SCDA (version 0.0.1)

SpatReg_GoF: Computes a set of goodness-of-fit indices (e.g., likelihood-based information criteria, Wald and LR test, Moran's I statistic) for a given spatial regression model of class lm or Sarlm.

Description

Computes a set of goodness-of-fit indices (e.g., likelihood-based information criteria, Wald and LR test, Moran's I statistic) for a given spatial regression model of class lm or Sarlm as defined in package spatialreg. The function can be applied to the output of any SCSR model and contained in the ClusterFitModels output of SCSR_Estim function.

Usage

SpatReg_GoF(SRModel_list, SRModel_W_list)

Value

A matrix containing 15 goodness-of-fit indices (e.g., likelihood-based information criteria, Wald and LR test, Moran's I statistic) for the list of models given as a input in SRModel_list.

Arguments

SRModel_list

List of estimated spatial or non-spatial regression model of class lm or Sarlm (see package spatialreg for details.)

SRModel_W_list

List of listw objects (see package spdep for details) containing the spatial weights for the spatial autoregressive component for the G groups.

Examples

data(Data_RC_PM_RM_JABES2024, package="SCDA")
SCSAR <- SCSR_Estim(Formula = "Gini_SO ~ GDPPC_PPS2020 + Share_AgroEmp",
                    Data_sf = Data2020, G=3, listW=listW, Type="SCSAR", Phi = 0.50)
reglist <- c(SCSAR$ClusterFitModels[1],SCSAR$ClusterFitModels[2],SCSAR$ClusterFitModels[3])
Wlist <- c(SCSAR$listW_g[1],SCSAR$listW_g[2],SCSAR$listW_g[3])
SpatReg_GoF(SRModel_list = reglist,SRModel_W_list = Wlist)