ProbitSpatial-class: Class of Spatial Probit Model.
In ProbitSpatial: Probit with Spatial Dependence, SAR, SEM and SARAR Models

Description Slots

Class of Spatial Probit Model.

beta: numeric, the estimated parameters for the covariates.
rho: numeric, the estimated spatial autocorrelation parameter.
lambda: numeric, the estimated spatial error autocorrelation parameter.
coeff: numeric, all estimated parameters.
loglik: numeric, the likelihood associated to the estimated model.
formula: formula.
nobs: numeric, number of observations.
nvar: numeric, number of covariates.
y: numeric, vector of observed dependent variable.
X: matrix, matrix of covariates.
time: numeric, estimation time.
DGP: character, DGP of the model (SAR, SEM or SARAR).
method: character, estimation method ("conditional" or "full-lik").
varcov: character, indicates the matrix used in the algorithm ("varcov" or "precision").
W: SparseMatrix, the spatial weight matrix of y.
M: SparseMatrix, the spatial weight matrix of the disturbances.
iW_CL: numeric, the order of approximation used in the conditional method.
iW_FL: numeric, the order of approximation used inside the likelihood function for the full-lik method.
iW_FG: numeric, the order of approximation used inside the gradient functions for the full-lik method.
reltol: numeric, the relative convergence tolerance.
prune: numeric, the pruning for the gradient functions.
env: an environment containing information for use in later function calls to save time.
message: a integer giving any additional information or NULL.