

## Load data sets
data(dataset2)
## Maximum Likelihood(ML) Estimates of alpha & beta for the data(dataset2)
## Estimates of alpha & beta using 'maxLik' package
## alpha.est = 5.31302, beta.est = 139.04515

ks.expo.logistic(dataset2, 5.31302, 139.04515, alternative = "two.sided", plot = TRUE)