gdeterminant

Generalized determinant = product of non-zero eigenvalues 
(see e.g., Wood 2017). Used for (log)determinant of penalty matrices,
required in log-likelihood function.

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) <doi:10.48550/arXiv.2211.14139>.

Theo Michelot

hmmTMB

Fit Hidden Markov Models using Template Model Builder

Richard Glennie

gdeterminant function

<dl><dt>x</dt>
<dd>Numeric matrix</dd>
<dt>eps</dt>
<dd>Threshold below which eigenvalues are ignored (default: 1e-10)</dd>
<dt>log</dt>
<dd>Logical: should the log-determinant be returned?</dd></dl>

Arguments

Generalized matrix determinant — gdeterminant

<dl>

<dt>x</dt>
<dd>Numeric matrix</dd>


<dt>eps</dt>
<dd>Threshold below which eigenvalues are ignored (default: 1e-10)</dd>


<dt>log</dt>
<dd>Logical: should the log-determinant be returned?</dd>

</dl>

gdeterminant: Generalized matrix determinant

Description

Usage

Value

Arguments