Dear list,
I am using spgwr::ggwr() to fit generalized geographically weighted regression
with Poisson model and log-link function. The results provide local coefficient
estimates, but i am missing how to get their standard errors (or t statistics)
to compute pseudo p-values.
Below is a toy example using SpatialEpi::NYleukemia dataset:
# --------
library(SpatialEpi)
library(spgwr)
## Load data
data(NYleukemia)
population <- NYleukemia$data$population
cases <- ceiling(NYleukemia$data$cases * 100)
centroids <- latlong2grid(NYleukemia$geo[, 2:3])
# data frame
nyleuk <- data.frame(centroids, cases, population)
# set coordinates as vector
coordny <- cbind(centroids[,1],centroids[,2])
# set a kernel bandwidth
bw <- 0.5
# fit ggwr()
m_pois <- ggwr(cases ~ offset(log(population)),
data = nyleuk, gweight = gwr.Gauss,
adapt = bw, family = poisson(link="log"),
type="working", coords = coordny)
# returns spatial point with coefficients
# but no standard errors :(
head(m_pois$SDF@data)
# -------
Is there any way to get standard errors of the local coefficients?
Thank you, Manuel
Sent from Mail for Windows 10
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