jSDM (version 0.1.0)

get_residual_cor: Calculate the residual correlation matrix from a LVM.

Description

This function use coefficients \((\lambda_j^l) with j=1,\dots,n_species and l=1,\dots,n_latent\)$ corresponding to latent variables to calculate the variance-covariance matrix which controls correlation between species.

Usage

get_residual_cor(mod)

Arguments

mod

An object of class "jSDM"

Value

cov.mean

Average over the MCMC samples of the variance-covariance matrix.

cov.median

Median over the MCMC samples of the variance-covariance matrix.

cor.mean

Average over the MCMC samples of the residual correlation matrix.

cor.median

Median over the MCMC samples of the residual correlation matrix.

Examples

# NOT RUN {
# frogs data
data(frogs, package="jSDM")

# Arranging data
PA_frogs <- frogs[,4:12]

# Normalized continuous variables
Env_frogs <- cbind(scale(frogs[,1]),frogs[,2],scale(frogs[,3]))
colnames(Env_frogs) <- colnames(frogs[,1:3])

# Parameter inference
# Increase the number of iterations to reach MCMC convergence
mod_jSDM_block_frogs <- jSDM::jSDM_probit_block (
  # Response variable 
  presence_site_sp = as.matrix(PA_frogs), 
  # Explanatory variables 
  site_suitability = ~.,   
  site_data = as.data.frame(Env_frogs), n_latent=2,
  # Chains
  burnin=1000, mcmc=1000, thin=1,
  # Starting values
  alpha_start=0, beta_start=0,
  lambda_start=0, W_start=0,
  V_alpha_start=1, 
  # Priors
  shape=0.5, rate=0.0005,
  mu_beta=0, V_beta=1.0E6,
  mu_lambda=0, V_lambda=10,
  # Various 
  seed=1234, verbose=1)
  
# Calcul of residual correlation between species 
result <- get_residual_cor(mod_jSDM_block_frogs)
result$cov.mean
result$cor.mean

# }