fitted.svcPGOcc

Method for extracting model fitted values and detection probabilities from a fitted single-species spatially-varying coefficients occupancy (<code>svcPGOcc</code>) model.

model

Fits single-species, multi-species, and integrated non-spatial and spatial occupancy models using Markov Chain Monte Carlo (MCMC). Models are fit using Polya-Gamma data augmentation detailed in Polson, Scott, and Windle (2013) <doi:10.1080/01621459.2013.829001>. Spatial models are fit using either Gaussian processes or Nearest Neighbor Gaussian Processes (NNGP) for large spatial datasets. Details on NNGP models are given in Datta, Banerjee, Finley, and Gelfand (2016) <doi:10.1080/01621459.2015.1044091> and Finley, Datta, and Banerjee (2022) <doi:10.18637/jss.v103.i05>. Provides functionality for data integration of multiple single-species occupancy data sets using a joint likelihood framework. Details on data integration are given in Miller, Pacifici, Sanderlin, and Reich (2019) <doi:10.1111/2041-210X.13110>. Details on single-species and multi-species models are found in MacKenzie, Nichols, Lachman, Droege, Royle, and Langtimm (2002) <doi:10.1890/0012-9658(2002)083[2248:ESORWD]2.0.CO;2> and Dorazio and Royle <doi:10.1198/016214505000000015>, respectively.

Jeffrey Doser

spOccupancy

Single-Species, Multi-Species, and Integrated Spatial Occupancy
Models

Andrew Finley

Marc Kery

fitted.svcPGOcc function

<dl> <dt>object</dt>
<dd>object of class <code>svcPGOcc</code>.</dd> <dt>...</dt>
<dd>currently no additional arguments</dd></dl>

Arguments

Extract Model Fitted Values for svcPGOcc Object — fitted.svcPGOcc

<dl>

 <dt>object</dt>
<dd>object of class <code>svcPGOcc</code>.</dd>

 <dt>...</dt>
<dd>currently no additional arguments</dd>

</dl>

fitted.svcPGOcc: Extract Model Fitted Values for svcPGOcc Object

Description

Usage

Value

Arguments

Details