cov.st: Multivariate Student's T Distribution Covariance Estimator

In abnormally-distributed/cvreg: Cross Validation and Robust Estimation Utilities

Description

Multivariate Student's T Distribution Covariance Estimator

Usage

cov.st(x, nu = NULL, wt = NULL, maxit = 100, tol = 1e-04)

Arguments

x	a data frame or matrix of numeric covariates
nu	the normality parameter. must be >= 3. lower values give more outlier resistant estimates. defaults to NULL, which estimates the parameter automatically.
wt	an optional vector of initial weights equal in length to the number of observations.
maxit	maximum number of iterations. defaults to 100.
tol	convergence tolerance. defaults to 1e-4

Value

a covRobust object containing the following elements:

• center: multivariate mean of cleaned data set after applying casewise weights.

• cov: covariance matrix of cleaned data set after applying casewise weights.

• dist: the mahalanobis distances used in calculating the weights.

• outliers: the indices of the outliers identified.

• weights: the weights for downweighting outliers.

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References

Kent, J.T., Tyler, D.E., and Vardi, Y. (1994). A curious likelihood identity for the multivariate t-distribution. Communications in Statistics—Simulation and Computation 23, 441–453.

abnormally-distributed/cvreg documentation built on May 3, 2020, 3:45 p.m.