SpatReg_GoF {SCDA} | R Documentation |
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)
Arguments
SRModel_list |
List of estimated spatial or non-spatial regression model of class |
SRModel_W_list |
List of |
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
.
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)