Recover posterior samples of scale parameters of spatial/spatial-temporal generalized linear models

A function to recover posterior samples of scale parameters that were marginalized out during model fit. This is only applicable for spatial or, spatial-temporal generalized linear models. This function applies on outputs of functions that fits a spatial/spatial-temporal generalized linear model, such as spGLMexact(), spGLMstack(), stvcGLMexact(), and stvcGLMstack().

Usage

recoverGLMscale(mod_out)

Arguments

mod_out: an object returned by a fitting a spatial or spatial-temporal GLM.

Value

An object of the same class as input, and updates the list tagged samples with the posterior samples of the scale parameters. The new tags are sigmasq.beta and z.scale.

Author

Soumyakanti Pan span18@ucla.edu,
Sudipto Banerjee sudipto@ucla.edu

Examples

set.seed(1234)
data("simPoisson")
dat <- simPoisson[1:100, ]
mod1 <- spGLMstack(y ~ x1, data = dat, family = "poisson",
                   coords = as.matrix(dat[, c("s1", "s2")]), cor.fn = "matern",
                   params.list = list(phi = c(3, 5, 7), nu = c(0.5, 1.5),
                                      boundary = c(0.5)),
                   n.samples = 100,
                   loopd.controls = list(method = "CV", CV.K = 10, nMC = 500),
                   verbose = TRUE)
#> 
#> STACKING WEIGHTS:
#> 
#>           | phi | nu  | boundary | weight |
#> +---------+-----+-----+----------+--------+
#> | Model 1 |    3|  0.5|       0.5| 0.000  |
#> | Model 2 |    5|  0.5|       0.5| 0.000  |
#> | Model 3 |    7|  0.5|       0.5| 0.000  |
#> | Model 4 |    3|  1.5|       0.5| 0.398  |
#> | Model 5 |    5|  1.5|       0.5| 0.082  |
#> | Model 6 |    7|  1.5|       0.5| 0.520  |
#> +---------+-----+-----+----------+--------+
#> 

# Recover posterior samples of scale parameters
mod1.1 <- recoverGLMscale(mod1)

# sample from the stacked posterior distribution
post_samps <- stackedSampler(mod1.1)