cov_grid

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

cov_grid function

<dl><dt>var</dt>
<dd>Name of variable</dd>
<dt>data</dt>
<dd>Data frame containing the covariates. If not provided, data
are extracted from obj</dd>
<dt>obj</dt>
<dd>HMM model object containing data and formulas</dd>
<dt>covs</dt>
<dd>Optional named list for values of covariates (other than 'var') 
that should be used in the plot (or dataframe with single row). If this is
not specified, the mean value is used for numeric variables, and the
first level for factor variables.</dd>
<dt>formulas</dt>
<dd>List of formulas used in the model</dd>
<dt>n_grid</dt>
<dd>Grid size (number of points). Default: 1000.</dd></dl>

Arguments

Grid of covariates — cov_grid

<dl>

<dt>var</dt>
<dd>Name of variable</dd>


<dt>data</dt>
<dd>Data frame containing the covariates. If not provided, data
are extracted from obj</dd>


<dt>obj</dt>
<dd>HMM model object containing data and formulas</dd>


<dt>covs</dt>
<dd>Optional named list for values of covariates (other than 'var') 
that should be used in the plot (or dataframe with single row). If this is
not specified, the mean value is used for numeric variables, and the
first level for factor variables.</dd>


<dt>formulas</dt>
<dd>List of formulas used in the model</dd>


<dt>n_grid</dt>
<dd>Grid size (number of points). Default: 1000.</dd>

</dl>

cov_grid: Grid of covariates

Description

Usage

Value

Arguments