similar to: lme() with known level-one variances

Hi, I am running R2.8.1 under Linux, and I am having trouble using the variance functions in nlme My basic model was something like: model0 <- lme( log(growth) ~ light * species.group , data=data, random=~light|species ) # with 20 odd species divided in 2 groups Following the methods in Pinheiro&Bates I tried to put a variance function in the model: model1 <- update(model0,

When I run Rcmd check on a package on my Windows 2000 machine, I get a series of error messages like the following: * checking generic/method consistency ...c:\DOCUME~1\R5018~1.WOO\LOCALS~1\Temp/R utils138414013: cannot open c:DOCUME~1R5018~1.WOOLOCALS~1Temp/Rin138408157: no s uch file It looks as if a Windows style path to the temp directory is not being interpreted correctly, with backslashes

I'm having trouble figuring out how to create a function using "body<-" (). The help file for body() says that the argument should be a list of R expressions. However if I try that I get an error: > tmpfun <- function(a, b=2){} > body(tmpfun) <- list(expression(z <- a + b),expression(z^2)) Error in as.function.default(c(formals(f), value), envir) :

Hello, I have a simulated data structure in which students are nested within teachers, and with each student are associated two test scores. There are 20 classrooms and 25 students per classroom, for a total of 500 students and two scores per student. Here are the first 10 lines of my dataframe "d": studid tchid Y time 1 1 1 -1.0833222 0 2 1 1

When I try to open a server socket on the system setup listed below, I get the following error: > a <- make.socket(port=8091,server=TRUE) Error in make.socket(port = 8091, server = TRUE) : sockets are not available on this system I just wanted to make sure that sockets were generally available for this platform (or, perhaps, I need to upgrade to 1.2.2 on this system), before I got

I have a package that solves systems of ordinary differential equations coded as an R function (odesolve, on CRAN). The function is passed to R code, and c and Fortran code called by it uses lang4() and eval() to evaluate the R function inside a compiled c function to use in a compiled ODE solver. This works quite well, but can be slow. I'd like to be able to supply the name of a compiled

Hi, I am trying to solve a model that consists of rather stiff ODEs in R. I use the package ODEsolve (lsoda) to solve these ODEs. To speed up the integration, the jacobian is also specified. Basically, the model is a one-dimensional advection-diffusion problem, and thus the jacobian is a tridiagonal matrix. The size of this jacobian is 100*100. In the original package

I think this is a bug; at least this behavior is not documented in plot or plot.default. plot.default resets xaxp, and leaves xaxp reset when it exits: par(xaxp=c(0,1,4)) print(par("xaxp")) plot(c(0,1),c(0.2,0.3)) print(par("xaxp")) R. Woodrow Setzer, Jr. Phone: (919) 541-0128 Experimental Toxicology Division

I found that predict.gnls failed with a wierd error message about a non-numeric argument to a binary vector in one of three nearly identical uses. Error in Inh/Ki : non-numeric argument to binary operator (Inh and Ki are arguments to the function used in the formula for the object whose predictions were requested). It turns out that the problem is in getCovariateFormula(). The final line in

Does the following indicate that I have a memory leak? > gc(TRUE) Garbage collection 22891 = 21012+1557+322 (level 2) ... 483257 cons cells free (59%) 11.0 Mbytes of heap free (82%) used (Mb) gc trigger (Mb) Ncells 334906 9.0 818163 21.9 Vcells 309342 2.4 1746173 13.4 > memory.size()/1024/1024 ## in MB [1] 643.8978 > sum(sapply(ls(all.names=TRUE),object.size)) [1] 1776

I think qqline does not do exactly what it is advertised to do ("`qqline' adds a line to a normal quantile-quantile plot which passes through the first and third quartiles."). Consider the graph: tmp <- qnorm(ppoints(10)) qqnorm(tmp) qqline(tmp) The line (which I expected go through all the points), has a slightly shallower slope than does the points plotted by qqnorm. I think

If a function needs to be passed as an argument to another function, default arguments to the function being passed are lost. Consider this example: fun1 <- function(x, A=c("power","constant")) { arg <- match.arg(A) cat(paste("A is:",paste(A,collapse=", "),"\narg is:",arg,"\n")) cat("formals:\n") print(formals())

A couple of minor points about the odesolve package (which I am otherwise enjoying very much): 1. "scalar" is misspelled as "scaler" in the definitions of the rtol and atol parameters 2. it is possible to crash R by doing something dumb, e.g failing to read the documentation carefully enough and (a) returning only a vector of derivatives and not a list of (derivatives,

Probably I've just misread the documentation, but I don't understand the behavior of .Alias. Consider this (on R-1.1.1, both Windows and SGI): > tmp <- matrix(nrow=3,ncol=2) > new <- .Alias(tmp) > new[1,1] <- 1 > tmp [,1] [,2] [1,] NA NA [2,] NA NA [3,] NA NA > new [,1] [,2] [1,] 1 NA [2,] NA NA [3,] NA NA I expected tmp[1,1] to

Hello there, Suppose you want to solve the following system of ODE's (a simple Lotka-Volterra predator prey model) dP/dt = beta*P*V - mu*P dV/dt = r*V - beta*P*V where P and V are the numbers of predators and prey. Now, this is easy to do, but suppose you have a system of equations like this, dP1/dt = beta1*P1*V1 - mu1*P1 dP2/dt = beta2*P2*V2 - mu2*P2 dV1/dt = r1*V1 - beta1*P1*V1

Dear All, I'm trying to model heteroscedasticity using a multilevel model. To do so, I make use of the nlme package and the weigths-parameter. Let's say that I hypothesize that the exam score of students (normexam) is influenced by their score on a standardized LR test (standLRT). Students are of course nested in "schools". These variables are contained in the

The binary package (version of 6/17) of rw1051 for Windows is missing html documentation for dyn.load() The file is present in $R_HOME/library/base/html, but has zero bytes. dyn.load help IS accessible through the windows help system. platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status major 1 minor 5.1 year 2002 month 06 day 17 language R

Dear R-help, I am trying to set up linear mixed effects models in R using the (recommended) nlme package (R version 2.3.1 on a Linux platform). When trying to reproduce an example from Jose Pinheiro & Douglas Bates (2000, p 210) I get the following error message (code to produce message pasted as well): library("nlme") data("Orthodont") vf1Ident <- varIdent(

I am beginning a much-delayed update of odesolve to include several ordinary differential equation solvers from the Livermore package ODEPACK. These are much-used and reliable Fortran codes, and I plan (as I did for lsoda in the current odesolve package) to make as few changes as possible to the Fortran 77 code. However, recently someone wanted to make nested calls to lsoda, which will not work,

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