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...couldn't find function predict.smooth.spline. The function smooth.spline() is OK. What am I missing? ====================================== I.White ICAPB, University of Edinburgh Ashworth Laboratories, West Mains Road Edinburgh EH9 3JT Fax: 0131 650 6564 Tel: 0131 650 5490 E-mail: iwhite at staffmail.ed.ac.uk

...Rcmd exec: INSTALL: not found. Indeed /usr/lib/R/bin seems to lack various shell scripts (INSTALL, REMOVE, etc). ====================================== I.White University of Edinburgh Ashworth Laboratories, West Mains Road Edinburgh EH9 3JT Tel: 0131 650 5490 Fax: 0131 650 6564 E-mail: iwhite at staffmail.ed.ac.uk

...I may have missed some reason why it can't be used. Perhaps it doesn't work when intercept=FALSE? ====================================== I.White ICAPB, University of Edinburgh Ashworth Laboratories, West Mains Road Edinburgh EH9 3JT Fax: 0131 650 6564 Tel: 0131 650 5490 E-mail: iwhite at staffmail.ed.ac.uk

...pancy between the two forms of output is > # confusing. > proc.time() [1] 1.60 0.08 1.65 0.00 0.00 > ====================================== I.White ICAPB, University of Edinburgh Ashworth Laboratories, West Mains Road Edinburgh EH9 3JT Fax: 0131 667 3210 Tel: 0131 650 5490 E-mail: iwhite@staffmail.ed.ac.uk ====================================== -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-devel mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body&quo...

...R package? I have Fox' "R and S-Plus Companion to Regression". I'm aware that this is a very basic question - thank you for your patience! Maria Wolters -- Dr Maria Wolters CSTR / HCRC, School of Informatics MATCH Research Fellow EdSST Project Manager mwolters AT staffmail.ed.ac.uk -- The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336.

...package:methods, package:ctest, package:mva, package:modreg, package:nls, package:ts, Autoloads, package:base ====================================== I.White ICAPB, University of Edinburgh Ashworth Laboratories, West Mains Road Edinburgh EH9 3JT Fax: 0131 650 6564 Tel: 0131 650 5490 E-mail: iwhite@staffmail.ed.ac.uk

...a contrast, but not the value of the contrast itself. Wouldn't this be useful? Am I missing something? ====================================== I.White ICAPB, University of Edinburgh Ashworth Laboratories, West Mains Road Edinburgh EH9 3JT Fax: 0131 650 6564 Tel: 0131 650 5490 E-mail: iwhite at staffmail.ed.ac.uk

Could anyone help with a linear mixed model fitting problem ? The model is : Y= Xp + Zu + e where X, Z are known design matrix, p is fixed effect factor, u is random effect, u~ (0, G) , e~(0,R) The main problem is , I want to fix the covariance matrix G to be a constant times a known covariance matrix A, G = c*A (c is positive constant, A is a predefined matrix with values manually set by

I am seeking for a method to calculate, given a fitted lme model and some data for a subject, the random effects predictors for this subject. I can only find predictors for the subjects used in creating the fit. Of course I could just add the subject and redo the fit. But I want to avoid just this refitting. Thanks for help wbk

Hi, You should look at Pinheiro and Bates (2000) Mixed-effects models in S and S-Plus. It describes how to format the correlation matrix to pass to functions lme and gls. Basically, the correlation matrix has to be one of the corStruct classes, probably corSymm for your example. So in the call to lme (or gls if you really have no random effects), use something like:

Hello everyone, I hope this is a fair enough question, but I don’t have access to a copy of Bates and Pinheiro. It is probably quite obvious but the answer might be of general interest. If I fit a fixed effect with an added quadratic term and then do it as an orthogonal polynomial using maximum likelihood I get the expected result- they have the same logLik.

Hi, I've generated a cox model, but I'm struggling to work out how to output predctions based on the model I've made. my.model<-coxph(Surv(duration,status) ~ gender + var1 + var2, data=mydata) My test data set looks something like this: id,actualduration,gender,var1,var2 a,65,m,1,3 b,34,f,1,5 ... What i need to do is for each id, output a predicted duration based on my cox

Hi, Does anyone know an easy way of retaining rows in a model.matrix where missing values are present in the predictors. Ideally I'd be able to retain these rows as zeros. Thanks, Jarrod -- The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336.

Does lme prediction work correctly with poly() terms? In the following simulated example, the predictions are wildly off. Or am I doing something daft? Milk yield for five cows is measured weekly for 45 weeks. Yield is simulated as cubic function of weekno + random cow effect (on intercept) + residual error. I want to recover an estimate of the fixed curve. ############### library(nlme)

Hi I thought this was something that might concern the developers so I thought I'd post here. Apologies in advance if that's not the case. I'm setting up a CentOS cluster with OpenSSH_4.3p2 which uses ssh to launch processes on the remote nodes. I'm trying to use the SendEnv/AcceptEnv functionality to send the PATH environment variable from the headnode when users are launching

Hi, I have a bit of a problem with as.numeric or as.double. I read in an excel-file (either xlsx::read.xlsx2 or gdata::read.xls). Select a subset and then try to make it numeric: # read in the excel-file alldata<-read.xlsx2("input.xls",1) # select the subset s<-subset(alldata, select=c("cI","cII","cIII","cIV","cV")) # unluckily