similar to: Dealing with heterogeneity with varComb weights

Dear R-help members, I have a question regarding how to use varComb function to specify a variance function for the "weights" in the gls. I need to fit a linear model with heteroscedasticity. The variance function is exp(c0+nu0*W +nu1*W^2) where W is a covariate. Initially I want to use varFunc to define my own variance function following the instruction in the Pinheiro and

Dear R-help members, I have a question regarding how to use varComb function to specify a variance function for the "weights" in the gls. I need to fit a linear model with heteroscedasticity. The variance function is exp(c0+nu0*W +nu1*W^2) where W is a covariate. Initially I want to use varFunc to define my own variance function following the instruction in the Pinheiro and Bates

  Hola,   Por favor, ¿podríais indicarme qué recursos (librerías o ideas) pueden resultar de utilidad para crear un gráfico del estilo del de la figura 3.8 del siguiente link?   http://www.tsc.uvigo.es/BIO/Bioing/ChrLDoc3.html#3.5   Actualmente estoy utilizando funciones muy básicas y la verdad es que no me encuentro muy satisfecha con el resultado.   Muchas gracias.   Eva [[alternative HTML

 Hello everyone, Apologies in advance, as this is partially a stats question and partially an R question.  I have been using a GAM to model the activity level of bats going into and coming out from a forested edge.  I had eight microphones set up in a line transect at each of eight sites, and I am hoping to construct a model for each of 7 species.  My count data has a reverse J-shaped skew and

Hello - I'm trying to modify an option for the lme() or nlme() macros. I want to write my own specification for the variance function and am following homework problem 4, Chapter 5, page 268 of Pinheiro and Bates book on mixed effect. I'm up to point where I've created a new class using an existing variance function class, varExp as a template. Next I need to write an

Hello. I am trying my hand at modifying the varFunc class varExp, but I must be missing a step. All I want to do right now is make a working copy of varExp, call it varExp2, and then later change it. coef.varExp2, coef<-.varExp2, and Initialize.varExp2 all seem to work properly after I construct them. I can successfully use the commands: v2 <- varExp2(form = ~age|Sex,fixed =

Dear list, I was trying to create a VarClass for nlme to work with Fay-Herriot (FH) models. The idea was to create a modification of VarComb that instead of multiplying the variance functions made their sum (I called it varSum). After some fails etc... I found that the I was not getting the expected results because I needed to make sigma fixed. Trying to find how to make sigma fixed I run into

Dear lmer users, The experiment includes 15 groups of (3 males and 1 female). The female is characterized by its quality Q1 and Q2. Each male of a group is characterized by the number of MatingAttempts (with Poisson distribution). I want to examine if male mating attempts depend on female quality. I can see from graphic exploration that the within-group heterogeneity of male attempts increases

Hello, I am trying to design new variance structures by using fixed effects variables in combination with the VarPower function. That is, I would like to create and evaluate my own variance function in the data frame and then incorporate it into the model using varPower, with value=.5. As a start, I am trying to recreate the function of VarConstPower by introducing two new variables in the

Dear All, I am using the function gls (in the nlme package) and I would like to fit a heteroscedastic model, with different variances for each of the levels of two stratification variables. In p. 210 of Pinheiro & Bates ("Mixed effects models in S and S-Plus", 2000, Springer), the authors show the use of the "*" operator. However, that is not what I want, because it

Dear R users; I was trying to fit a nonlinear model using gnls (nlme version 3.1-80, R 2.5.0, WinXP) and I got the following error and warning message: Error in gnls(ht ~ a1 * hd * (1 - a2 * exp(-a3 * (dbh/dq2))), data = hdat, : Step halving factor reduced below minimum in NLS step In addition: Warning message: $ operator is deprecated for atomic vectors, returning NULL in:

Hi, I am trying to plot the original data with the line of the model using the predict function. I want to add SE to the graph, but not sure how to get them out as the predict function for gls does not appear to allow for SE=TRUE argument. Here is my code so far: f1<-formula(MaxNASC40_50~hu3+flcmax+TidalFlag) vf1Exp<-varExp(form=~hu3) B1D<-gls(f1,correlation=corGaus(form=Lat~Lon,

R-users - I must preface this question by saying that I'm a relative newbie to both R and mixed-modeling. I'm using lme fit an ANCOVA-like model. My data consist of bone length measurements for a developmental series of two capuchin monkey species. I'm interested in whether the rate of bone length scaling to body mass (i.e., growth) differs between species. My call to lme

Amigos de la erre. He creado mi primer bucle con for para entrenar unos modelos con GAM. La respuesta es quasipoisson porque estoy trabajando con densidades de peces. Sin embargo, tengo un problema, no se muy bien como añadir el offset a la formula siguiente cuando creo el bucle. GAM.A1 <-gam ((DYO)~s(DMA,k=4)+ s(WOD,k=4)+s(CIN,k=4)+s(DRA,k=4)+s(DBR,k=4)

Hello everybody, I have a dataset where each row has number of subjects and that gives me natural weights for the variance function. Additionally I see that variance increases with Age, which is a regressor. So using gls I have weights=varFixed(~1/n) but don't know how to include the extra effect of the regressor. Fitted values show a quadratic curve vs. age, not sure if that helps.

Hi All, I am making the switch to R and uncertain which of the several packages for mixed models is appropriate for my analysis. I am waiting for Pinheiro and Bates' book to arrive via inter-library loan, but it will be a week or more before it arrives. I am trying to fit a generalized linear mixed model of survival data (successes/trials) as a function of several categorical fixed and

Hello all. I was wondering if the logLike.nls() and logLike.nlme() functions are still being used. Neither function seems to be available in the most recent release of R (1.9.1). The following is contained in the help file for logLik(): "classes which already have methods for this function include: 'glm', 'lm', 'nls' and 'gls', 'lme' and others in

Amigos de la erre. He creado mi primer bucle con for para entrenar unos modelos con GAM. La respuesta es quasipoisson porque estoy trabajando con densidades de peces. Sin embargo, tengo un problema, no se muy bien como añadir el offset a la formula siguiente cuando creo el bucle. GAM.A1 <-gam ((DYO)~s(DMA,k=4)+ s(WOD,k=4)+s(CIN,k=4)+s(DRA,k=4)+s(DBR,k=4)

Hello everybody. I am trying to upgrade from R-1.9.0 to R-1.9.1 on a RedHat linux 2.4.18 system. I get the following error after "tar -xvzf R-1.9.1.tgz ; cd ./R-1.9.1/ ; ./configure" and "make" : [make works for 10 minutes ... snip ...] varExp text html latex varFixed text html latex varFunc

I measured nitrate concentration and primary production (PP) biweekly for 23 months in one headwater stream. I would like to use linear regression to determine if PP is related to nitrate concentration. My dataframe is called "data" and consists of the vectors Rdate, PP, and nitrate. Rdate is the observation date in class "date" and PP is primary production. I first