Description Usage Arguments Details Value References See Also Examples
The function ks.log.gamma()
gives the values for the KS test assuming a log-gamma(LG) 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.
1 2 | ks.log.gamma(x, alpha.est, lambda.est,
alternative = c("less", "two.sided", "greater"), plot = FALSE, ...)
|
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 |
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.log.gamma()
carries out the KS test for the log-gamma(LG)
Klugman, S., Panjer, H. and Willmot, G. (2004). Loss Models: From Data to Decisions, 2nd ed., New York, Wiley.
Lawless, J. F., (2003). Statistical Models and Methods for Lifetime Data, 2nd ed., John Wiley and Sons, New York.
pp.log.gamma
for PP
plot and qq.log.gamma
for QQ
plot
1 2 3 4 5 6 7 | ## Load data sets
data(conductors)
## Maximum Likelihood(ML) Estimates of alpha & lambda for the data(conductors)
## Estimates of alpha & lambda using 'maxLik' package
## alpha.est = 0.0088741, lambda.est = 0.6059935
ks.log.gamma(conductors, 0.0088741, 0.6059935, alternative = "two.sided", plot = TRUE)
|
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