search for: ieu

...t work either. What am I doing wrong? Any help would be most appreciated Best benedikt -- Benedikt Gehr Ph.D. Student Institute of Evolutionary Biology and Environmental Studies University of Zurich Winterthurerstrasse 190 CH-8057 Zurich Office 13 J 36b Phone: +41 (0)44 635 49 72 http://www.ieu.uzh.ch/staff/phd/gehr.html

...but that release in 2000. Any suggestions are highly appreciated. Thanks already! Kaya PS: I know I could try WineX but even there I've read same errors, even though it's reported working- is it something with the hardware? -- Kaya O?uz http://www.geocities.com/kayaoguz/ http://stdhomes.ieu.edu.tr/~kayaoguz/ Get Firefox! <http://www.spreadfirefox.com//?q=affiliates&id=4079&t=85> -------------- next part -------------- Skipped content of type multipart/related

Hi I implemented the age-structure model in Gove et al (2002) in R, which is a nonlinear statistical model. However running the model in R was very slow. So Dave Fournier suggested to use the AD Model Builder Software package and helped me implement the model there. ADMB was incredibly fast in running the model: While running the model in R took 5-10 minutes, depending on the

Hi there I am using mle2 for a multinomial likelihood optimization problem. My function works fine when I'm using simulated data, however my cell probabilities of the true data for the multinomial likelihood are sometimes very small (in some cases <0.00...) and the estimated point estimates fit the true vlaues quite poorly. Is there a way how to handle near zero probabilities in

Hi there I'm trying to find the mle fo a multinomial model ->*L(N,h,S?x)*. There is only *N* I want to estimate, which is used in the number of successes for the last cell probability. These successes are given by: p^(N-x1-x2-...xi) All the other parameters (i.e. h and S) I know from somewhere else. Here is what I've tried to do so far for a imaginary data set:

Dear all, In lme, models in which a factor is fully "contained" in another lead to an error. This is not the case when using lm/aov. I understand that these factors are aliased, but believe that such models make sense when the factors are fitted sequentially. For example, I sometimes fit a factor first as linear term (continuous variable with discrete levels, e.g. 1,2,4,6), and

Dear all, I am not sure if this mail is for R-help or should be sent to R-devel instead, and therefore post to both. While using nlrob from package 'robustbase', I ran into the following problem: For psi-functions that can become zero (e.g. psi.bisquare), weights in the internal call to nls can become zero. Example: d <- data.frame(x=1:5,y=c(2,3,5,10,9)) d.nlrob <-

Hi I'm trying to read a data file with output from another program (admb) into R for further analysis. However I'm not very successfull. The file extension for the data file is file.rep but it also doesn't help when I change it to file.txt I have two problems/questions: 1. The file is a single line of n values separated by a single space tab each. These values represent a time

...to create some directory. However I need to know whether such directory already exists or not, otherwise I will create that. Thanks, [[alternative HTML version deleted]] ------------------------------ Message: 7 Date: Fri, 29 Oct 2010 13:12:31 +0200 From: Benedikt Gehr <benedikt.gehr@ieu.uzh.ch> To: r-help@r-project.org Subject: [R] true time series lags behind fitted values in arima model Message-ID: <4CCAAC1F.5000507@ieu.uzh.ch> Content-Type: text/plain; charset=ISO-8859-1; format=flowed Hi I am fitting an arima model to some time series X. When I was comparing the fi...

Hi I'm trying to maximize a joint likelihood of 2 likelihoods (Likelihood 1 and Likelihood 2) in mle2, where the parameters I estimate in Likelihood 2 go into the likelihood 1. In Likelihood 1 I estimate the vector logN with length 37, and for the Likelihood 2 I measure a vector s of length 8. The values of s in Lieklihood 2 are used in the Likelihood 1. I have 2 questions: ##1 I manage

Hi I'm using mle2 for optimization of a multinomial likelihood. The model fit is not very good and I would like to look at the likelihood profiles. However I'm optimizing many parameters (~40) so using the function profile() takes forever and is not practical. How can I calculate approximate likelihood profiles? Is there a function for this in R? thanks a lot for the help Beni

Hi I'm trying to fit arima models with the arima() function and I have two questions. ###### ##1. ## ###### I have n observations for my time series. Now, no matter what arima(p,d,q)- model I fit, I always get n residuals. How is that possible? For example: If I try this out myself on an AR(1) and calculate the fitted values from the estimated coefficients I can calculate n-1 residuals.

Hi I would like to use arima () to find the best arima model for y time series. The default in arima apparently is to use conditional sum of squares to find the starting values and then ML (as described on the help page). Now using the default may lead to error messages saying: "non-stationary ar part in CSS". When changeing the default to "ML" only the minimization

Hi I posted this problem yesterday but didn't get a reply so I try again today. I hope someone can help me with this. thank you very much for the help cheers Benedikt I would like to use arima () to find the best arima model for a time series. The default in arima apparently is to use conditional sum of squares to find the starting values and then use ML for the

Hi I am fitting an arima model to some time series X. When I was comparing the fitted values of the model to the true time series I realized that the true time series lags one time step behind the fitted values of the arima model. And this is the case for any model. When I did a simple linear regression using lm to check, I also find the same results, that the true series lags behind the

Dear all, I experience a problem in implementing a S4 class in a package and would appreciate your help in this matter. The class is implemented using Rcpp, which works well. I then extend the class with R functions, adding them as methods with a call to setMethod(...). When I do this outside the package (after loading the package with "library(...)"), everything works smoothly.

Hi all, Is there a way to modify the optional arguments (...) passed to a function, so that these can be passed in modified form to a subsequent function call? I checked "Programming with Data" but could not find a solution there. What I'd like is something along these lines: test <- function(x,y,...) { if(!hasArg(xlab)) { ___add xlab to ...___ } if(hasArg(xlab)) {

hi I'm trying to use the function odiag(x) for matrix calculations. I would like to assign new values to an off-diagonal in a matrix. When I use the diag (x) function I could write something like p<-matrix(seq(1:12),ncol=4) p.new<-matrix(rep(0,12),ncol=4) diag(p.new)<-diag(p) p.new But this won't work with odiag. How can I turn odiag (x) into something like diag (x) in order

Hi everyone I am new to the list and read all the instructions, hope i get it right. I have the following linear model: model_sqrt<-lm(sqrt(mortality)~richness +Acer_davidii+Ailanthus_altissima+Alniphyllum_fortunei +Betula_luminifera+Castanea_henryi+Castanopsis_carlesii +Castanopsis_eyrei+Castanopsis_fargesii+Castanopsis_sclerophylla

Hi I'm trying to run an admb model from R by using the system () command. The admb model runs fine when running it from the admb command line or when using emacs. However when I try it with system() then R crashes every time. And I tried using the R command line and RGui and in both it crashes. I also tried it from different computers. What I do is I first set the directory where I keep