similar to: RGui crashes on wle call

Dear [R]-list, I'm looking for a classic equivalent of the wle.gamma function (library wle) that estimate robustly the shape and the scale parameters of gamma data. I have a vector of iid gamma rv : >data=rgamma(100,shape=10,scale=3) and a vector of their weights: >weights=c(rep(.5/70,70),rep(.25/20,20),rep(.25/10,10)) and want to estimate the scale and shape of the gamma

Hi, all When I am using mle.cv(wle), I find a interesting problem: I can't do leave-one-out cross-validation with mle.cv(wle). I will illustrate the problem as following: > xx=matrix(rnorm(20*3),ncol=3) > bb=c(1,2,0) > yy=xx%*%bb+rnorm(20,0,0.001)+0 > summary(mle.cv(yy~xx,split=nrow(xx)-1,monte.carlo=2*nrow(xx),verbose=T), num.max=1)[[1]] mle.cv: dimension of the split subsample

Hello, I have a question pertaining to the stepwise regression which I am trying to perform. I have a data set in which I have 14 predictor variables accompanying my response variable. I am not sure what the difference is between the function "mle.stepwise" found in the wle package and the functions "step" or "stepAIC"? When would one use

Buenas tardes, Estoy intentando ajustar distribuciones utilizando un vector de ponderación en los datos (Weighted Likelihood). ¿Existen paquetes en R que resuelven esto? He mirado ya el paquete "wle" pero no me permite introducir los pesos mediante los cuales ponderar los datos. En un primer momento, se me ha ocurrido realizar lo siguiente: repetir cada elemento del vector datos

I haven't seen this cryptic warning before: > update.views('Robust') Warning message: In update.views("Robust") : The following packages are not available: covRobust, distr, FRB, MASS, mblm, multinomRob, mvoutlier, quantreg, RandVar, rgam, RobAStBase, robfilter, RobLox, RobRex, robust, RobustAFT, robustbase, ROptEst, ROptRegTS, rrcov, sandwich, wle >

======================================================================= Simple CRAN packages which do not compile without modifications (all others do) ======================================================================= -- akima /usr/bin/ld: multiple definitions of symbol _idlc_ -- fracdiff /usr/bin/ld: multiple definitions of symbol _gammfd_ (and others) -- odesolve --

I have re-built all the compiled packages for R 1.2.0 for Windows, and the set available in CRAN/bin/windows/contrib are now for rw1020. If you are upgrading to rw1020, please replace all the compiled packages you have downloaded by ones from this set. There a few packages available for the first time: RMySQL mlbench netCDF and a few that are not yet running on 1.2.0 on any platform hdf5

I have re-built all the compiled packages for R 1.2.0 for Windows, and the set available in CRAN/bin/windows/contrib are now for rw1020. If you are upgrading to rw1020, please replace all the compiled packages you have downloaded by ones from this set. There a few packages available for the first time: RMySQL mlbench netCDF and a few that are not yet running on 1.2.0 on any platform hdf5

Hola! Anybody knows if there exists somewhere in R some implementation of robust Poisson regression, where robust is taken in the sense as usen in rlm(MASS). I found something in the package wle, but only for the Poisson distribution, not for regression. For the moment I try to use linear models with the square-root transformation, and rlm. Kjetil -- Kjetil Halvorsen. Peace is the most

Here's a more general question following up on the specific question I asked earlier: Can anybody recommend an R command other than mle.aic() (from the wle package) that will give back a ranked list of submodels? It seems like a pretty basic piece of functionality, but the closest I've been able to find is stepAIC(), which as far as I can tell only gives back the best submodel, not a

Hi, I have the response variable 'Y' and four predictors say X1, X2, X3 and X4. Assuming all the assmptions like Y follows normal distribution etc. hold and I want to run linear multiple regression. How do I run the stepwise regression (forward as well as the backward regression). >From other software (i.e. minitab), I know only X1 and X2 are significant so my regression equation

Hi All: Package TSERIES is stated to depend on MVA. However, there is no MVA package to be found under the list of package sources. Best wishes, ANDREW tseries: Package for time series analysis Package for time series analysis with emphasis on non-linear and non-stationary modelling Version: 0.7-6 Depends: ts, mva, quadprog Date: 2001-08-27 Author: Compiled by Adrian

Hello, I cannot figure out how to shade between two lines in a plot. For example, if I am trying to plot a confidence envelope and I would like to shade the interior of the envelope grey. Is this possible in R? Thanks in advance. Heather Lynch

-------------- next part -------------- An embedded message was scrubbed... From: Hella Heikki <Heikki.Hella at bof.fi> Subject: R code and robust regression Date: Tue, 12 Dec 2000 12:12:14 +0200 Size: 2187 Url: https://stat.ethz.ch/pipermail/r-help/attachments/20001212/c3361c7d/attachment-0001.mht

Hi all -- I have to calculate a likelihood ratio test for a logit model. I found logLik, but I need to calculate the log likelihood for the model without any predictors. How can I specify this in glm? If the full model is glm(y ~ x1), is the one without predictors (y ~ 0)? Or (y ~ 1)? Is there a more direct way of getting this? -- Chris

I am running R 1.2.1 under Mandrake Linux 7.2 (installed from RPM) and I installed a few packages using install.packages() . Now, I am trying to upgrade these packages using update.packages() but I believe I am running into some kind of error. See below. Any tips will be greatly welcome. Thanks in advance. Francisco PS: update.packages() only tries to update wle from version 0.3 to 0.4, gives

¡Muchas gracias Olivier! Un saludo. El 16 de abril de 2015, 10:44, Olivier Nuñez <onunez en unex.es> escribió: > Mira el paquete survey. > Un saludo. Olivier > > ----- Mensaje original ----- > De: "Víctor Nalda Castellet" <victor.nalda.castellet en gmail.com> > Para: "r-help-es" <r-help-es en r-project.org> > Enviados: Miércoles, 15 de

Subject: Eliminate repeated components from a vector X-Mailer: VM 7.00 under 21.4 (patch 6) "Common Lisp" XEmacs Lucid Reply-To: fjmolina at lbl.gov FCC: /home/f/.xemacs/mail/sent Does anyone know how I can eliminate repeated elements from a vector?

I've been given the job of extracting some data from the United States 2000 census (files at http://www2.census.gov/census_2000/datasets/Summary_File_2/Maryland/all_ Maryland.zip 52M). I'm only interested in Census Block Groups (CBGs) located within Baltimore City, Maryland. Additionally, I just have to extract certain data fields. I think I'll be using Summary File 2. This is my first

I am wondering if there is an R function that could estimate a generalized nonlinear mixed model. >From my reading it seems that nlme from the nlme package can fit nonlinear mixed models, while lmer from the lme4 package can fit generalized linear mixed models. One alternative I?ve found is gnlmix from the repeated package, although this only allows for a single random effect. Is there