plotACF

a matrix (or data.frame) with each row containing the posterior samples of one latent variable

S.mcmc

the maximum number of lags; the default "NULL" will result in $10*\log_{10}(N/m)$ where N is the number of observations and m the number of series

lags


  This function plots auto-correlation curves for latent variables.

MCMC

This package provides a variety of functions to analyze and model geostatistical count data with generalized linear spatial models, including
1) simulate and visualize the data;
2) posterior sampling with robust MCMC algorithms (in serial or parallel way);
3) perform prediction for unsampled locations;
4) conduct Bayesian model checking procedure to evaluate the goodness of fitting;
5) conduct transformed residual checking procedure.
In the package, seamlessly embedded C++ programs and parallel computing techniques are implemented to speed up the computing processes.

plotACF: Auto-correlation Plot for Latent Variables

Description

Usage

Arguments

Value

Details

Examples