estparmtd: Estimation of the Parameters of a Multivariate t Distribution

In multvardiv: Multivariate Probability Distributions, Statistical Divergence

Estimation of the Parameters of a Multivariate t Distribution

Description

Estimation of the degrees of freedom, mean vector and correlation matrix of a multivariate t distribution (MTD).

Usage

estparmtd(x, eps = 1e-6, display = FALSE, plot = display)

Arguments

x	numeric matrix or data frame.
eps	numeric. Precision for the estimation of the parameters.
display	logical. When TRUE the value of the nu parameter at each iteration is printed.
plot	logical. When TRUE the successive values of the nu parameter are plotted, allowing to visualise its convergence.

Details

The EM method is used to estimate the parameters.

Value

A list of 3 elements:

• nu non-negative numeric value. The degrees of freedom.

• mu the mean vector.

• Sigma: symmetric positive-definite matrix. The correlation matrix.

with two attributes attr(, "epsilon") (precision of the result) and attr(, "k") (number of iterations).

Author(s)

Pierre Santagostini, Nizar Bouhlel

References

Doğru, F., Bulut, Y. M. and Arslan, O. (2018). Doubly reweighted estimators for the parameters of the multivariate t-distribution. Communications in Statistics - Theory and Methods. 47. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/03610926.2018.1445861")}.

See Also

dmtd: probability density of a MTD

rmtd: random generation from a MTD.

Examples

nu <- 3
mu <- c(0, 1, 4)
Sigma <- matrix(c(1, 0.6, 0.2, 0.6, 1, 0.3, 0.2, 0.3, 1), nrow = 3)
x <- rmtd(100, nu, mu, Sigma)

# Estimation of the parameters
estparmggd(x)

multvardiv documentation built on April 3, 2025, 6:08 p.m.