ressie"))
plot(vario100); lines(wls)
(wls.sum <- summary(wls))
(sse <- wls.sum$sum.of.squares)
(n <- length(s100$data))
(p <- length(wls.sum$estimated.pars))
(df <- n-p-1)
(mse <- sse/df)
(rmse <- sqrt(mse))
Could you follow up and let me know if this approach worked?
-Chri
quot;)
dev.off()
kmlOverlay(SG.big.ten, "bigten.kml", "bigten.png")
plot(data, xlim=SG.big.ten$xlim, ylim=SG.big.ten$ylim, setParUsrBB=TRUE,
cex=3, pch=21, bg="red")
Thank you for your assistance.
Regards,
Chris
P.S. I'm usi
plement to multiple imputation on
the attribute side.
Thanks,
Chris
P.S. My apologies for double posting to the list. I mistakenly used an
uninformative subject line in the first posting.
--
Christopher Moore, M.P.P.
Doctoral Student
Quantitative Methods in Education
University of Minnesota
m
plement to multiple imputation on
the attribute side.
Thanks,
Chris
--
Christopher Moore, M.P.P.
Doctoral Student
Quantitative Methods in Education
University of Minnesota
moor0...@umn.edu
http://www.tc.umn.edu/~moor0554/
On Jan 1 2009, r-sig-geo-requ...@stat.math.ethz.ch wrote:
Date: Wed, 31 Dec
lues before
lagging, or is there a good justification for treating NA as zero when
calculating spatial lags, thereby pulling lagged values downward?
Thanks,
Chris
--
Christopher Moore, M.P.P.
Doctoral Student
Quantitative Methods in Education
University of Minnesota
moor0...@umn.edu
http://www
have provided a reproducible
example below (see the very bottom of the of the example in particular).
Please let me know if you need further clarification.
Regards,
Chris
--
Christopher Moore, M.P.P.
Doctoral Student
Quantitative Methods in Education
University of Minnesota
moor0...@umn.edu
http:
