summary.dsspMod: Summarise a 'dsspMod' model

In DSSP: Implementation of the Direct Sampling Spatial Prior

Summarise a dsspMod model

Description

Summarise a dsspMod model

Usage

## S3 method for class 'dsspMod'
summary(object, prob = 0.95, robust = FALSE, mc_se = FALSE, ...)

Arguments

object	an object of class dsspMod
prob	the desired probability to be covered by the credible intervals. The default is 0.95.
robust	whether or not to use the median (rather than the mean) to calculate the estimates that summarise the posterior. Default to FALSE.
mc_se	whether or not to include the uncertainty in Estimate caused by sampling should be shown in the summary. Defaults to FALSE.
...	additional arguments which are ignored.

Value

An object of class "dsspModsummary". Provides a summary of the the Direct Sampling Spatial Prior (DSSP) model. Includes details of the formula used to fit the model, and a summary of the model (eta, delta) and the covariates.

Examples

library(sp)
library(gstat)
data(meuse.all)
coordinates(meuse.all) <- ~ x + y

f <- function(x) -x ## log-prior for exponential distribution for the smoothing parameter

## Draw 100 samples from the posterior of eta given the data y.
OUTPUT <- DSSP(
  formula = log(zinc) ~ 1, data = meuse.all, N = 100,
  pars = c(0.001, 0.001), log_prior = f
)
summary(OUTPUT)

DSSP documentation built on July 12, 2022, 5:06 p.m.