portal_data

A dataset containing timeseries of total captures (across all control plots) for select rodent species from the Portal Project

datasets

Fit Bayesian Dynamic Generalized Additive Models to multivariate observations. Users can build nonlinear State-Space models that can incorporate semiparametric effects in observation and process components, using a wide range of observation families. Estimation is performed using Markov Chain Monte Carlo with Hamiltonian Monte Carlo in the software 'Stan'. References: Clark & Wells (2023) <doi:10.1111/2041-210X.13974>.

Nicholas J Clark

mvgam

Multivariate (Dynamic) Generalized Additive Models

portal_data function

A <code>data.frame</code> containing the following fields:<dl>
<dt>time</dt>
<dd>time of sampling, in lunar monthly cycles</dd><dt>series</dt>
<dd>factor indicator of the time series, i.e. the species</dd><dt>captures</dt>
<dd>total captures across all control plots</dd><dt>mintemp</dt>
<dd>monthly mean minimum temperature</dd><dt>ndvi_ma12</dt>
<dd>12-month moving average of the mean Normalised Difference Vegetation Index</dd><dt>mintemp</dt>
<dd>monthly mean of minimum temperature</dd>
</dl>

Format

Portal Project rodent capture survey data — portal_data

A <code>data.frame</code> containing the following fields:<dl>
<dt>time</dt>
<dd>time of sampling, in lunar monthly cycles</dd>

<dt>series</dt>
<dd>factor indicator of the time series, i.e. the species</dd>

<dt>captures</dt>
<dd>total captures across all control plots</dd>

<dt>mintemp</dt>
<dd>monthly mean minimum temperature</dd>

<dt>ndvi_ma12</dt>
<dd>12-month moving average of the mean Normalised Difference Vegetation Index</dd>

<dt>mintemp</dt>
<dd>monthly mean of minimum temperature</dd>


</dl>

portal_data: Portal Project rodent capture survey data

Description

Usage

Arguments

Format