# maovjames: Multivariate analysis of variance (James test) In Compositional: Compositional Data Analysis

## Description

Multivariate analysis of variance without assuming equality of the covariance matrices.

## Usage

 `1` ```maovjames(x, ina, a = 0.05) ```

## Arguments

 `x` A matrix containing Euclidean data. `ina` A numerical or factor variable indicating the groups of the data. `a` The significance level, set to 0.005 by default.

## Details

Multivariate analysis of variance without assuming equality of the covariance matrices.

## Value

A vector with the next 4 elements:

 `test` The test statistic. `correction` The value of the correction factor. `corr.critical` The corrected critical value of the chi-square distribution. `p-value` The p-value of the corrected test statistic.

## Author(s)

Michail Tsagris

R implementation and documentation: Michail Tsagris <[email protected]> and Giorgos Athineou <[email protected]>

## References

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

``` maov, hotel2T2, james, comp.test ```

## Examples

 ```1 2``` ```maov( as.matrix(iris[,1:4]), iris[,5] ) maovjames( as.matrix(iris[,1:4]), iris[,5] ) ```

### Example output

```\$note
[1] "F approximation has been used"

\$result
stat       p-value
1.991453e+02 1.365006e-112

test    correction corr.critical       p-value
6142.293071      1.096842     17.009068      0.000000
```

Compositional documentation built on March 18, 2018, 1:57 p.m.