1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
|
% Copyright 2004 by Roger S. Bivand
\name{p.adjustSP}
\alias{p.adjustSP}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{Adjust local association measures' p-values}
\description{
Make an adjustment to local association measures' p-values based on the number of neighbours (+1) of each region, rather than the total number of regions.
}
\usage{
p.adjustSP(p, nb, method = "none")
}
%- maybe also 'usage' for other objects documented here.
\arguments{
\item{p}{vector of p-values}
\item{nb}{a list of neighbours of class \code{nb}}
\item{method}{correction method as defined in \code{\link{p.adjust}}: "The adjustment methods include the Bonferroni correction ('"bonferroni"') in which the p-values are multiplied by the number of comparisons. Four less conservative corrections are also included by Holm (1979) ('holm'), Hochberg (1988) ('hochberg'), Hommel (1988) ('hommel') and Benjamini & Hochberg (1995) ('fdr'), respectively. A pass-through option ('none') is also included."}
}
\value{
A vector of corrected p-values using only the number of neighbours + 1.
}
\author{Danlin Yu and Roger Bivand \email{Roger.Bivand@nhh.no}}
\seealso{\code{\link{p.adjust}}, \code{\link{localG}}, \code{\link{localmoran}}}
\examples{
data(afcon, package="spData")
oid <- order(afcon$id)
resG <- as.vector(localG(afcon$totcon, nb2listw(include.self(paper.nb))))
non <- format.pval(pnorm(2*(abs(resG)), lower.tail=FALSE), 2)
bon <- format.pval(p.adjustSP(pnorm(2*(abs(resG)), lower.tail=FALSE),
paper.nb, "bonferroni"), 2)
tot <- format.pval(p.adjust(pnorm(2*(abs(resG)), lower.tail=FALSE),
"bonferroni", n=length(resG)), 2)
data.frame(resG, non, bon, tot, row.names=afcon$name)[oid,]
}
\keyword{spatial}
|
