ks.logis.exp: Test of Kolmogorov-Smirnov for the Logistic-Exponential(LE)...

In reliaR: Package for some probability distributions.

Description

The function ks.logis.exp() gives the values for the KS test assuming a Logistic-Exponential(LE) 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.logis.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.logis.exp() carries out the KS test for the Logistic-Exponential(LE)

References

Lan, Y. and Leemis, L. M. (2008). The Logistic-Exponential Survival Distribution, Naval Research Logistics, 55, 252-264.

See Also

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

Examples

## Load data sets
data(bearings)
## Maximum Likelihood(ML) Estimates of alpha & lambda for the data(bearings)
## Estimates of alpha & lambda using 'maxLik' package
## alpha.est = 2.36754, lambda.est = 0.01059

ks.logis.exp(bearings, 2.36754, 0.01059, alternative = "two.sided", plot = TRUE)

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