aple.plot

0th

Percentile

Approximate profile-likelihood estimator (APLE) scatterplot

A scatterplot decomposition of the approximate profile-likelihood estimator, and a local APLE based on the list of vectors returned by the scatterplot function.

Keywords
spatial
Usage
aple.plot(x, listw, override_similarity_check=FALSE, useTrace=TRUE, do.plot=TRUE, ...) localAple(x, listw, override_similarity_check=FALSE, useTrace=TRUE)
Arguments
x
a zero-mean detrended continuous variable
listw
a listw object from for example 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)
do.plot
default TRUE: should a scatterplot be drawn
...
other arguments to be passed to plot
Details

The function solves a secondary eigenproblem of size n internally, so constructing the values for the scatterplot is quite compute and memory intensive, and is not suitable for very large n.

Value

aple.plot returns list with components:localAple returns a vector of local APLE values.

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, pp. 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

aple

Aliases
  • aple.plot
  • localAple
Examples
## Not run: 
# example(aple)
# plt_out <- aple.plot(as.vector(scale(wheat$yield_detrend, scale=FALSE)),
#  nb2listw(nbr12, style="W"), cex=0.6)
# crossprod(plt_out$Y, plt_out$X)/crossprod(plt_out$X)
# lm_obj <- lm(Y ~ X, plt_out)
# abline(lm_obj)
# abline(v=0, h=0, lty=2)
# zz <- summary(influence.measures(lm_obj))
# infl <- as.integer(rownames(zz))
# points(plt_out$X[infl], plt_out$Y[infl], pch=3, cex=0.6, col="red")
# wheat$localAple <- localAple(as.vector(scale(wheat$yield_detrend, scale=FALSE)),
#  nb2listw(nbr12, style="W"))
# mean(wheat$localAple)
# hist(wheat$localAple)
# spl <- list("sp.text", coordinates(wheat)[infl,], rep("*", length(infl)))
# spplot(wheat, "localAple", sp.layout=spl)
# ## End(Not run)
Documentation reproduced from package spdep, version 0.6-9, License: GPL (>= 2)

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