getLVcorrMat: Compute results of a Joint Species Distribution Model (JSDM)

In AHMbook: Functions and Data for the Book 'Applied Hierarchical Modeling in Ecology' Vols 1 and 2

Compute results of a Joint Species Distribution Model (JSDM)

Description

Compute pairwise residual correlation in occurrence or abundance in a Joint Species Distribution Model (JSDM) with latent variables.

getLVcorrMat computes the correlation matrix in residual occurrence or abundance in an latent-variable multi-species occupancy or N-mixture model which has been fit using MCMC (eg, in JAGS or WinBUGS). See Tobler et al. (2019) and Kéry & Royle (2021) chapter 8.

getEcorrMat computes the correlation matrix for the coefficients of the observed environmental covariates.

Usage

getLVcorrMat(lv.coef, type=c("occupancy", "Nmix"), stat=mean)

getEcorrMat(beta, stat=mean)

Arguments

lv.coef	MCMC chains for the coefficients of the latent variables, typically from the sims.list of a model fit; an iterations x species x latent variables array.
beta	MCMC chains for the coefficients of the environment variables (excluding the intercept), typically from the sims.list of a model fit; an iterations x species x environmental variables array.
type	Indication of whether the model fit was for occupancy data (with a probit link) or an N-mixture model based on count data.
stat	The function used to summarize the MCMC chains for the correlations; if stat = NULL. the full array with the MCMC chains is returned

Value

The relevant correlation matrix, species x species; if stat = NULL, an array, iterations x species x species, with the MCMC chains.

Author(s)

Mathias Tobler.

References

Tobler, M. et al. (2019) Joint species distribution models with species correlations and imperfect detection. Ecology, 100(8), e02754.

Kéry, M. & Royle, J.A. (2021) Applied Hierarchical Modeling in Ecology AHM2 - 8.4.2 and 8.5.4.

AHMbook documentation built on Aug. 24, 2023, 1:07 a.m.