Performs Tests for the structure of covariance matrices.

Ahmad2015(x, Sigma = "identity", ...)

Chen2010(x, Sigma = "identity", ...)

Fisher2012(x, Sigma = "identity", ...)

LedoitWolf2002(x, Sigma = "identity", ...)

Nagao1973(x, Sigma = "identity", ...)

Srivastava2005(x, Sigma = "identity", ...)

Srivastava2011(x, Sigma = "identity", ...)

## Arguments

x data as a list of matrices Population covariance matrix as a matrix other options passed to covTest method

## Value

A list with class "htest" containing the following components:

 statistic the value of equality of covariance test statistic parameter the degrees of freedom for the chi-squared statistic p.value the p=value for the test estimate the estimated covariances if less than 5 dimensions null.value the specified hypothesized value of the covariance difference alternative a character string describing the alternative hyposthesis method a character string indicating what type of equality of covariance test was performed data.name a character string giving the names of the data

## References

Ahmad, M. R. and Rosen, D. von. (2015). Tests for High-Dimensional Covariance Matrices Using the Theory of U-statistics. Journal of Statistical Computation and Simulation, 85(13), 2619-2631. 10.1080/00949655.2014.948441

Chen, S., et al. (2010). Tests for High-Dimensional Covariance Matrices. Journal of the American Statistical Association, 105(490):810-819. 10.1198/jasa.2010.tm09560

Fisher, T. J. (2012). On Testing for an Identity Covariance Matrix when the Dimensionality Equals or Exceeds the Sample Size. Journal of Statistical Planning and Infernece, 142(1), 312-326. 10.1016/j.jspi.2011.07.019

Ledoit, O., and Wolf, M. (2002). Some Hypothesis Tests for the Covariance Matrix When the Dimension Is Large Compared to the Sample Size. The Annals of Statistics, 30(4), 1081-1102. 10.1214/aos/1031689018

Nagao, H. (1973). On Some Test Criteria for Covariance Matrix. The Annals of Statistics, 1(4), 700-709

Srivastava, M. S. (2005). Some Tests Concerning the Covariance Matrix in High Dimensional Data. Journal of the Japan Statistical Society, 35(2), 251-272. 10.14490/jjss.35.251

Srivastava, M. S., Kollo, T., and Rosen, D. von. (2011). Some Tests for the Covariance Matrix with Fewer Observations then the Dimension Under Non-normality. Journal of Multivariate Analysis, 102(6), 1090-1103. 10.1016/j.jmva.2011.03.003

Other Testing for Structure of Covariance Matrices: structureCovariances

## Examples

Chen2010(as.matrix(iris[1:50, 1:3]))#>
#> 	Chen et al. 2010 Test of Covariance Matrix Structure
#>
#> data:
#> Standard Normal = -180.68, Mean = 0, Variance = 1, p-value < 2.2e-16
#> alternative hypothesis: true difference between the Sample Covariance Matrix and the Null Covariance Matrix Structure is not equal to 0
#> sample estimates:
#>              Sepal.Length Sepal.Width Petal.Length
#> Sepal.Length   0.12424898  0.09921633   0.01635510
#> Sepal.Width    0.09921633  0.14368980   0.01169796
#> Petal.Length   0.01635510  0.01169796   0.03015918
#>