similar to: Potential clue for Bug 16975 - lme fixed sigma - inconsistent REML estimation

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

Hi, I am trying to add multiple variance structures such as the first example below: vf1 <- varComb(varIdent(form = ~1|Sex), varPower()) However my code below will not work can anybody please advise me? VFcomb<-varComb(varExp(form=~depcptwithextybf),varFixed(form=~FebNAO)) also if you have two variables with the same weights function would you write that as:

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

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

 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

Dear R users: 1. Is there a function which fits to the data the t-student distribution with parameters mu, sigma, nu. Is the function fitdistr of MASS with the syntax fitdistr(x, "t") appropriate for this? 2. Is there a function which can fit the exponential power distribution? Thanks. --------------------------------- ÁðïêôÞóôå ôçí äùñåÜí óáò@yahoo.gr [[alternative

I'm trying to get started with maximum likelihood estimation with a simple regression equivalent out of Bolker (Ecological Models and Data in R, p302). With this code: #Basic example regression library(bbmle) RegData<-data.frame(c(0.3,0.9,0.6),c(1.7,1.1,1.5)) names(RegData)<-c("x", "y") linregfun = function(a,b,sigma) { Y.pred = a+b*x

Dear List, I am trying to label a plot with the symbol +/- sigma. Using something like - expression (2*sigma) gives me the symbol 2ó. However, adding +/- to it beats me. The code I am using is: plot(x,y,type="l",main=" expression(paste("±", plain(2*ó)),sep=""). Any suggestion will be appreciated. Best Ogbos [[alternative HTML version deleted]]

Hi, I'm playing around with gamlss and don't entirely understand the sigma result from an attempted lognormal fit. In the example below, I've created lognormal data with mu=10 and sigma=2. When I try a gamlss fit, I get an estimated mu=9.947 and sigma=0.69 The mu estimate seems in the ballpark, but sigma is very low. I get similar results on repeated trials and with Normal and

Dear all &nbsp; I wish to carry out sigma- and beta-convergence analysis in respect of panel data [wherein current value of one of the variables needs be regressed upon suitably transformed lagged values of another variable(s)]. I am quite new to the R-language and am not very much aware of the availbaility of suitable package(s)/ code in the language. Can any one help me in letting me know of

Dear Sir, I have data, coming from tests, consisting of 300 values. Is there a way in R with which I can confirm this data to 68-95-99.8 rule or three-sigma rule? I need to look around percentile ranks and prediction intervals for this data. I, however, used SixSigma package and used ss.ci() function, which produced 95% confidence intervals. I still am not certain about percentile ranks

I'm proposing to add something like this to the stats package : ---------------------------------------------------------- ### "The" sigma in lm/nls - "like" models: sigma <- function(object, ...) UseMethod("sigma") ## works whenever deviance(), nobs() and coef() do fine: sigma.default <- function (object, use.fallback=TRUE, ...)

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

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)

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)

Paul, You solution worked out really well when I ran my code in R. However, when I try to turn the plot into a pdf, the unicode string no longer seems to function and instead of the sigma symbol there are just two periods (See example code below). The following is the code working in the R environment just like I want it to look: set.seed(1) Data=rnorm(100,sd=10000) plot(density(Data))

R-help I'm trying to compute the 'dist' function of a data set consisting of 16975 observations and 5 variables(2 quantitative and 3 categorical). If I call the function on a subset of the data frame everything works fine but when I reach above 3000 observations R either crash or gives the following error message. Error: cannot allocate vector of size 1125522 Kb In addition: Warning

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.

Hello all,I'm trying to add a self compiled samba 4.12 DC to a Windows 2008R2 domain.Adding the samba DC was troublesome but successful (I had to modify join.py as I swa in another thread "Join Samba to a Windows AD ERR_DS_NO_CROSSREF_FOR_NC". After that I could join the samba DC and everything seemed ok. But now, when I check the DNS server on the samba DC using the windows DNS

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