ADgof {Dogoftest} | R Documentation |
Anderson-Darling Goodness-of-Fit Test for a Specified Distribution
Description
Performs the Anderson-Darling (AD) goodness-of-fit test for a given univariate distribution. The function computes the AD statistic and returns an approximate p-value based on adjusted formulas.
Usage
ADgof(
x,
dist = c("norm", "exp", "unif", "lnorm", "weibull", "gamma", "t", "chisq"),
...,
eps = 1e-15
)
Arguments
x |
A numeric vector of sample observations. |
dist |
A character string specifying the null distribution. Options are
|
... |
Additional named parameters passed to the corresponding distribution functions
(e.g., |
eps |
A small positive constant to avoid log(0) during computation (default: |
Details
This implementation supports several common distributions. Parameters of the null distribution
must be supplied via ...
. The p-value is calculated using the approximations suggested
by Stephens (1986) and other refinements. For small samples or custom distributions, a bootstrap
version may be preferred.
Value
A list of class "htest"
with components:
- statistic
The value of the Anderson-Darling test statistic.
- p.value
The approximate p-value computed using adjustment formulas.
- method
A description of the test performed.
- data.name
The name of the input data.
Examples
set.seed(123)
x1 <- rnorm(500, mean = 5, sd = 2)
ADgof(x1, dist = "norm", mean = 5, sd = 2)
x2 <- rexp(400, rate = 1.5)
ADgof(x2, dist = "exp")
ADgof(x2, dist = "exp", rate = 1.5)
x3 <- runif(300, min = -2, max = 4)
ADgof(x3, dist = "unif", min = -2, max = 4)