spatialreg (version 1.3-5)

aple: Approximate profile-likelihood estimator (APLE)

Description

The Approximate profile-likelihood estimator (APLE) of the simultaneous autoregressive model's spatial dependence parameter was introduced in Li et al. (2007). It employs a correction term using the eigenvalues of the spatial weights matrix, and consequently should not be used for large numbers of observations. It also requires that the variable has a mean of zero, and it is assumed that it has been detrended. The spatial weights object is assumed to be row-standardised, that is using default style="W" in nb2listw.

Usage

aple(x, listw, override_similarity_check=FALSE, useTrace=TRUE)

Value

A scalar APLE value.

Arguments

x

a zero-mean detrended continuous variable

listw

a listw object from for example spdep::nb2listw

override_similarity_check

default FALSE, if TRUE - typically for row-standardised weights with asymmetric underlying general weights - similarity is not checked

useTrace

default TRUE, use trace of sparse matrix W %*% W (Li et al. (2010)), if FALSE, use crossproduct of eigenvalues of W as in Li et al. (2007)

Author

Roger Bivand

Details

This implementation has been checked with Hongfei Li's own implementation using her data; her help was very valuable.

References

Li, H, Calder, C. A. and Cressie N. A. C. (2007) Beyond Moran's I: testing for spatial dependence based on the spatial autoregressive model. Geographical Analysis 39, 357-375; Li, H, Calder, C. A. and Cressie N. A. C. (2012) One-step estimation of spatial dependence parameters: Properties and extensions of the APLE statistic, Journal of Multivariate Analysis 105, 68-84.

See Also

nb2listw, aple.mc, aple.plot

Examples

wheat <- st_read(system.file("shapes/wheat.gpkg", package="spData")[1], quiet=TRUE)
library(spdep)
nbr1 <- spdep::poly2nb(wheat, queen=FALSE)
nbrl <- spdep::nblag(nbr1, 2)
nbr12 <- spdep::nblag_cumul(nbrl)
cms0 <- with(as.data.frame(wheat), tapply(yield, c, median))
cms1 <- c(model.matrix(~ factor(c) -1, data=wheat) %*% cms0)
wheat$yield_detrend <- wheat$yield - cms1
isTRUE(all.equal(c(with(as.data.frame(wheat),
 tapply(yield_detrend, c, median))), rep(0.0, 25),
 check.attributes=FALSE))
spdep::moran.test(wheat$yield_detrend, spdep::nb2listw(nbr12, style="W"))
aple(as.vector(scale(wheat$yield_detrend, scale=FALSE)), spdep::nb2listw(nbr12, style="W"))
if (FALSE) {
errorsarlm(yield_detrend ~ 1, wheat, spdep::nb2listw(nbr12, style="W"))
}