similar to: installing new packages

I am writing a package which uses the Rgraphviz package which in turn uses the graph package, but my question does not (I believe) pertain specifically to the these packages so therefore I dare to post the question here: I my package I have a function "edges" which works on some graphs I have defined. However, there is also a function "edges" (or rather a generic method) in

I have some questions and observations about these: Will these replace manually setting options(CRAN), which doesn't work in R-2.1.0? In R-2.1.0, setRepositories() looks to see if options("repos") contains a CRAN entry and will not override that CRAN entry even if the $R_HOME/etc/repositories file (which setRepositories reads from) contains a CRAN entry. Why is this? The user

Hello. Please excuse this off-topic request, but I know that the question has been debated in summary form on this list a number of times. I would find a paper that lays out the advantages and disadvantages of using different types of SS in the context of unbalanced data in ANOVA, regression and ANCOVA, especially including the use of different types of contrasts and the meaning of the

To avoid angry replies, let me first say that I know that the use of Type III sums of squares is controversial, and that some statisticians recommend instead that significance be judged using the non-marginal terms in the ANOVA. However, given that type III SS is also demanded by some… is there a function (equivalent to drop1 for lm) to obtain type III sums of squares for mixed models using the

Hello. I am sorry for posting a (seemingly) simple question, but I have just spent 2 hours trying to find the answer, without success. I want to make a histogram with conditioning on a factor, using Trellis graphics. However, I do not want any colours (only black and white) either in the histograms or in the strip. There must be some simple argument but I can’t find it. Here is my code so

Hello. Following pages 342-347 of Pinheiro & Bates, I am trying to write a self-starting nonlinear function (a non-rectagular hyperbola) to be used in nonlinear least squares regression (and eventually for a mixed model). When I use the getInitial function for my self-starting function I get the following error message: > getInitial(photo~NRhyperbola(Irr,theta,Am,alpha,Rd),dat) Error

Hello. I am trying to determine whether I should be using ML or REML methods to estimate a linear mixed model. In the book by Pinheiro & Bates (Mixed-effects models in S and S-PLUS, page 76) they state that one difference between REML and ML is that « LME models with different fixed-effects structures fit using REML cannot be compared on the basis of their restricted likelihoods. In

Hello. Slope estimates in lme are shrinkage estimates which pull the OLS slope estimates towards the population estimates, the degree of which depends on the group sample size and the distance between the group-based estimate and the overall population estimate. Although these shrinkage estimates as said to be more precise with respect to the true values, they are also biased. So there is a

Hello. I have to fit a mixed model from a repeated measures split-plot experiment in which the response variable is binary. This requires a generalised linear mixed model in which I can specify a binomial distribution. I can’t find the appropriate package in R. I have looked at glmmML, but it doesn’t seem to allow any mixed structure beyond a simple 2-level one. Can anyone point me to the

Hello. I want to plot the distribution of a continuous variable (y) in each of two groups on the same graph as histograms. I suppose one could call this a 2-d histogram? Can this be done in R? Here is a typical data.set: y group 1.2 1 3.3 1 2.4 2 5.7 1 0.2 2 etc. Bill Shipley Subject Matter Editor, Ecology North American Editor, Annals of

Hello. I cannot find out how to extract the residuals from a mixed model using the lmer function. Can someone help? Bill Shipley North American Editor, Annals of Botany Editor, "Population and Community Biology" series, Springer Publishing Département de biologie, Université de Sherbrooke, Sherbrooke (Québec) J1K 2R1 CANADA Bill.Shipley@USherbrooke.ca

Dear List: I just successfully installed R 2.8.0 (under Windows XP SP2, 1GB RAM) and wanted to run update.packages. When I first called chooseCRANmirror I obtained the following error message: ---------------- > chooseCRANmirror() Warning message: In open.connection(con, "r") : kann nicht mit 'cran.r-project.org' auf Port 80 verbinden -------------------- What should I do?

I get this error when using chooseCRANmirror(). > chooseCRANmirror() Error in open.connection(file, "r") : unable to open connection In addition: Warning message: unable to connect to 'cran.r-project.org' on port 80. > The TclTk window comes up and I can scroll and select a mirror, but it doesn't appear that I can connect properly. I am using RedHat Enterprise. I

Hello. I am having trouble downloading the lme4 package from the CRAN site. The error is: > local({a <- CRAN.packages() + install.packages(select.list(a[,1],,TRUE), .libPaths()[1], available=a, dependencies=TRUE)}) trying URL `http://cran.r-project.org/bin/windows/contrib/2.0/PACKAGES' Content type `text/plain; charset=iso-8859-1' length 26129 bytes opened URL downloaded 25Kb

Hello. I am about to do a rather complicated analysis and am not sure how to do it. The experiment has a split-plot design and also repeated measures. Both of these complications require one to define an error term and it seems that one cannot specify two such terms. The split-plot command is: aov(y~covariates +A*B+Error(C), data=) where A and B are the fixed effects and C is the

Hello. I am trying to fit a non-rectangular hyperbola function to data of photosynthetic rate vs. light intensity. There are 4 parameters that have to be estimated. I find the nls function very difficult to use because it often fails to converge and then gives out cryptic error messages. I have tried playing with the control parameters but this does not always help. Is there another

Full_Name: Chris Evans Version: 2.10.1 OS: Windows XP sp3 Submission from: (NULL) (86.159.235.204) I was on leave and using a wifi internet connection in France and got connected, launched R (2.10.1 on Windoze XPsp3) and tried to update my packages and got: > chooseCRANmirror() Error in m[, 1L] : incorrect number of dimensions It took me a bit to realise that the message was coming up

Hello. I want to estimate the predicted values and standard errors of Y=f(t) and its first derivative at each unique value of t using the smooth.spline function. However, the data (plant growth as a function of time) show substantial heterogeneity of variance since the variance of plant mass increases over time. What is the consequence of such heterogeneity of variance in terms of bias in the

Hello. I want to specify a diagonal structure for the covariance matrix of random effects in the lme() function. Here is the call before I specify a diagonal structure: > fit2<-lme(Ln.rgr~I(Ln.nar-log(0.0011)),data=meta.analysis, + random=~1+I(Ln.nar-log(0.0011)|STUDY.CODE,na.action=na.omit) and this works fine. Now, I want to fix the covariance between the between-groups slopes

Hello. I am using the nonlinear least squares function (nls). The function that I am trying to fit seems to be very sensitive to the starting values and, if these are not chosen properly, the nls function stops and gives an error message: Error in numericDeriv(form[[3]], names(ind), env) : Missing value or an Infinity produced when evaluating the model In addition: Warning