similar to: model selection in lme when corARMA is assumed

Hi, I'm a new member here in the list. I am a graduate from University of Georgia. Recently in doing analysis using lme on a dataset, I found several questions: 1. How to express the equation when the correlation structure is very complicated. For exmaple, if the fixed is y(t)=0.03x1(t)+1.5x2(t)(I omitted "hat" and others). And the model with corARMA(p=2,q=3) is proper. What will be

Trying following example from Pinheiro and Bates in order to fit an ARMA(1,1) model: library(nlme) fm1Ovary.lme<-lme(follicles~sin(2*pi*Time)+cos(*pi*Time),data=Ovary,random=p dDiag(~sin(2*pi*Time))) fm5Ovary.lme<-update(fm1Ovary.lme,corr=corARMA(p=1,q=1)) I get follwing error message: Error in "coef<-.corARMA"(`*tmp*`, value = c(62.3428455941166, 62.3428517930051 :

I am currently trying to get a "lme" analyses running to correct for the non-independence of residuals (using e.g. corAR1, corARMA) for a larger data set (>10000 obs) for an independent (lgeodisE) and dependent variable (gendis). Previous attempts using SAS failed. In addition we were told by SAS that our data set was too large to be handled by this procedure anyway (!!). SAS script

Dear Madams/Sirs, Hello. I am using the gls function to specify an arma correlation during estimation in my model. The parameter values which I am sending the corARMA function are from a previous fit using arima. I have had some success with the method, however in other cases I get the following error from gls: "All parameters must be less than 1 in absolute value". None of

Dear All: I am trying to fit a special case of a 2-banded Toeplitz correlation structure. A 2-banded Toeplitz has ones on the diagonal, a correlation, RHO1, on the first off-diagonal, and a correlation, RHO2, on the second off-diagonal, with zeros on all subsequent off-diagonals. After reading relevant sections in Mixed-Effects Models in S and S-PLUS (Pinheiro & Bates, 2000) and searching

Dear all I am tryiing to fit the following lme with an ARMA correlation structure: test <- lme(fixed=fev1f~year, random=~1|id2, data=pheno2, correlation=corARMA(value=0.2, form=~year|id2), na.action=na.omit) But I get the following error message: Error in getGroupsFormula.default(correlation, asList = TRUE) : "Form" argument must be a formula I have used this same form

R-helpers, n <- 100 arcoefs <- c(0.8) macoefs <- c(-0.6) p <- length(arcoefs) q <- length(macoefs) require(nlme) tmp <- corARMA(value=c(arcoefs,macoefs), form=~1, p=p, q=q) Sigma <- corMatrix(tmp, covariate = 1:n) # results in segfault Have I used these commands in an improper way? Thanks Ben

Full_Name: Benjamin Tyner Version: 2.6.0 RC 2007-10-01 r43043 OS: WinXP Submission from: (NULL) (171.161.224.10) platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status RC major

Hi R-sters, Just wondering what I might be doing wrong. I'm trying to fit a multiple linear regression model, and being ever mindful about the possibilities of autocorrelation in the errors (it's a time series), the errors appear to follow an AR1 process (ar(ts(glsfit$residuals)) selected order 1). So, when I go back and try to do the simultaneous regression and error fit with gls,

Hi i'm a french medical student, i have some data that i import from excel. My colomn of the datafram are the localisations of metastasis. If there is a metatsasis there is the symbol "_". i want to exclude the row without metastasis wich represent the NA data. so, i wrote this mela is the data fram mela1=ifelse(mela[,c(11:12,14:21,23,24)]=="_",1,0) # selection of the

Hi there fellow R-users, I am trying to follow an example of modelling a serial correlation structure in the textbook "Mixed Effects Model in S and Splus". However, I am getting some very odd results. Here is what I am trying to run: library(nlme) data(Ovary) fm1<-lme(follicles~sin(2*pi*Time)+cos(2*pi*Time),data=Ovary,random=pdDiag(~s in(2*pi*Time))) ### The example is fine up

Dear helpers, I tried these models to run in the package nlme, but allways got the same error message... I have a correlation in 5 sessions within a field (n=12) with ten traps in one field. res2a <- lme(response~x+y+z+treatment),correlation = corARMA(form = ~ session|trapfield, p = 1, q = 0), random=~1|field, na.action=na.omit, data=plates, method="ML") res2a <-

I've installed new fifa and written in the code of the terminal had opened up to play EA Sports intro then comb a new error message in there Standt: "In the program were difficult manager11.exe gent fault and it must be-beeendet We apologize for this unnanehmlichkeiten. The cause may be a problem in the program or may fail to run in wine sein.sie www.appdb.winehq.org tips under the

Dear all, I have a character string object: > chara [1] "The name of first slot" and a list object: > class( try1) [1] "list" what I want to do is to use the chara as a slot's name of "try1". Of course I could do it like: > try1$"The name of first slot" <- matrix("", 3, 4) to create a slot of 3x4 matrix with the name

Thanks. Hmm. The loop is doing what it is supposed to do. > try1<-function(joint12=FALSE,marg1=FALSE,marg2=FALSE, +??????????????? cond12=FALSE,cond21=FALSE){ + # *************************************************** + # Testing if loop + # *************************************************** + if(joint12){ +?? {print ("joint12"); cat(joint12,"\n")} +?? {print

Let me modify my question about user-defined covariance structures for LME models: Can somebody tell me how I can see the code for the definition of the correlation structures that come with the NLME package. Specifically I like to see the code for the functions coef, corMatrix, and intialize for any of the pre-defined correlation structures, and use this as a template to define a new correlation

salutations! i am doing some longitudinal modeling with sem and thought calculating some "simple variables" would make my model more readable. this is the smallest subset of my model that illustrates the resulting problem. i have 2 observed exogenous variables (c1, d2) and 4 observed endogenous variables (dc1, dd1, dc2, dd2). c1 is the observed state at time 1, dc1 is the change in c

OK. The fact it's in a function is making things clearer. Are you trying to update the values of an object from within the function, and have them available outside the function. I don't speak functional programming articulately enough but basically v <- 1 funA <- function() { v <- v+1 } funA() cat (v) # 1 You either return the v from the function so funB <- function() {

Hello > orderulcount Group.1 Group.2 Group.3 x V5 7 C L 0.0 30 C / L 19 C L 0.2 27 C / L 31 C L 0.4 15 C / L 43 C L 0.6 7 C / L 54 C L 0.8 2 C / L 10 C S 0.0 27 C / S 22 C S 0.2 10 C / S 34 C S 0.4 6 C / S 46 C S 0.6 1 C / S 1 D

On 06/01/16 17:36, Andreas Maier wrote: > Hi, > I have started using symbolic links on an SMB share and find that > symbolic links whose target no longer exists cannot be removed on the > client side. > > Example, on the SMB client side in an SMB-mounted directory: > > 1. Create a file and a relative symlink to it: > > $ touch a > $ ln -s a b > $