SpatialRegimes (version 1.1)

Sareg: Spatial clusterwise regression by a constrained version of the Simulated Annealing

Description

This function implements a spatial clusterwise regression based on the procedure suggested by Postiglione et al. (2013).

Usage

Sareg(data, coly,colx, cont, intemp, rho, niter, subit, ncl, bcont)

Value

A object of Sareg class with:

groups

Estimated clusters.

Arguments

data

A data.frame

coly

The dependent variable in the c("y_ols") form.

colx

The covariates in the c("x1","x2") form.

cont

The contiguity matrix.

intemp

The initial temperature.

rho

The temperature decay rate parameter.

niter

The maximum number of iterations.

subit

The number of sub-iterations for each iteration.

ncl

The number of clusters.

bcont

A parameter that regulates the penalty of simulated annealing in non-contiguous configurations of the clusters.

Author

R. Benedetti

References

Postiglione, P., Benedetti, R., and Andreano, M.S. (2013). "Using Constrained Optimization for the Identification of Convergence Clubs", Computational Economics, 42, 151-174.

Examples

data(SimData)
SimData = SimData[1:50,]
coords = cbind(SimData$long, SimData$lat)

#######################

dmat   <-gw.dist(coords,focus=0,p=2,theta=0,longlat=FALSE)
W      <- matrix(0,nrow(dmat),ncol(dmat))
W[dmat < 0.2] <- 1
diag(W)       <- 0

#######################

sa <- Sareg(data=SimData,
               coly = c("y_ols"),
               colx = c("A"),
               W,
               intemp=0.5,
               rho=0.96,
               niter=30,
               subit=3,
               ncl=2,
               bcont=-4)

SimData$regimes = sa$groups
plot(lat~long,SimData,col=regimes,pch=16)