KSgof2 {Dogoftest} | R Documentation |
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
)
Arguments
x |
Numeric vector of observations. |
dist |
Character string specifying the distribution to test against.
One of |
... |
Additional parameters passed to the distribution’s cumulative distribution function (CDF).
For example, |
eps |
Numeric lower and upper bound for tail probabilities to avoid numerical issues (default: |
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.
Value
An object of class "htest"
containing the test statistic, p-value, method description, and data name.
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)