R: James multivariate version of the t-test

James multivariate version of the t-test {Rfast} | R Documentation

## James multivariate version of the t-test

### Description

James test for testing the equality of two population mean vectors without assuming equality of the covariance matrices.

### Usage

    james(y1, y2, a = 0.05, R = 1)

### Arguments

`y1` | A matrix containing the Euclidean data of the first group.
`y2` | A matrix containing the Euclidean data of the second group.
`a` | The significance level, set to 0.05 by default.
`R` | If R is 1 the classical James test is returned. If R is 2 the MNV modficiation is implemented.

### Details

Multivariate analysis of variance without assuming equality of the covariance matrices. The p-value can be calculated either asymptotically or via bootstrap. The James test (1954) or a modification proposed by Krishnamoorthy and Yanping (2006) is implemented. The James test uses a corected chi-square distribution, whereas the modified version uses an F distribution.

### Value

A list including:

`note` | A message informing the user about the test used.
`mesoi` | The two mean vectors.
`info` | The test statistic, the p-value, the correction factor and the corrected critical value of the chi-square distribution if the James test has been used or, the test statistic, the p-value, the critical value and the degrees of freedom (numerator and denominator) of the F distribution if the modified James test has been used.

### Author(s)

Michail Tsagris

R implementation and documentation: Michail Tsagris <mtsagris@yahoo.gr>.

### References

G.S. James (1954). Tests of Linear Hypothese in Univariate and Multivariate Analysis when the Ratios of the Population Variances are Unknown. Biometrika, 41(1/2): 19-43

Krishnamoorthy K. and Yanping Xia. On Selecting Tests for Equality of Two Normal Mean Vectors (2006). Multivariate Behavioral Research 41(4): 533-548

### See Also

`mv.eeltest2`

### Examples

    james( as.matrix(iris[1:25, 1:4]), as.matrix(iris[26:50, 1:4]), R = 1 )
    james( as.matrix(iris[1:25, 1:4]), as.matrix(iris[26:50, 1:4]), R = 2 )

[Package Rfast version 2.0.0 Index]