rtgmrf_st: Random observations of a Transformed Gaussian Markov Random...

In DouglasMesquita/TGMRF: Transformed Gaussian Markov Random Fields

Random observations of a Transformed Gaussian Markov Random Field

Description

Use this function to simulate a data of a spatio-temporal TGMRF.

Usage

rtgmrf_st(rowid = 10, colid = 10, n_var = 2, X = NULL,
  neigh = NULL, n_trials = NULL, E = NULL, rho_s = 0.9,
  rho_t = 0, rho_st = 0, betas = c(-0.1, 0.3, 0.8), intercept = T,
  nu = 2, tau = 1, type_data = "gamma-shape", family = "poisson",
  mat_type = "car", seed = 1)

Arguments

rowid	Number of lines of a lattice. (Used if neigh = NULL)
colid	Number of columns of a lattice. (Used if neigh = NULL)
n_var	Number of variables in problem (for multivariate problems)
neigh	A object of class nb
rho_s	Spatial dependence parameter
rho_t	Temporal dependence parameter
rho_st	Spatio-temporal dependence parameter
betas	Coeficients
nu	Dispersion parameter for gamma models
tau	Vector of precisions of variables
type_data	Depends of family. 'lognormal', 'lognormal-precision', 'gamma-shape', 'gamma-scale', 'weibull-shape', 'weibull-scale' for Poisson family 'beta-logit', 'beta-probit', 'beta-alpha', 'beta-beta' for Binomial family
family	'poisson' or 'binary'
seed	A seed to reproduce the reuslts
n	Vector with size of binomial trials

Value

y Response variable

X Covariates matrix

neigh Neighborhood structure

Q Covariance matrix

mu Means (TGMRF)

eps Errors (GMRF)

DouglasMesquita/TGMRF documentation built on May 28, 2022, 8:34 p.m.