Routines to perform estimation and inference under the multivariate t-distribution. Currently, the following methodologies are implemented: multivariate mean and covariance estimation, hypothesis testing about the mean, equicorrelation and homogeneity of variances, the Wilson-Hilferty transformation, QQ-plots with envelopes and random variate generation. Some auxiliary functions are also provided.
|Date of publication||2015-10-11 00:12:53|
|Maintainer||Felipe Osorio <firstname.lastname@example.org>|
|License||GPL (>= 2)|
center.test: One-sample location test
commutation: Commutation matrix for square matrices
companies: Financial data
cork: Cork borings
duplication: Duplication matrix
envelope: QQ-plot with simulated envelopes
equicorrelation.test: Equicorrelation test
examScor: Open/Closed book data
fisher.info: Fisher information matrix
homogeneity.test: Test of variance homogeneity of correlated variances
kurtosis: Mardia's multivariate kurtosis coefficient
mvt.control: Set control parameters
PFM: Returns from the Chilean Pension Funds
rmt: Multivariate-t random deviates
Student.family: Family object for the multivariate t-distribution
studentFit: Estimation of mean and covariance using the multivariate...
Weights: Distribution of the weights from a multivariate...
wilson.hilferty: Wilson-Hilferty transformation