est_sigma: Estimate the covariance matrix Sigma = C(A otimes B)C using...

Description Usage Arguments Value

View source: R/functions.R

Description

Estimate the covariance matrix Sigma = C(A otimes B)C using kpcor or MN algorithm

Usage

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est_sigma(E, r, type = "kpcor", restr = "N", tol = 1e-16,
  maxiter = 1000, verbose = FALSE)

Arguments

E

Matrix of dimension rc x n, each column is a (vectorized) residual vector

r

The number of "rows" of the inverse vectorized columns of E

type

One of "kpcor" and "mn", indicating which algorithm to use

restr

Allows the user to impose the matrix A or B to be diagonal. "N" for no restriction, "A" for diagonal A, "B" for diagonal B, and "AB" for both (only for kpcor).

tol

Algorithm terminates when an iteration increases the log-likelihood less than tol

maxiter

The maximum number of iterations the algorithm runs if not converging before

verbose

Print additional info about iterates if TRUE (only for kpcor)

Value

List with MLEs of the parameters A, B and D (D = inv(C), only for kpcor), log-likelihood at the final iterates, and the numver of iterations performed.


koekvall/crkr documentation built on April 18, 2018, 11:17 p.m.