AndersonDarling {MissMech} | R Documentation |
K-Sample Anderson Darling Test
Description
This is a non-parametric K-sample test that tests equality of distribution of a variable between k populations based on samples from each of the populations.
Usage
AndersonDarling(data, number.cases)
Arguments
data |
A single vector consisting of concatenation of the k samples data being used for the test. |
number.cases |
A vector consisting of the number of cases in samples 1, 2, ..., k, respectively. |
Details
The data is a vector including all the k samples to be used for the test. The j-th element of number.cases is the number of cases in sample j (included in data), for j= 1,...,k.
Value
pn |
The test's p-value. |
adk.all |
The Anderson Darling test statistic corresponding to each group. |
adl |
The sum of elements of adk.all. |
var.sdk |
The variance of the finite sample distribution of the Anderson Darling test statistic under the null. |
Note
The test does not adjust for tie observations.
Author(s)
Mortaza Jamshidian, Siavash Jalal, and Camden Jansen
References
Scholz, F.W. and Stephens, M.A. (1987). ”K-Sample Anderson-Darling Tests,”Journal of the American Statistical Association, 82, 918-924, doi:10.2307/2288805.
Examples
#---- Example 1
set.seed(50)
n1 <- 30
n2 <- 45
n3 <- 60
v1 <- rnorm(n1)
v2 <- runif(n2)
v3 <- rnorm(n3, 2, 3)
AndersonDarling(data = c(v1, v2, v3), number.cases=c(n1, n2, n3))
#---- Example 2
set.seed(50)
n1 <- 30
n2 <- 45
n3 <- 60
v1 <- rt(n1,4)
v2 <- rt(n2,4)
v3 <- rt(n3,4)
AndersonDarling(data=c(v1, v2, v3), number.cases=c(n1, n2, n3))