similar to: Problems with corARMA

hi I am trying to write a function around a glm or similar function, in which I can pass the subsetting constraint as an argument to the function, but I am having trouble. the following commands (if I wanted SEX==0 to be my subset) in the global environment work fine: subexpr <- expression(SEX==0) subtest <- with(mydata, eval(subexpr)) test.glm <- glm(y~x1+x2, data=mydata,

Hi all, this one left me a bit puzzled, as I don't seem to find a function to perform this easily. I must have overlooked the obvious, so sorry in advance. I have a list of dates in numerical format (i.e. 34576), defined as the number of days that passed since january 1st 1900. So I apply the function : > MyDate <-as.Date(34576,origin="1900-01-01") > MyDate [1]

Hi all I have made some changes to a package (SimHap) I wrote a couple of years ago, and it has passed R CMD check under windows, but under linux (ubuntu jaunty) I am getting the following error: * installing *source* package 'SimHap' ... ** R Error in parse(outFile) : 2:1: unexpected $end ERROR: unable to collate files for package 'SimHap' Does anyone know what the

Thankyou for your help with subsetting within a function. I have now tried to apply the same theory in the framework of an lme as follows: fit1.lme <- eval(substitute(lme(fixed=fixed, data=dataframe, random=random, correlation=corCAR1(form= corr), na.action=na.omit, subset=subset),list(subset=subs))) but I get the following error: Error in switch(mode(object), name = , numeric = , call =

Dear list, I using R as the statistical package for my dissertation in political sciences and I am using Sweave for documenting the work done for the creation of my dataset. However, I have a problem with Sweave (which is great, by the way) which is (hopefully) easy to solve: I want Sweave to "echo" my code, so that the R source code of the code chunks appears in the Latex

Hi I'm trying to wrap predict.lm within a function, but I'm having problems passing arguments into it in this way. Basically I want to create a lm object, then pass it into the predict.lm function and be able to tell predict.lm which variable I want to predict for, by passing the variable name as an argument of the wrapper function. This variable will always be a factor with 3 levels,

Hi folks, I am tearing my hair out on this one. I am using an example from Pinheiro and Bates. ### this works data(Orange) mod.lis <- nlsList(circumference ~ SSlogis(age, Asymp, xmid, scal), data=Orange ) ### This works mod <- nlme(circumference ~ SSlogis(age, Asymp, xmid, scal), data=Orange, fixed = Asymp + xmid + scal ~ 1, start =

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

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 :

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 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

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

I have a data analysis job for which lme may be used. Prof. Spencer Graves had helped me much on that. I'm really appreciated for that. Could anybody else in the list give me some hints from other perspectives? I hope I can learn as much as possible for this complicated real data. Thanks in advance. Hanhan To briefly describe my data: My data is health effect measurements (y) and personal

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 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

Hi, I am currently writing code to input a few thousand files, run them through the Random Forests package, and then output corresponding results. When I use the code below: zz<-textConnection("ex.lm.out", "w") sink(zz)

Hola! I am encountering the following problem, in a multilevel analysis, using glmmPQL from MASS. This occurs with bothj rw1062 and r-devel, respectively with nlme versions 3.1-38 and 3.1-39 (windows XP). > S817.mod1 <- glmmPQL( S817 ~ MIEMBROScat+S901+S902A+S923+URBRUR+REGION+ + S102+S103+S106A+S108+S110A+S109A+S202+S401+S557A+S557B+ + YHOGFcat,

Hi there, I trying to solve this problem for the whole day not going anywhere, so I really hope maybe somebody can help me in this community... I've got an object coefficient2 which I want to plot in differerent ways, with colors and labels added to the points, but somehow there seems to be a problem if a value is NA within the independent variable, resulting in false labels and false colors

Hi all, I am stuck at ploting multiple graphs on one page. I don't why it doesn't work. All the 6 plots are either exactly the same, or they simply don't plot at all. I made sure that in each iteration the "datasub" and "factorsub" are different ... Could you please help me? Thanks a lot! I did my homework and followed the following advice: