aple.mc

0th

Percentile

Approximate profile-likelihood estimator (APLE) permutation test

A permutation bootstrap test for the approximate profile-likelihood estimator (APLE).

Keywords
spatial
Usage
aple.mc(x, listw, nsim, override_similarity_check=FALSE, useTrace=TRUE)
Arguments
x
a zero-mean detrended continuous variable
listw
a listw object from for example nb2listw
nsim
number of simulations
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)
Value

A boot object as returned by the boot function.

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

aple, boot

Aliases
  • aple.mc
Examples

example(aple)
oldRNG <- RNGkind()
RNGkind("L'Ecuyer-CMRG")
set.seed(1L)
boot_out_ser <- aple.mc(as.vector(scale(wheat$yield_detrend, scale=FALSE)),
 nb2listw(nbr12, style="W"), nsim=500)
plot(boot_out_ser)
boot_out_ser
library(parallel)
oldCores <- set.coresOption(NULL)
nc <- detectCores(logical=FALSE)
# set nc to 1L here
if (nc > 1L) nc <- 1L
invisible(set.coresOption(nc))
set.seed(1L)
if (!get.mcOption()) {
  cl <- makeCluster(nc)
  set.ClusterOption(cl)
} else{
  mc.reset.stream()
}
boot_out_par <- aple.mc(as.vector(scale(wheat$yield_detrend, scale=FALSE)),
    nb2listw(nbr12, style="W"), nsim=500)
if (!get.mcOption()) {
  set.ClusterOption(NULL)
  stopCluster(cl)
}
boot_out_par
invisible(set.coresOption(oldCores))
RNGkind(oldRNG[1], oldRNG[2])

Documentation reproduced from package spdep, version 0.6-9, License: GPL (>= 2)

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