rtgmrf | R Documentation |
Use this function to simulate a data of a TGMRF.
rtgmrf(rowid = 10, colid = 10, X = NULL, n_var = 1, 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 = NULL, nu = 2, tau = 1, type_data = "gamma-shape", family = "poisson", mat_type = "car", seed = 1)
rowid |
Number of lines of a lattice. (Used if neigh = NULL) |
colid |
Number of columns of a lattice. (Used if neigh = NULL) |
neigh |
A object of class nb |
betas |
Coeficients |
intercept |
Should use intercept? NULL or coefficiente |
nu |
Dispersion parameter for gamma models |
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 |
rho |
Dependence parameter |
y Response variable
X Covariates matrix
neigh Neighborhood structure
Q Covariance matrix
mu Means (TGMRF)
eps Errors (GMRF)
#--- library(mvtnorm) #--- library(spdep) data(nenia) coord <- as.data.frame(cbind(x = nenia$x, y = nenia$y)) coordinates(coord) <- c("x","y") dst <- 3 neigh <- dnearneigh(coord, 0, dst) data_poisson <- rtgmrf_s(neigh = neigh, rho_s = 0.9, betas = c(1, 0.9, -0.1), nu = 2, type_data = 'gamma-shape', family = 'poisson', seed = 1) data_binary <- rtgmrf_s(rowid = 10, colid = 10, rho_s = 0.9, betas = c(1, 0.9), nu = 5, type_data = 'gamma-shape', family = 'poisson', seed = 1)
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