Description Usage Arguments Details Value References See Also Examples
The function ks.gp.weibull()
gives the values for the KS test assuming a generalized power Weibull(GPW) with shape
parameter alpha and scale parameter theta. In addition, optionally, this function
allows one to show a comparative graph between the empirical and theoretical cdfs for a specified data set.
1 2 | ks.gp.weibull(x, alpha.est, theta.est,
alternative = c("less", "two.sided", "greater"), plot = FALSE, ...)
|
x |
vector of observations. |
alpha.est |
estimate of the parameter alpha |
theta.est |
estimate of the parameter theta |
alternative |
indicates the alternative hypothesis and must be one of |
plot |
Logical; if TRUE, the cdf plot is provided. |
... |
additional arguments to be passed to the underlying plot function. |
The Kolmogorov-Smirnov test is a goodness-of-fit technique based on the maximum distance between the empirical and theoretical cdfs.
The function ks.gp.weibull()
carries out the KS test for the generalized power Weibull(GPW)
Nikulin, M. and Haghighi, F. (2006). A Chi-squared test for the generalized power Weibull family for the head-and-neck cancer censored data, Journal of Mathematical Sciences, Vol. 133(3), 1333-1341.
Pham, H. and Lai, C.D. (2007). On recent generalizations of the Weibull distribution, IEEE Trans. on Reliability, Vol. 56(3), 454-458.
pp.gp.weibull
for PP
plot and qq.gp.weibull
for QQ
plot
1 2 3 4 5 6 7 | ## Load data sets
data(repairtimes)
## Maximum Likelihood(ML) Estimates of alpha & theta for the data(repairtimes)
## Estimates of alpha & theta using 'maxLik' package
## alpha.est = 1.566093, theta.est = 0.355321
ks.gp.weibull(repairtimes, 1.566093, 0.355321, alternative = "two.sided", plot = TRUE)
|
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