similar to: puzzles with assign()

Running the Chapter 4 examples in Pinheiro & Bates' "Mixed-Effects Models in S and S-PLUS" (2000), I get a message that the default optimizer doesn't converge, but using "optim" for the optimizer results in convergence: > > library(nlme) > > fm1IGF.lis <- lmList(IGF) > > fm1IGF.lme <- lme(fm1IGF.lis) > Error in lme.formula(fixed =

Dear R users, I have been trying to obtain the MLE of the following model state 0: y_t = 2 + 0.5 * y_{t-1} + e_t state 1: y_t = 0.5 + 0.9 * y_{t-1} + e_t where e_t ~ iidN(0,1) transition probability between states is 0.2 I've generated some fake data and tried to estimate the parameters using the constrOptim() function but I can't get sensible answers using it. I've tried using

All, Given the following commands: > ag.m35<-read.table("m35.txt",header=TRUE,sep=",") > ag.m35.lp<-subset(ag.m35, race=="lp") > aov.m35.lp=aov(year~time,data=ag.m35.lp) > anova.m35.lp=anova(aov.m35.lp) > anova.m35.lp Analysis of Variance Table Response: year Df Sum Sq Mean Sq F value Pr(>F) time 1 11.56 11.5649 1.7282

Hola! I have some problems with gam in mgcv. Firts a detail: it would be nice igf gam would accept an na.action argument, but that not the main point. I want to have a smooth term for time over a year, the same pattern repeating in succesive years. It would be natural then to impose the condition s(0)=s(12). Is this possible within mgcv? I tried to obtain this with trigonometric terms, aca:

I'm transferring 1.1 Mb files over very poor GSM EDGE connection. My rsync command is: rsync --partial --remove-source-files --timeout=120 --append --progress --rsh=ssh -z LOCAL_FILE root at SERVER:REMOTE_PATH File on remote server "grows" in size in steps of 262144 bytes. That is a lot, because system needs to transfer at least 262144 (before compression) every time connection

I need some guidance from someone who is familiar/has some experience with the survey package. The data that I am using is from the Medical Expenditure Panel Survey (www.meps.ahrq.gov <http://www.meps.ahrq.gov/> ). The STRATA and PSU variables are varstr01 and varpsu01 respectively. When I try to specify them with the svydesign function I get an error message. An excerpt of my session

I have been attempting to set up RH9 as a file server using Windows authentication. I have winbind running and both the wbinfo, and getent passwd commands return users and groups from the windows domain. Samba is set up, using the gui but when I try and add users, the domain users do not appear in the list. I am sure the gurus will tell me not to use the gui's but I am really new at this

> > It was essentially my own mistake. After the Embedded C++ IDE crashed unexpectedly, > the .lib file was no longer present in the project settings (the project had not been saved) > so all the errors I got were caused by a missing .lib reference in the link stage! > I had to change my cross compiler target to "arm-wince-pe" because otherwise the > object/.lib files

I'm getting an interesting problem. I can create/rename/delete/edit policies, but I can't change the security filtering or delegation settings. When I first open any policy, I get the following: "The permissions for this GPO in the SYSVOL folder are inconsistent with those in Active Directory. It is recommended that these permissions be consistent. To change the SYSVOL permissions

I'm looking at Pinheiro & Bates "Mixed-Effects Models in S and S-PLUS" at the moment. Several datasets are used, one of which is called "PBIB" (a partially balanced incomplete block design). All the other datasets can be found somewhere or other in R. However, I cannot locate PBIB, and it does not seem to be mentioned in the latest edition of the R Full Reference

Dear R users, I'm trying to use function 'refit' from lme4 and I get this error that I can't understand: > refit(dolo4.model4,cbind(uu,50-uu)) Error in function (classes, fdef, mtable) : unable to find an inherited method for function "refit", for signature "mer", "matrix" if I try: > refit(dolo4.model4,uu) Error in asMethod(object) :

Hi Is there any way to fit a bivaraite longitudinal mixed model using R. I have a data set with col names resp1 (Y_ij1), resp2 (Y_ij2), timepts (t_ij), unit(i) j=1,2,..,m and i=1,2,..n. I want to fit the following two models Model 1 Y_ij1, Y_ij2 | U_i = u_i ~ N(alpha + u_i + beta1*t_ij, Sigma) U_i ~ iid N(0, sigu^2) Sigma = bivariate AR structure alpha and beta are vectors of order 2.

I have a model “Conversation” and a model “Leader”. A Conversation is always led by exactly 1 Leader. I’ve overridden Conversation’s “validate” method to validate the presence of an associated Leader model. If I add a similar validation to the Leader model, however, Conversations can no longer be saved on creation because the Leader model is invalid. On creation of both a new Conversation and

Hi all! I would like to import a matlab or gauss code to R. Could you help me? Bye, Sebasti?n. 2007/6/23, r-help-request en stat.math.ethz.ch <r-help-request en stat.math.ethz.ch>: > Send R-help mailing list submissions to > r-help en stat.math.ethz.ch > > To subscribe or unsubscribe via the World Wide Web, visit >

Hello, I am new to R and have a couple of questions. My data set contains the variables "Bwt" and "Hwt", which are bodyweight and heartweight, respectively, of a group of cats. With the following code, I am making two plots, both to be viewed in the same plot window in R: library(MASS) maleData <- subset(cats, Sex == "M") linreg0 <- lm(maleData$Hwt ~

Hello, everyone! I'd like to find out how I can do first log differences in a panel? (The Penn World Table data that's available in the PWT package) The regular diff() function ignores the country/index/"panel unit", with depressing results. A second request, how can I best "filter" the data (e.g. generate a data frame with the data for a single country or a single

Dear All, For logistic regression models: is it possible to use validate (rms package) to compute bias-corrected AUC, but have variable selection with AIC use step (or stepAIC, from MASS), instead of fastbw? More details: I've been using the validate function (in the rms package, by Frank Harrell) to obtain, among other things, bootstrap bias-corrected estimates of the AUC, when variable

I simply put, > NEVER=subset(infants$bwt,ISNO1) > UNTILPREGNANT=subset(infants$bwt, ISNO2) > ONCENOTNOW=subset(infants$bwt, ISNO3) and I wanna combine those three. I do it like ISNO=NEVER&UNTILPREGNANT&ONCENOTNOW and R tells me 1: In NEVER & UNTILPREGNANT : longer object length is not a multiple of shorter object length 2: In NEVER & UNTILPREGNANT & ONCENOTNOW

Dear R users, The nnet package includes the multinom method for the confint function. The R Help file (?confint) for the generic function in the stats package and the help files for the glm and nls methods in the MASS package indicate that one can use the "parm" argument as "a specification of which parameters are to be given confidence intervals, either a vector of numbers or

Dear List-Members, I have a problem with the function lqs() from package MASS. In some cases it produces different results for the same settings and needs a random seed to be set, in other cases not. I really cannot understand, why this happens. As well I do not understand what exactly you need the random seed for. Is it a starting point for iterations? Or do different results occur because of