KS2gof {Dogoftest} | R Documentation |
Two-Sample Kolmogorov–Smirnov Test with Bootstrap
Description
Performs a two-sample Kolmogorov–Smirnov (KS) test using a bootstrap method to assess whether two independent samples come from the same distribution.
Usage
KS2gof(
x,
y,
alternative = c("two.sided", "less", "greater"),
nboots = 5000,
keep.boots = FALSE
)
Arguments
x , y |
Numeric vectors of data values for the two independent samples. |
alternative |
Character string specifying the alternative hypothesis,
must be one of |
nboots |
Number of bootstrap resamples used to approximate the null distribution (default: 5000). |
keep.boots |
Logical; if |
Details
This implementation performs a nonparametric KS test for equality of distributions by resampling under the null hypothesis. It supports one-sided and two-sided alternatives.
If keep.boots = TRUE
, the function returns all bootstrap statistics,
which can be used for further analysis (e.g., plotting).
If the p-value is zero due to no bootstrap statistic exceeding the observed value,
it is adjusted to 1 / (2 * nboots)
to avoid a zero p-value.
Value
An object of class "htest"
with the following components:
- statistic
The observed KS statistic.
- p.value
The p-value based on the bootstrap distribution.
- alternative
The alternative hypothesis.
- method
Description of the test used.
Examples
set.seed(123)
x <- rnorm(100, mean = 0, sd = 4)
y <- rnorm(100, mean = 2, sd = 4)
KS2gof(x, y)