ks.weibull.ext: Test of Kolmogorov-Smirnov for the Weibull Extension(WE)...

In reliaR: Package for some probability distributions.

Description

The function ks.weibull.ext() gives the values for the KS test assuming a Weibull Extension(WE) 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.weibull.ext(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.

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.weibull.ext() carries out the KS test for the Weibull Extension(WE)

References

Tang, Y., Xie, M. and Goh, T.N., (2003). Statistical analysis of a Weibull extension model, Communications in Statistics: Theory & Methods 32(5):913-928.

Zhang, T., and Xie, M.(2007). Failure Data Analysis with Extended Weibull Distribution, Communications in Statistics-Simulation and Computation, 36(3), 579-592.

See Also

pp.weibull.ext for PP plot and qq.weibull.ext for QQ plot

Examples

## Load data sets
data(sys2)
## Maximum Likelihood(ML) Estimates of alpha & beta for the data(sys2)
## Estimates of alpha & beta using 'maxLik' package
## alpha.est = 0.00019114, beta.est = 0.14696242

ks.weibull.ext(sys2, 0.00019114, 0.14696242, alternative = "two.sided", plot = TRUE)

Example output

	One-sample Kolmogorov-Smirnov test

data:  x
D = 0.058416, p-value = 0.9142
alternative hypothesis: two-sided

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