similar to: José C. Pinheiro Training in UK - Analyzing Mixed-Effects Models with S-PLUS

S-PLUS ESSENTIALS 24-27th April 2006 Venue : Insightful UK Office, Network House, Basing View, Basingstoke, Hants RG21 4HG We are pleased to be taking registrations for the next scheduled S-PLUS Essentials course being held in Basingstoke 24-27th April 2006. If you are unfamiliar with S-PLUS or have been meaning to upgrade your S-PLUS skills, this is the course for you. This course will be

Insightful are now taking bookings for the Advanced Time Series Modelling course to be held at Carlton Terrace in London SW1 on 20th September. Advanced workshop Extract for Financial Time Series Modelling : The Advanced Time Series Course focuses on the most up to date theory and its application around the following topics (note that not all topics will be covered during the workshop) 1.

Analysis of Microarray Data Using S-PLUS, R and S+ArrayAnalyzer 23rd March 2006 Presenter: Adam Diaz Venue: Insightful UK, Network House, Basing View, Basingstoke, Hants RG21 4HG This is the last chance to register for this unique course being run by a member of Insightful's microarray development team from the US. Extract Microarray technology is complex, and experiments using

Insightful are now taking bookings for the Financial Time Series Modelling course to be held at Carlton Terrace in London SW1 on 12th and 13th April 2005. We are also pleased to offer the 1 day Advanced Time Series Modelling course on April 19th at the same location. Extract for Financial Time Series Modelling : This two day course will provide participants with a working knowledge of a range

2005 APPLIED QUANTITATIVE ANALYTICS IN FINANCE EVENT o OCTOBER 6, 2005 o LONDON Please join us at the Museum of London for a series of guru-led presentations, networking, and demonstrations by academic and business thought leaders in finance from Basel II Committee, Swiss Union of Raiffeisen Banks, Swiss Federal Institute of Technology (ETH) in Zurich, UBS Warburg, Ingenious Media Plc. and

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Hi everyone This summer we are moving all our UK Linux training short courses over from Fedora Core to CentOS. For more information please visit: http://ce.bromley.ac.uk/linux Thanks very much Clive

(Apologies for cross posting) Mango Solutions are pleased to announce the following public courses in the UK. Date Course Location 29th - 31st October Advanced <http://www.mango-solutions.com/pubadvanceds.htm> S-PLUS Programming Oxford 11th - 13th November R <http://www.mango-solutions.com/pubrprogramming.htm> Programming London 14th November R for

We (Eli Lilly & co) have a vacancy for an experienced industrial statistician who is familiar with mainstream statistical software, particularly Splus (or R) and/or SAS and/or JMP. The role is to provide expertise and training in Statistics in support of process-improvement in all areas of the business, particularly Statistical Process Control, Design of Experiments, and Quality

In your per-phone configuration: <phone1> <reg> ... <divert divert.fwd.1.enabled = "0" divert.fwd.2.enabled = "0" divert.fwd.3.enabled = "0" divert.fwd.4.enabled = "0" divert.fwd.5.enabled = "0" divert.fwd.6.enabled = "0" /> This removes the soft-key and disallows the

Hello! could you give me some advice where i can finde out/recieve/download a GLME package, written by Jose Pinheiro. i couldn'ti find it in the package lists (probably becouse it is still in a beta version). thank you for your replay

Dear Mixed Effect Friends, Somehow, R(1021, Windows) seem to run differently from S Plus: The soybean example from Pinheiro/Bates on page 290 fails in R. (Soybean1 is Soybean with the NA and "critical" case removed. Same procedure with full Soybean). > fm1Soy.lis<-nlsList(weight~SSlogis(Time,Asym,xmid,scal),data=Soybean1) > fm1Soy.nlme<-nlme(fm1Soy.lis) Error: Singularity

Hi everyone. I am trying to add a formula to my data using the groupedData function. My experiment consists of randomized block design using fruits, vegetation and time as factors. The idea is to see if fruits, vegetation and time explain the abundance of mice. I am using tree density as a covariate. So I tried to fit the following structure to my data. >

Estar? ausente de la oficina desde el 19/12/2008 y no volver? hasta el 07/01/2009. Responder? a su mensaje cuando regrese.

Estaré ausente de la oficina desde el 19/12/2008 y no volveré hasta el 07/01/2009. Responderé a su mensaje cuando regrese.

All, Sorry for overly simplistic question, but I can't seem to remember how to create the basic plot shown in Figure 1.1 of Pinheiro & Bates (2004; p.4). The y-axis delineates a factor (Rail) while the x-axis displays the distribution of a continuous variable (time) according to each level of the factor. Didn't see it in archives but perhaps I'm not searching on correct key words,

Hi all, I'm trying to figure out the example about mixed models in the Pinheiro and Bates book (Mixed-Effects Models in S and S-Plus, 2000, pp. 135-137). One thing I don't understand is: When I run the command fm1Orth.lm <- lm( distance ~ age, Orthodont ) followed by fm2Orth.lm <- update( fm1Orth.lm, formula = distance ~ Sex*age ) and then do summary(fm2Orth.lm)

Dear R users, I would like to exactly reproduce a figure like the 1.5 or 1.9 or 4.13 from the book Mixed effects models in S and S-Plus. Not for the sake of it, but because I have my own data I would like to plot in that fashion (no colors) If I write plot(ergoStool) I can get a good informative plot with colors, but I would like to have a B&W one instead. I've played a little with

Hola. Tengo un problema sencillo que no logro desentrañar: Tengo estos tres objetos: a <- as.matrix(with(ProduccionAC, tapply(Costo, Provincia, mean))) b <- as.matrix(with(ProduccionAC, tapply(Costo, Provincia, median))) c <- as.matrix(with(ProduccionAC, tapply(Costo, Provincia, quantile, probs = c(0.25, 0.75, 0.85, 0.90, 0.95)))) Pero resulta que cbind(a,b,c) devuelve este resultado:

Gracias, Javier. Es lo que hice, en efecto, para salir del paso. Requerir de a uno por vez. El problema es que no entiendo por qué debo hacerlo así si quantile es una función más, como cualquier otra, que podría utilizar en un tapply (porque necesito los datos según provincia, que obviamente es un factor) El 8 de julio de 2013 17:25, Marcuzzi, Javier Rubén <