similar to: [nls] singular gradient

Hi, I am a student of Earthquake Engineering, and am new to R. Currently I try to run nonlinear regression analysis by R. My data has three variables: X, Y, and Z. Z is a function of (X, Y). My R script is as below. rm(list=ls()) # read in data Alldata <- read.table("~/Documents/R/Wu_data.dat", header=TRUE) # assign variables Z <- Wu[[1]] # N1,60 X <- Wu[[2]]

Hola de nuevo, Esta es la información de mi sesion: R version 2.10.1 (2009-12-14) i386-pc-mingw32 locale: [1] LC_COLLATE=Spanish_Spain.1252 LC_CTYPE=Spanish_Spain.1252 [3] LC_MONETARY=Spanish_Spain.1252 LC_NUMERIC=C [5] LC_TIME=Spanish_Spain.1252 attached base packages: [1] stats graphics grDevices utils datasets methods base Lo que yo prentendo es

Here's the latest batch of words to get shipped out to Allison Smith. Please submit reasonably small changes to me by tomorrow 10:00 AM Eastern time, and I'll add them. As usual, donations to what will be a ~$110 USD expense would be appreciated, as I am paying for this round out of my pocket. Please send to paypal address "jtodd@loligo.com". I did not include all

Hi all, I wonder if it is somehow possible to execture or redirect to a controller function from RJS? Right now I do: def foo() render :partial => ''executeagain'' end _executeagain.rhtml <script> new Ajax.Updater(''elmntID'', ''/test/foo/'', {evalScripts:true}); </script> This will loop I know :) How can I achieve the same

The coxme package has a ranef() method, as does lme4. I'm having trouble getting them to play together, as shown below. (The particular model in the example isn't defensible, but uses a standard data set.) The problem is that most of the time only one of lme4 or coxme will be loaded, so each needs to define the basic ranef function as well as a method for it. But when loaded together

Using ranef() (package nlme, version 3.1-75) with an 'lme' object I can obtain random effects for intercept and slope of a certain level (say: 1) - this corresponds to (say level 1) "residuals" in MLWin. Maybe I'm mistaken here, but the results are identical. However, if I try to get the standardized random effects adding the paramter "standard=T" to the

Hi, I have a file that looks like this : one,0 two,0.591,0 three,0.356,0.350,0 four,-0.098,0.072,0.380,0 five,0.573,0.408,0.382,0.062,0 six,0.156,0.232,0.517,0.424,0.303,0 seven,0.400,0.414,0.611,0.320,0.401,0.479,0 eight,0.282,0.375,0.512,0.346,0.308,0.463,0.605,0 nine,0.519,0.484,0.467,0.167,0.455,0.311,0.574,0.557,0 I want to create a data matrix out of it, so I tried this :

I'm testing out a new version of coxme and R CMD check fails with "could not find function ranef" (or random.effects or fixef, or anything from nlme). The NAMESPACE file has the line below importFrom(nlme, ranef, random.effects, fixef, fixed.effects, VarCorr) and nlme is declared in the DESCRIPTION file as an import. I feel that I must be staring at some obvious (but

I'm trying to use the lmeSplines package together with lme4. Below is (1) an example of lmeSplines together with nlme (2) an attempt to use lmeSplines with lme4 (3) then a comparison of the random effects from the two different methods. (1) require(lmeSplines) data(smSplineEx1) dat <- smSplineEx1 dat.lo <- loess(y~time, data=dat) plot(dat.lo) dat$all <- rep(1,nrow(dat)) times20

User of the coxme library (mixed effects Cox models) are instructed to use ranef(), fixed(), VarCorr(), etc to retrieve bits out of a fitted model; it purposely uses the same methods as nlme and/or lmer. The current behavior is to "depend" on nlme. If I defined the methods myself in coxme, then someone who had both nlme and coxme loaded will suffer from "last loaded wins",

library(nlme) data(Phenobarb) na.include <- function(x)x phe1 <- nlme(conc~phenoModel(Subject, time, dose, lCl, lV), data = Phenobarb, fixed = lCl+lV~1, random= pdDiag(lCl+lV~1), start = c(-5,0), na.action = na.include, naPattern = ~!is.na(conc)) phe.ranef <- ranef(phe1,augFrame=TRUE) plot(phe.ranef, form=lCl~Wt+ApgarInd) [Error in max(length(x0),

I have been struggling all day to import a particular function/method combination (ranef(), which extracts the random effects from a mixed model fit) from the nlme package into another package ... so far without success. The NAMESPACE for nlme contains the following lines: export(..., ranef, ...) S3method(ranef, lme) ranef is defined as a standard S3 generic, function (object, ...)

I am fitting models to the responses to a questionnaire that has seven yes/no questions (Item). For each combination of Subject and Item, the variable Response is coded as 0 or 1. I want to include random effects for both Subject and Item. While I understand that the datasets are fairly small, and there are a lot of invariant subjects, I do not understand something that is happening

Dear List: I am having difficulties with the fitted values at different levels of a multilevel model. My data set is a series of student test scores over time with a total of 7,280 observations, 1,720 students nested witin 60 schools. The data set is not balanced. The model was fit using eg.model.1<-lme(math~year, random=~year|schoolid/childid, data=single). When I call the random

So, per the discussion last week and generous donations, we have some new sound files with which to work. The sounds are located in: http://www.loligo.com/asterisk/sounds/ For those of you who just want to download the _new_ sounds, please fetch: http://www.loligo.com/asterisk/sounds/20040117.newsounds.tar All of the sounds in that tarball are also in the main ../sounds/ directory in

R múltiple Estoy pensando en un problema que tendré que solucionar pero aún no comencé a escribirlo, por lo tanto no hay código en R como para compartir, sin embargo no tengo idea de cómo realizarlo desde R. El planteo es el siguiente: Los datos son en una cantidad necesaria para que el procesamiento estadístico demore (minutos, horas). Supongamos dos variables (serían más), la A y la B,

I have a model: mod1<-lmer( x ~ (1|rtr)+ trth/(1|cs) , data=dtf) # Here, cs and rtr are crossed random effects. cs 1-5 are of type TRUE, cs 6-10 are of type FALSE, so cs is nested in trth, which is fixed. So for cs I should get a fit for 1-5 and 6-10. This appears to be the case from the random effects: > mean( ranef(mod1)$cs[[1]][1:5] ) [1] -2.498002e-16 > var(

Hello, I would like to read and write sparse matrices using the functions write.matrix.csr() and read.matrix.csr() of the package e1071. Writing is OK but reading back the matrix fails: x <- rnorm(100) m <- matrix(x, 10) m[m < 0.5] <- 0 m.csr <- as.matrix.csr(m) write.matrix.csr(m, "sparse.dat") read.matrix("sparse.dat") Error in initialize(value, ...)

Hi all! How is it possible to estimate standard errors for coef obtained from lme? Is there sth like se.coef() for lmer or what is the anaytical solution? Thank you!

I'm working on lldb. I've just submitted a very small change (r217229) to Triple.h/.cpp. Soon after I get a mail subject: buildbot failure in LLVM on lld-x86_64-darwin13 Details: http://lab.llvm.org:8011/builders/lld-x86_64-darwin13/builds/2571 Blamelist: mg11 My small change certainly did not cause lldb's build to fail on my machine. I looked into the build-log: