similar to: NLME and NA:s

Hello, are there any good methods in R that will test if two correlation matrices (obtained in different ways) are equal? Something better than the Mantel test would be preferable. Regards, Patrik Waldmann -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info",

Hello again, I was too quick before. What I was looking for was a function that constructs the design (or incidence) matrix (X in a linear model) from a factor. Uwe Ligges suggested using model.matrix and this does almost what I want, but it is first necessary to construct a data variable. It also asigns ones to all rows of the first column (because this is set to be the contrast, not really what

Hello, I wonder if someone could send me suggestions on how to solve the following problem: I have a vector of an arbitrary size (ex. data<-c(10,10,11,10,12,11,10,12,11,11,10,11)) and use the table function, which gives the following result 10 11 12 5 5 2 that''s fine, but what I would like to do now is: construct new classes based on the number of classes from table, 10

Hello, I wonder if someone could help me with the following: I have generated 10 000 values from rnorm and now I want to randomly replace 500 of those with NA. The problem is that values indexed between 6-10,16-20,26-30.... only should be considered for replacement. Any suggestions? Patrik Waldmann -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing

I wonder if someone could help me adjusting the following code to parallelized snow code: #Creating a data set (not needed to be parallel) n<-100 p<-100 x<-matrix(rnorm(n*p),p) y<-rnorm(n) # Bootstrapping nboot<-1000 alpha<-0.05 rhoboot <- array(0, dim=c(p,nboot)) bootranks <- array(0, dim=c(p,nboot)) bootsamples <- array( floor(runif(n*nboot)*n+1), dim=c(n,nboot)) for

Hello, are there any functions in R for estimation of the mode of a MCMC-chain? Best, Patrik Waldmann [[alternate HTML version deleted]]

I haven't found a function that directly calculates the matrix inverse, does it exist? Otherwise what would be the fastest way to do it? Patrik Waldmann -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the

Dear Ralph, have you already generated/submitted a sitemap for moin? Also Thomas Waldmann suggested to place a prominent link to 'TitleIndex'. Best Regards Marcus

I have one factor with say five levels (fact) of different size and a corresponding variable (var). I randomly generate five new levels (nfact ex. 2,2,1,5,4). What I would like to do is to extract the corresponding variable values into a new variable (nvar). I did try the following, why doesn't it work? nvar<-var[fact==nfact[ ]] Patrik Waldmann

https://bugzilla.mindrot.org/show_bug.cgi?id=2331 Bug ID: 2331 Summary: ssh-copy-id -i id_new.pub fails to copy that id, also: wrong error msg Product: Portable OpenSSH Version: -current Hardware: All OS: Linux Status: NEW Severity: major Priority: P5 Component:

How does one coerce predict.gls to incorporate the fitted correlation structure from the gls object into predictions? In the example below the AR(1) process with phi=0.545 is not used with predict.gls. Is there another function that does this? I'm going to want to fit a few dozen models varying in order from AR(1) to AR(3) and would like to look at the fits with the correlation structure

Dear All -- I am trying to use within a little table producing code an anova comparison of two gls fitted objects, contained in a list of such object, obtained using nlme function gls. The anova procedure fails to locate the second of the objects. The following code, borrowed from the help page of anova.gls, exemplifies: --------------- start example code --------------- library(nlme) ##

https://bugzilla.mindrot.org/show_bug.cgi?id=2110 Bug ID: 2110 Summary: ssh-copy-id fails on nonexisting private key Product: Portable OpenSSH Version: 6.2p1 Hardware: Other OS: Linux Status: NEW Severity: normal Priority: P5 Component: Miscellaneous Assignee: unassigned-bugs

Hello R users, When trying to fit a nonlinear mixed model to a respiration time series, I get the following error message: Error in recalc.varFunc(object[[i]], conLin) : dims [product 30] do not match the length of object [34] In addition: Warning message: In conLin$Xy * varWeights(object) : longer object length is not a multiple of shorter object length Below is an example that generates

Hola a todos Les consulto por un problema con xtable y nlme, tomando un ejemplo del manual de nlme para obtener los resultados en latex utilizando xtable, se puede utilizar el siguiente código, pero hay un problema y causa error. library(nlme) library(xtable) fm1 <- nlme(height ~ SSasymp(age, Asym, R0, lrc), data = Loblolly, fixed = Asym + R0 + lrc ~ 1,

Dear R developers, first of all let me join the chorus of congratulations for the release of R 1.0.0. Well, done! Unfortunately, I find it necessary to e-mail in a bug report regarding the `nlme' package. On my office machine I experience the following trouble: bossiaea:/opt/R$ R CMD check -c nlme Checking package `nlme' ... Massaging examples into `nlme-Ex.R' ... Running

Dear listserv members, In Croissant (2008) “Panel Data Econometrics in R: The plm Package” the authors seem to indicate that the nlme package for R cannot correctly handle unbalanced panel data: “Moreover, economic panel datasets often happen to be unbalanced (i.e., they have a different number of observations between groups), which case needs some adaptation to the methods and is not

I am analyzing a dataset on the effects of six pesticides on population growth rate of a predatory mite. The response variable is the population growth rate of the mite expressed as ln(Nfinal/Nstarting) of the mite, where N final the population of the mite at the end of the experiment and N starting the population of the mite at the beginning of the experiment. Each of the six treatments was ran

Hi, I guess this is a final plea, and maybe this should go to R-help but here goes. I am writing a set of functions for calibration and prediction, and to calculate standard errors and intervals I need the variance function to be evaluated at new prediction points. So for instance fit<-gnls(Y~SSlogis(foo,Asym,xmid,scal),weights=varPower())

I have a need to call and pass arguments to nlme() from within another function. I use R version 1.8. I have found an apparent way to make this work, but I would appreciate some comments on whether this fix is really appropriate, or there is another way to do it that does not involve changing the source code. I don't have enough experience to start changing the sorurce code of a library