LOSH.cs | R Documentation |
The function implements the chi-square based test statistic for local spatial heteroscedasticity (LOSH) as proposed by Ord & Getis (2012).
LOSH.cs(x, listw, zero.policy = NULL, na.action = na.fail, p.adjust.method = "none", spChk = NULL)
x |
a numeric vector of the same length as the neighbours list in listw |
listw |
a |
zero.policy |
default NULL, use global option value; if TRUE assign zero to the lagged value of zones without neighbours, if FALSE assign NA |
na.action |
a function (default |
p.adjust.method |
a character string specifying the probability value adjustment for multiple tests, default "none"; see |
spChk |
should the data vector names be checked against the spatial objects for identity integrity, TRUE, or FALSE, default NULL to use |
The test uses a = 2 (see LOSH
) because chi-square based inference is not applicable with other exponents. The function makes use of LOSH
in its calculations.
Hi |
LOSH statistic |
E.Hi |
expectation of LOSH |
Var.Hi |
variance of LOSH |
Z.Hi |
the approximately chi-square distributed test statistics |
x_bar_i |
local spatially weighted mean values |
ei |
residuals about local spatially weighted mean values |
Pr() |
p-values for |
René Westerholt rene.westerholt@tu-dortmund.de
Ord, J. K., & Getis, A. 2012. Local spatial heteroscedasticity (LOSH), The Annals of Regional Science, 48 (2), 529–539.
LOSH
, LOSH.mc
data(boston, package="spData") resLOSH <- LOSH.cs(boston.c$NOX, nb2listw(boston.soi)) hist(resLOSH[,"Hi"]) mean(resLOSH[,"Hi"])
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