prec_to_cov

The covariance matrix is the inverse of the precision matrix. By default,
the function <code>solve</code> is used for inversion. If it fails (e.g.,
singular system), then <code><a href="/link/MASS%3A%3Aginv?package=hmmTMB&version=1.0.2" data-mini-rdoc="hmmTMB::MASS::ginv">MASS::ginv</a></code> is used instead, and returns the
Moore-Penrose generalised inverse of the precision matrix.

Fitting hidden Markov models using automatic differentiation
and Laplace approximation, allowing for fast inference and flexible covariate
effects (including random effects and smoothing splines) on model parameters.
The package is described by Michelot (2022) <arXiv:2211.14139>.

Theo Michelot

hmmTMB

Fit Hidden Markov Models using Template Model Builder

Richard Glennie

prec_to_cov function

<dl><dt>prec_mat</dt>
<dd>Precision matrix (either of 'matrix' type
or sparse matrix on which as.matrix can be used)</dd></dl>

Arguments

The covariance matrix is the inverse of the precision matrix. By default,
the function <code>solve</code> is used for inversion. If it fails (e.g.,
singular system), then <code><a href='https://rdrr.io/pkg/MASS/man/ginv.html'>MASS::ginv</a></code> is used instead, and returns the
Moore-Penrose generalised inverse of the precision matrix.

Get covariance matrix from precision matrix — prec_to_cov

<dl>

<dt>prec_mat</dt>
<dd>Precision matrix (either of 'matrix' type
or sparse matrix on which as.matrix can be used)</dd>

</dl>

prec_to_cov: Get covariance matrix from precision matrix

Description

Usage

Value

Arguments