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Dear R users I encounter a problem when i perform a generalized linear mixed model (binary data) with the lmer function (package lme4) with R 2.1.0 on windows XP and the latest version of package "lme4" (0.96-1) and "matrix" (0.96-2) both options "PQL" and "Laplace" for the method argument in lmer function gave me the same results (random and fixed effects

...t KalmanForecast and at the C code of KalmanFore, but it did not help me understand what was going on. thanks Franck A. btw, it has nothing to do with it, but i've done some stuff on time series (filtering with Hodrick prescott or Baxter King, for instance) that you can find on http://arnaud.ensae.net [[alternative HTML version deleted]]

Hello R users Would somebody know how to estimate survival from a frailty cox model, using the function survfit and the argument newdata ? (or from any other way that could provide individual expected survival with standard error); Is the problem related to how the random term is included in newdata ? kfitm1 <- coxph(Surv(time,status) ~ age + sex + disease + frailty(id,

Hello, I am trying to estimate a choice model with varying choice set for each individual. I would like to fit different kinds of model (logit ,nested logit, probit...). So far I have found that package *mnp* allows me to estimate a probit model with varying choice set. But for estimation of a logit model, I have only found function *multinom* of package *nnet* which does not seem to allow for

Helo, I'm looking for package and database concerning egalisation in telecommunication. Please can you help me to find it on R. Thank you for your help. -- Fatima-Zahra ELGHAZOULI Elève Ingénieur GSTR5 ENSA Tanger ----- www.ensat.ac.ma [[alternative HTML version deleted]]

Full_Name: Maxime To Version: 2.9 OS: WIndows Submission from: (NULL) (81.57.236.122) I am using the npindex and npindexbw fubctions of the NP package. I would like to compute the predicted values of the model and tried to use the predict function for this purpose but the function only gives me the summary of the model but no vector of predicted values as with any other model. Simply using the

I'm trying to use garchFit from fSeries, with Student or Skewed Student conditionnal distribution. Let's say that eps (vector) is my series of daily log-returns: data(EuStockMarkets) eps = diff(log(EuStockMarkets[,"CAC"])) library(fSeries) g = garchFit(series = eps, formula.var = ~garch(2,2), cond.dist = "dstd") s = g at fit$series All the coefficients are ok