Dogoftest (version 0.3)

KSgof2: One-sample Kolmogorov-Smirnov goodness-of-fit test

Description

Performs the one-sample Kolmogorov-Smirnov test for a specified theoretical distribution.

Usage

KSgof2(
  x,
  dist = c("norm", "exp", "unif", "lnorm", "weibull", "gamma", "t", "chisq"),
  ...,
  eps = 1e-15
)

Value

An object of class "htest" containing the test statistic, p-value, method description, and data name.

Arguments

x

Numeric vector of observations.

dist

Character string specifying the distribution to test against. One of "norm", "exp", "unif", "lnorm", "weibull", "gamma", "t", or "chisq".

...

Additional parameters passed to the distribution’s cumulative distribution function (CDF). For example, mean and sd for the normal distribution.

eps

Numeric lower and upper bound for tail probabilities to avoid numerical issues (default: 1e-15).

Details

The test compares the empirical distribution function of x with the cumulative distribution function of a specified theoretical distribution using the Kolmogorov-Smirnov statistic. For large sample sizes, a p-value approximation based on the asymptotic distribution is used.

A correction is applied when sample size exceeds 100, adjusting the test statistic to approximate a fixed sample size. For very small or very large statistics, piecewise polynomial approximations are used to compute the p-value.

Examples

set.seed(123)
x <- rnorm(1000, mean = 5, sd = 2)
KSgof2(x, dist = "norm", mean = 5, sd = 2)

y <- rexp(500, rate = 0.5)
KSgof2(y, dist = "exp", rate = 0.5)

u <- runif(300, min = 0, max = 10)
KSgof2(u, dist = "unif", min = 0, max = 10)