simulate.sjSDM

Simulate nsim responses from the fitted model following a multivariate probit model.
So currently only supported for <code>family = stats::binomial("probit")</code>

A scalable and fast method for estimating joint Species Distribution Models (jSDMs) for big community data, including eDNA data. The package estimates a full (i.e. non-latent) jSDM with different response distributions (including the traditional multivariate probit model). The package allows to perform variation partitioning (VP) / ANOVA on the fitted models to separate the contribution of environmental, spatial, and biotic associations. In addition, the total R-squared can be further partitioned per species and site to reveal the internal metacommunity structure, see Leibold et al., <doi:10.1111/oik.08618>. The internal structure can then be regressed against environmental and spatial distinctiveness, richness, and traits to analyze metacommunity assembly processes. The package includes support for accounting for spatial autocorrelation and the option to fit responses using deep neural networks instead of a standard linear predictor. As described in Pichler & Hartig (2021) <doi:10.1111/2041-210X.13687>, scalability is achieved by using a Monte Carlo approximation of the joint likelihood implemented via 'PyTorch' and 'reticulate', which can be run on CPUs or GPUs.

Maximilian Pichler

sjSDM

Scalable Joint Species Distribution Modeling

Florian Hartig

Wang Cai

simulate.sjSDM function

<dl><dt>object</dt>
<dd>a model fitted by <code>sjSDM</code></dd>
<dt>nsim</dt>
<dd>number of simulations</dd>
<dt>seed</dt>
<dd>seed for random number generator</dd>
<dt>...</dt>
<dd>optional arguments for compatibility with the generic function, no functionality implemented</dd></dl>

Arguments

Generates simulations from sjSDM model — simulate.sjSDM

<dl>

<dt>object</dt>
<dd>a model fitted by <code>sjSDM</code></dd>


<dt>nsim</dt>
<dd>number of simulations</dd>


<dt>seed</dt>
<dd>seed for random number generator</dd>


<dt>...</dt>
<dd>optional arguments for compatibility with the generic function, no functionality implemented</dd>

</dl>

simulate.sjSDM: Generates simulations from sjSDM model

Description

Usage

Value

Arguments