lesage_pace: LeSage and Pace procedure

In Psqrt/spcomparison: Spatial Regression Models Selection

Description

LeSage and Pace procedure

Usage

lesage_pace(formula, data, listw, alpha = 0.05, criterion = "AIC")

Arguments

formula	a formula object (or one that can be coerced to that class): a symbolic description of the model to be fitted.
data	a data.frame object containing the variables in the model.
listw	a listw object containing weights.
alpha	a numeric value providing the confidence level between 0 and 1.
criterion	either AIC (default) or BIC: in case if several models are selected, using information criterion to draw out the best model.

Value

returns a data.frame object containing likelihood ratio tests information.

References

LeSage, J., & Pace, R. K. (2009). Introduction to spatial econometrics. Chapman and Hall/CRC.

Examples

require(spatialreg)
require(spdep)
require(rgdal)
columbus <- readOGR(system.file("shapes/columbus.shp", package="spData")[1])
weights <- nb2listw(poly2nb(columbus))
formula <- CRIME ~ INC + HOVAL

lesage_pace(formula = formula, data = columbus,
            listw = weights, alpha = 0.05, criterion = "AIC")
lesage_pace(formula = INC ~ CRIME, data = columbus, listw = weights)

Psqrt/spcomparison documentation built on Nov. 25, 2019, 12:33 a.m.