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On Sun, Apr 12, 2009 at 10:23 AM, gianni lavaredo <gianni.lavaredo at gmail.com> wrote: > Dear R User, > > "Buona Pasqua". > I have a simple regression model > > myModel <- lm( y ~ x) > Summary(myModel) > > I wish to save the value...
On Thu, Jan 22, 2009 at 10:48 PM, Chun Zhang <usamelie at yahoo.com> wrote: > Hi all, > I am using cross-validation to validate a generalized linear mixed effects model fitted using glmmPQL. i found that the predict function...
On Thu, Jul 9, 2009 at 6:12 PM, Kitty Lee<lee.kitty at yahoo.com> wrote: > > Hi. I have a dataset of unique coordinates (no missing coordinates). When I did the following: > > lonlat<-mydata[, c("lon, "lat")] > sp1<-corSpatial...
On Wed, Mar 4, 2009 at 8:40 PM, Fuchs Ira <irafuchs at gmail.com> wrote: > So functions in the base package are all written in C? No, a large proportion are written in R and the code can be...
This may help a bit with intuition. Think about randomly picking a spot in the box below and then choosing the nearest neighbor. What's the inclusion probability for 1? What about 6? Clearly not a simple random sample... ----------- |123...
On Tue, Apr 29, 2008 at 6:20 AM, tom soyer <tom.soyer at gmail.com> wrote: > Hi, > > I would like to use a weighted lm model to reduce heteroscendasticity. I am > wondering if the only way to generate the...
How about: a <- c(1,2,3,3,2,1,6,3,2) b <- c(NA,a[-length(a)]) c <- c(a[-1],NA) a[b==1 & c==3] [1] 2 6 hth, Kingsford Jones On Sun, Jan 25, 2009...
See 'mar' under ?par e.g., x <- y <- -100:100 z <- outer(x, y, function(x,y) sqrt(x^2 + y^2)) par(mar=c(0,0,0,0)) image(x,y,z) hth, Kingsford Jones On Wed, Apr 8...
I thought I'd share this with the list since it appears to provide a quick fix to some memory problems, and I haven't see it discussed in relation to R. To reallocate virtual memory from kernel-mode to...
Unangu, If you haven't seen the 200pg workshop notes that Adrian Baddeley has made available from his spatstat webpage, I highly recommend them: http://www.csiro.au/files/files/pn0y.pdf hth, Kingsford Jones On Sat, Jan 10, 2009...
On Tue, Apr 6, 2010 at 3:37 PM, Andrew Dolman <andydolman at gmail.com> wrote: [snip] > > This is not entirely correct. The syntax will work because the populations > are uniquely labeled but it does not model population as nested...
For permutations a couple of options are 'permutations' in package gtools, and 'urnsamples' in package prob hth, Kingsford Jones On Fri, Mar 13, 2009 at 6:35 AM, Dale Steele <dale.w.steele at gmail.com> wrote: > I'm doing...
to make the desired within R's plotting device rather than in latex try: par(mfrow = c(3, 2)) and you'll probably want to adjust other mar, parameters as well (e.g. mar, cex.lab, etc). Or, take advantage...
Hi John, The SIDS examples in the spatial graphics gallery may be helpful: http://r-spatial.sourceforge.net/gallery/ For a general reference, see Applied Spatial Data Analysis with R. Note that the book's webpage includes figures with code...
A few thoughts: -- As for naming preferences, in an interactive R session or answering an R-help question I'm glad I can type lm(log(y) ~ atan(x)) rather than FitLinearModel(CalculateNaturalLogarithm(y) ~ CalculateInverseTangent(x)) -- For consistency, their function...
Hi Bessie, library(lattice) x <- rep(1:3, each=20) y <- rnorm(60, x) x <- c('level1', 'level2', 'level3')[x] stripplot(y ~ x) # or perhaps stripplot(x ~ y, jitter=TRUE) Kingsford Jones On Fri, Jun 5, 2009 at 5:02...
Hi Danielle, If you don't get an answer here you might want to look at chapter 4 of Applied Spatial Data Analysis with R, or ask on the r-sig-geo list. hth, Kingsford On Thu, Jan 28, 2010...
help(gnls, pack=nlme) hth, Kingsford Jones On Thu, Oct 22, 2009 at 4:36 PM, Michael A. Gilchrist <mikeg at utk.edu> wrote: > Hello, > > I've been fitting a random effects model using nlme to some data, but I...
See ?"[" and its examples Also, section 2.7 of An Introduction to R is a good place to start: http://cran.r-project.org/doc/manuals/R-intro.html#Index-vectors hth, Kingsford Jones On Mon, Feb 9, 2009 at...
See the nlme library and accompanying book by Pinheiro and Bates. The lme function is appropriate for linear mixed models with normal errors, and the 'weights' argument provides flexible methods for modeling error heterogeneity. hth, Kingsford On Mon, Nov 2...
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