spsample: Posterior samples for spatial effects and regression...

In arh926/spWombling: Bayesian Wombling for Spatial Processes

Posterior samples for spatial effects and regression coefficients

Description

Posterior sampling algorithm for generating samples of spatial random effects and regression coefficients using a Gibbs sampling algorithm.

Posterior sampling algorithm for generating samples of spatio-temporal random effects and regression coefficients using a Gibbs sampling algorithm.

Usage

spsample(
  y = NULL,
  X = NULL,
  coords = NULL,
  phi = NULL,
  sig2 = NULL,
  tau2 = NULL,
  cov.type = c("matern1", "matern2", "gaussian"),
  silent = TRUE
)

spsample(
  y = NULL,
  X = NULL,
  coords = NULL,
  phi = NULL,
  sig2 = NULL,
  tau2 = NULL,
  cov.type = c("matern1", "matern2", "gaussian"),
  silent = TRUE
)

Arguments

y	response
X	design matrix
coords	spatial co-ordinates
phi	posterior samples of the spatial range parameter
sig2	posterior samples of the spatio-temporal variance parameter (partial sill)
tau2	posterior samples of the error variance (nugget)
cov.type	type of covariance kernel being used. Choices include Exponential, Mat\'ern(\nu=3/2)), Mat\'ern(\nu=5/2), Gaussian
silent	logical argument for print-statements
t	temporal coordinates
phis	posterior samples of the spatial range parameter
phit	posterior samples of the temporal range parameter

arh926/spWombling documentation built on April 14, 2025, 4 p.m.