| RobCat {MVTests} | R Documentation |
Robust CAT Algorithm
Description
RobCat computes p value based on robust CAT algorithm to compare two means vectors
under multivariate Behrens-Fisher problem.
Usage
RobCat(X, Y, M = 1000, alpha = 0.75)
Arguments
X |
a matrix or data frame for first group. |
Y |
a matrix or data frame for second group. |
M |
iteration number and the default is 1000. |
alpha |
numeric parameter controlling the size of the subsets over which the determinant is minimized; roughly alpha*n, observations are used for computing the determinant. Allowed values are between 0.5 and 1 and the default is 0.75. |
Details
This function computes p value based on robust CAT algorithm to compare two means vectors under multivariate Behrens-Fisher problem. When p value<0.05, it means the difference of two mean vectors is significant statistically.
Value
a list with 2 elements:
Cstat |
Calculated value of test statistic |
pval |
The p value |
Author(s)
Hasan BULUT <hasan.bulut@omu.edu.tr>
Examples
data(iris)
RobCat(X=iris[1:20,-5],Y=iris[81:100,-5])