similar to: How to extract parameter estimates of variance function from lme fit

I have been using gnls with the weights argument (and varConstPower) to specify a variance structure for curve fits. In attempting to extract the parameters for the variance model I am seeing results I don't understand. When I simply display the model (or use "summary" on the model), I get what seem like reasonable values for both "power" and "const". When I

R 1.6.2 for Windows, Win2k: I have fitted a weighted least squares model using the code "wls.out <- gls(y ~ x1 + x2 + x3 + x4 + x5 + x6 - 1, data = foo.frame, weights = varConstPower(form = ~ fitted(.), fixed = list(power = 0.5), const = 1))" The data has 62 rows and the response is zero when the covariates are zero. The purpose of the model was to account for the the fact that

Dear Thomas Lumley, and R-help list members, I have read your article "Network meta-analysis for indirect treatment comparisons" (Statist Med, 2002) with great interest. I found it very helpful that you included the R code to replicate your analysis; however, I have had a problem replicating your example and wondered if you are able to give me a hint. When I use the code from the

Works perfectly. Thank you. -Hugh Rand -----Original Message----- From: Spencer Graves [mailto:spencer.graves at pdf.com] Sent: Sunday, January 15, 2006 6:41 PM To: Rand, Hugh Cc: 'r-help at lists.R-project.org' Subject: Re: [R] trouble with extraction/interpretation of variance structure para meters from a model built using gnls and varConstPower How about this: >

Hello, Excuse me for posting two questions in one day, but I figured it would be better to ask my questions in separate emails. I will again give the caveat that I'm not a statistician by training, but have a fairly decent understanding of probability and likelihood. As before, I'm trying to fit a nonlinear model to a dataset which has two main factors using nlme. Within the dataset

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

I have files many SAMBA file shares on a unix bot and clients are connecting to those file shares. 1. Problem: I can use explorer to view,browse and access files in those file shares without any problems except files on the top level which I can not double click to open them. Any lower level files are no problem. 2. When I use excel or word (Notepad, wordpad and others have no problem) and

I am having trouble fitting correlation structures within nlme. I would like to fit corCAR1, corGaus and corExp correlation structures to my data. I either get the error "step halving reduced below minimum in pnls step" or alternatively R crashes. My dataset is similar to the CO2 example in the nlme package. The one major difference is that in my case the 'conc' steps are

Dear R-experts, I need to replace in an expression the character "Cl" by "Cl+beta" But in the following case: form<-expression((Cl-(V *ka) ) +(V *Vm *exp(-(Clm/Vm) *t))) gsub("Cl","(Cl+beta)",as.character(form)) We obtain: [1] "((Cl+beta) - (V * ka)) + (V * Vm * exp(-((Cl+beta)m/Vm) * t))" the character "Clm" has been

Dear R-users, Do you know if we can use the function lme in R for log-normal distribution of parameters as used in Nonmem ? theta=theta0*exp(eta) In our model, the parameters follow the log-normal distribution so it's not reasonable to deal with normal distribution which gives us negative values in simulation Thanks for your help, Thu [[alternative HTML version deleted]]

Good day R-Users, I have a problem accessing some values in the output from the summary of an lme fit. The structure of my data is as shown below (I have attached a copy of the full data). id trials endp Z.sas ST 1 1 -1 -1 42.42884 1 1 1 -1 48.12007 2 1 -1 -1 43.42878 2 1 1 -1

Dear R-Users I have a problem accessing some values in the output from the summary of an lme fit. I fit the model below: ggg <- lme (ST~ -1 + as.factor(endp):Z.sas + as.factor(endp), data=dat4a, random=~-1 + as.factor(endp) + as.factor(endp):Z.sas|as.factor(trials), correlation = corSymm(form=~1|as.factor(trials)/as.factor(id)), weights=varIdent(form=~1|endp)) hh

Hi all, I understand that gls() uses generalized least squares, but I thought that maybe optimum weights from gls might be used as weights in lm (as shown below), but apparently this is not the case. See: library(nlme) f1 <- gls(Petal.Width ~ Species / Petal.Length, data = iris, weights = varIdent(form = ~ 1 | Species)) aa <- attributes(summary(f1)$modelStruct$varStruct)$weights f2 <-

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

Hi, I am not sure this is a bug but I can repeat it, The functions and data are below. I know this is nasty data, and it is very questionable whether a 4pl model is appropriate, but it is data fed to an automated tool and I would have hoped for an error. Does this repeat for anyone else? My details: > version _ platform i686-pc-linux-gnu

Hi, Does anybody know if there is a way for a call goes back to transferer if unanswered ? Thanks Luis A P Barbosa -------------- next part -------------- An HTML attachment was scrubbed... URL: http://lists.digium.com/pipermail/asterisk-users/attachments/20070912/1e356013/attachment.htm

Hello,   I am attempting to use nlme to model the response of 19 groups.  I am able to get a reasonable fit of all of the groups to the observed data using an exponential decay model (a*exp-x*b).  The problem is that when I plot the fitted values to residuals, it demonstrates a pattern of increasing variance.   I attempt to model this variance using   Sig3.nlme <- update(Sig2.nlme, weights =

Hi everybody, I'm interested in evaluating the effect of a continuous variable on the mean and/or the variance of my response variable. I have built functions expliciting these and used the 'mle2' function to estimate the coefficients, as follows: func.1 <- function(m=62.9, c0=8.84, c1=-1.6) { s <- c0+c1*(x) -sum(dnorm(y, mean=m, sd=s,log=T)) } m1 <- mle2(func.1,

Hi! I try to explain the efffect of (1) forest where i took samples's soils (* Lugar*: categorical variable with three levels), (2) nitrogen addition treatments (*Tra*: categorical variable with two levels) on total carbon concentration's soil samples (*C: *continue* *variable) during four months of sampling (*Time:* categorical and ordered variable with four levels). I fitted the

  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