similar to: Creating a pdf with layers?

Dear all, How can I replace text in objects that are of class "formula"? y="a * x + b" class(y)="formula" grep("x",y) y[1] Suppose I would like to replace the "x" by "w" in the formula object "y". How can this be done? Somehow, the methods that can be used in character objects do not work 1:1 in formula objects... Many

Dear all, I am forced to work in an environment without administrator rights. When using R2.13.1 on Windows 7 (64-Bit), I found that I can?t install or update any packages due to missing writing permissions. I managed to get full access to a directory on my C:\ drive now - but how do I specify that all libraries shall be installed into this directory? In Rcmd_environ I have the following

Dear R users, Let?s say I have 10 models, each named m1,m2,m3..., and I would like to summarize them automatically and simultaneously - e.g., to extract parameter estimates later on from all models; how can I do that? I have tried: x=1:10 #this creates some example data y=rnorm(10) m1=lm(x~y) m2=lm(x~1) sum.lms=function(x)summary(paste("m",x,sep="")) sum.lms(1:2) but

Dear all, Suppose I have a nested, repeated measure lme model. Which of the following formulae is correct? (assuming data are sampled from several plots in an agricultural experiment) (1) y~explanatory.variables,random=~time|block/plot/subplot/individual (2) y~explanatory.variables,random=~time|unique.ID.of.every.individual I have read that (2) is the only approach that works. But how could I

Dear all, Is there a way to retrieve standard errors from nls models? The help page tells me that arguments such as se.fit are ignored... Many thanks and best wishes Christoph -- Dr. rer.nat. Christoph Scherber University of Goettingen DNPW, Agroecology Waldweg 26 D-37073 Goettingen Germany phone +49 (0)551 39 8807 fax +49 (0)551 39 8806 Homepage http://www.gwdg.de/~cscherb1

Dear R users, suppose I have a matrix of observations for which I calculate all pair-wise correlations: m=matrix(sample(1:100,replace=T),10,10) w=cor(m,use="pairwise.complete.obs") How do I extract only those correlations that are >0.6? w[w>0.6] #obviously doesn?t work, and I can?t find a way around it. I would very much appreciate any help! Best wishes Christoph (using R

Dear all, How can I extract the total and residual d.f. from a gnls object? I have tried str(summary(gnls.model)) and str(gnls.model) as well as gnls(), but couldn?t find the entry in the resulting lists. Many thanks! Best wishes Christoph -- Dr. rer.nat. Christoph Scherber University of Goettingen DNPW, Agroecology Waldweg 26 D-37073 Goettingen Germany phone +49 (0)551 39 8807 fax +49

Dear R users, Assume I have three models with the following AIC values: model AIC df model1 -10 2 model2 -12 5 model3 -11 2 Obviously, model2 would be preferred, but it "wastes" 5 df compared to the other models. Would it be allowed to select model3 instead, simply because it uses up less df and the delta-AIC between model2 and model3 is just 1? Many thanks for any

Dear all, For an introductory course on glm?s I would like to create an example to show the difference between glm and transformation of the response. For this, I tried to create a dataset where the variance increases with the mean (as is the case in many ecological datasets): poissondata=data.frame( response=rpois(40,1:40), explanatory=1:40) attach(poissondata) However, I have run into

Dear all, I am fitting a multivariate linear model with 7 response variables and 1 explanatory variable. The following matrix P: P <- cbind( c(1,-1,0,0,0,0,0), c(2,2,2,2,2,-5,-5), c(1,0,0,-1,0,0,0), c(-2,-2,0,-2,2,2,2), c(-2,1,0,1,0,0,0), c(0,-1,0,1,0,0,0)) should consist of orthogonal elements (as can be shown using %*% on the individual columns). However, when I use

Dear R users, Suppose I have a set of 10 candidate models, and these all differ by a delta-AIC of 5. Would it be sensible, then, to choose the best-fit model as the one that has *both* minimal AIC *and* minimal number of d.f.? Are there any references for such an approach? Many thanks for your help! Best wishes, Christoph -- Dr. rer.nat. Christoph Scherber University of Goettingen DNPW,

Dear R users, I am analyzing several response variables (all scaled to [0;1]) using a multivariate linear model. After fitting the model, I set up a hypothesis matrix to test specific contrasts for these response variables; for example: "a always increases significantly more than b when regressed against x". What I am stuck with now is how to calculate the correct F-values (and

Hello, We are attempting to use nlme to fit a linear mixed model to explain bird abundance as a function of habitat: lme(abundance~habitat-1,data=data,method="ML",random=~1|sampleunit) The data consist of repeated counts of birds in sample units across multiple years, and we have two questions: 1) Is it necessary (and, if so, how) to specify the repeated measure (years)? As written,

I have data that looks like YC Age Num 82 11 2 83 10 0 84 9 8 85 8 21 86 7 49 87 6 18 88 5 79 89 4 28 90 3 273 91 2 175 with a program mod1=lm(log(Num+1)~YC, data=box44) plot(log(Num+1)~YC, data=box44, pch=19, xlab="Year Class", ylab="Loge Number at age", ylim=c(0,6), xlim=c(91,82)) abline(lm(log(Num+1)~YC), col="blue", lwd=2) summary(mod1) I need to

Dear all, I got this error message > library(dprep) > mardia(Savg) Error in cov(data) : 'x' is empty But with the same data, I got > library(mvnormtest) > mshapiro.test(Savg) Shapiro-Wilk normality test data: Z W = 0.9411, p-value = 0.6739 What does the error message "Error in cov(data) : 'x' is empty" mean? Thanks a lot! Jiao

Sorry for asking - but I found or understood nothing appropriate in the FAQs etc. I run a Samba print service (1.9.18p7) on a FreeBSD box for the university of Goettingen. Authentification is user-based and done by an NT system. Everyone who wants to print must have an account on that system. There are a lot of NT domains on the campus, of course. If now someone tries to connect to a print

Hi, I have the following (probably trivial) problem: I am running a Windows 95 System and have setted the environment variables R_HOME and especillay R_USER in the autoexec.bat. The idea was, to invoke R at the startup to read in the files .Renviron and .Rprofile from my home directory, even when the current working directory is somewhere else. Subject to the manual it should work, but it does

I have a problem with function 'inout()' in package 'splancs' on CRAN-R Version 1.2.3 under FreeBSD4.3-STABLE. The following script produces and draws points and a polygon-surrounded area. Repeating the same script many times shows, that points on the polygon-line often, but not always, are outside of the polygon-area. library(splancs) # dataset with polygon (convex

Hi everyone, every comment about this: http://xforce.iss.net/xforce/xfdb/16264 Didn't find any hint or patch on http://www.xfree86.org/security/. Best regards Konrad Heuer (kheuer2@gwdg.de) ____ ___ _______ GWDG / __/______ ___ / _ )/ __/ _ \ Am Fassberg / _// __/ -_) -_) _ |\ \/ // / 37077 Goettingen /_/ /_/

1. If your code actually runs, you should upgrade R, and quit using `_' for assignment... 8-) 2. You seem to have an extraneous `]' after the na.exclude. Could that be the problem? Andy > From: Christoph Scherber > > actually, the situation is much more complicated. I am producing > multiple graphs within a "for" loop. For some strange reason, the >