AGPRIS (version 2.0)

mml: MML estimator

Description

This function estimates a space time linear model according to the specified formula using the ML estimator as in Elhorst (2010) tools:::Rd_expr_doi("10.1016/j.regsciurbeco.2010.03.003"). The estimator maximizes the full log-likelihood function in which the parameter of spatial dependence is constrained.

Usage

mml(Rho, ff, dataset, wmat, var.agg, m = 10)

Value

The estimates tables

Arguments

Rho

the constrained parameter of spatial dependence

ff

Formula of the linear model. It excludes the spatial lag

dataset

Data frame with the data

wmat

Spatial weight matrix

var.agg

Spatial index of the data frame

m

How many time periods have passed since the beginning of the space-time process

Examples

# \donttest{

set.seed(123)
sd = sim_data_fe(dataset=regsamp,N=50,TT=6,
                spatial = 80,Tau = -0.2,Rho = 0.4,
                Beta = 2,sdDev = 2,startingT = 10,
                LONGLAT = TRUE);sd[[1]]$X2 = stats::rnorm(nrow(sd[[1]]@data))
est_mml = mml(dataset = sd[[1]]@data,Rho = 0.4,
              ff = Y~X1+X2,
              wmat = sd[[2]],var.agg = c('Anno','Cod_Provincia'),
              m = 10)
est_mml
# }