KScorrect-package {KScorrect}

KScorrect: Lilliefors-Corrected Kolmogorov-Smirnov Goodness-of-Fit Tests

Description

Implements the Lilliefors-corrected Kolmogorov-Smirnov test for use in goodness-of-fit tests.

Details

KScorrect implements the Lilliefors-corrected Kolmogorov-Smirnov test for use in goodness-of-fit tests, suitable when population parameters are unknown and must be estimated by sample statistics. P-values are estimated by simulation. Coded to complement ks.test, it can be used with a variety of continuous distributions, including normal, lognormal, univariate mixtures of normals, uniform, loguniform, exponential, gamma, and Weibull distributions.

Functions to generate random numbers and calculate density, distribution, and quantile functions are provided for use with the loguniform and mixture distributions.

Author(s)

Phil Novack-Gottshall [e-mail]

Steve C. Wang [e-mail]

Examples

# Get the package version and citation of KScorrect
packageVersion("KScorrect")
citation("KScorrect")

x <- runif(200)
Lc <- LcKS(x, cdf="pnorm", nreps=999)
hist(Lc$D.sim)
abline(v = Lc$D.obs, lty = 2)
print(Lc, max=50)  # Print first 50 simulated statistics
# Approximate p-value (usually) << 0.05

# Confirmation uncorrected version has increased Type II error rate when
#   using sample statistics to estimate parameters:
ks.test(x, "pnorm", mean(x), sd(x))   # p-value always larger, (usually) > 0.05

x <- rlunif(200, min=exp(1), max=exp(10)) # random loguniform sample
Lc <- LcKS(x, cdf="plnorm")
Lc$p.value      # Approximate p-value: (usually) << 0.05