Ind2Variates: Independence of k Sets of Varieties
In andresfpc/AMUN: Analisis Multivariado Universidad Nacional de Colombia (AMUN)

Description Usage Arguments Value Author(s) References Examples

When the matrices of covaraince and correlation have been partitioned according with the population matrix it is recommended to use the Wilk's test but since is quite complicated there is an approximation to a Chi-square Morrison(2005).

1	Ind2Variates(S, n)

`S`	a positive define matrix which contains the whole variances and covariances
`n`	the total number of observations cover by the S matrix

`S11`	a positive define matrix related which contains the variances and covariances of the first group
`S22`	a positive define matrix related which contains the variances and covariances of the second group
`ChiSquareStatistic`	the value of the Chi Square Statistic
`DegreeOfFreedom`	total normal of degrees of freedom of the Chi Square Statistic
`pValue`	the p value of the Chi square statistic

Jesus Gonzalez <jmgonzalezf@unal.edu.co>, Andres Palacios <anfpalacioscl@unal.edu.co>, Campo Elias Pardo <cepardot@unal.edu.co>

Morrison, D. F. (2005), Multivariate statistical methods, Series in Probabilty and Statistics, 4 edn, McGraw-Hill, New York.

S <- matrix(c(1, 0.45, -0.19, 0.43,
              0.45, 1, -0.02, 0.62,
              -0.19, -0.02, 1, -0.29,
              0.43, 0.62, -0.29, 1),
            nrow = 4, byrow = TRUE)
n <- 933

Ind2Variates(S = S, n = n)