View source: R/mcmc_poisson_st.R
mcmc_poisson_st | R Documentation |
MCMC for Poisson data using TGMRF
mcmc_poisson_st(y, X, E, n_reg, n_var, neigh, beta, nu, eps, mu, rho_s, rho_t, rho_st, tau, nsim, burnin, thin, type, type_num, mat_type, method, tau_beta, mean_beta, eta_nu, psi_nu, ninit, maxpoint, var_beta, var_eps, var_log_mu, var_log_nu, var_rho, fix_rho_s, fix_rho_t, fix_rho_st, range_rho_s, range_rho_t, range_rho_st, verbose, c_beta, c_eps, c_mu, c_nu, c_rho, conj_beta)
y |
Response variable |
X |
Matrix or data.frame of covariates |
E |
Offsets for Poisson data |
n_reg |
Number of regions in study |
n_var |
Number of variables in study |
neigh |
Neighborhood structure of nb class or a neighborhood matrix |
beta |
Vector of the initial values to coeficients vector |
nu |
A Initial value to variance of copula |
eps |
Initial values to eps parameters |
rho_s |
A Initial value to spatial dependence |
rho_t |
A Initial value to temporal dependence |
rho_st |
A Initial value to spatio-temporal dependence |
tau |
Precision parameter vector of MCAR |
nsim |
Number of MCMC iterations |
burnin |
number of discards iterations |
thin |
Lag to collect the observations |
type |
'lognormal', 'lognormal-precision', 'gamma-shape', 'gamma-scale', 'weibull-shape', 'weibull-scale' |
type_num |
A numeric that represent type in .C functions |
mat_type |
car or leroux |
method |
arms or metropolis |
tau_beta |
Prior precision of beta vector |
mean_beta |
Prior mean of beta vector |
eta_nu |
Prior Shape of nu parameter |
psi_nu |
Prior Scale of nu parameter |
ninit |
Number of initial points in ARMS method |
maxpoint |
Maximum number of evaluation a envelope in each iteration |
var_beta |
Variance of beta proposal (metropolis) |
var_eps |
Variance of eps proposal (metropolis) |
var_log_mu |
Variance of log(mu) proposal (metropolis) |
var_rho |
Variance of rho proposal (metropolis) |
fix_rho_s |
Is rho_s fixed? |
fix_rho_t |
Is rho_t fixed? |
fix_rho_st |
Is rho_st fixed? |
range_rho_s |
Range to sample rho_s |
range_rho_t |
Range to sample rho_t |
range_rho_st |
Range to sample rho_st |
eps A matrix with eps samples
mu A matrix with intensities samples
beta A matrix with beta samples
nu A vector with samples of nu
rho A vector with samples of rho
model_info A data_frame with some models' informations
fit measures A data_frame with some fit measures
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