similar to: (no subject) -- rename to optim() crash due to NA returned

Dear R users I have a data frame that looks like this: m j X1 X2 1 1 1 2 1 ... 1 J 2 1 2 2 2 ... 2 J . . . M 1 M 2 M ... M J The data frame essentially looks like a panel: m and j are indicators where m is 1:M and j is 1:J (and M > J); X1 and X2 are variables. I

Dear R users I have the following problem when calling optim() to minimize a function "f.obj" (= outer loop) that calls another function "f.con" (a contraction mapping, = inner loop). It seems to me that it is a numerical problem that I currently fail to take into account when coding. Calling optim(), for the first few iterations of the outer loop, everything seems fine; the

To Whom It May Concern: I have an R package and want to put this package be part of R-project and available to anyone who is interested in. The R package is created for my paper, titled "Acceptance Sampling Plans from Truncated Life Tests Based on the Birnbaum-Saunders Distribution for Percentiles". The paper has been accepted by Communications in Statistics: Simulation and

Hello, I am interested in fitting a generalized nonlinear regression (gnlr) model with negative binomial errors. I have found Jim Lindsay's package that will do gnlr, but I have having trouble with the particular model I am interested in fitting. It is a threshhold model, where below a certain value of one of the parameters being fitted, the model changes. Here is a sample: Cones:

Rembert.DeBlander@econ.kuleuven.ac.be wrote: >>version > PLEASE: a) Use a sensible subject line b) Please post only post bug reports if you are sure it is a bug (and here it is not a bug!) c) Check the recent R version (1.9.1) if posting bugs, not an outdated one! d) Only named arguments are passed through the ... argument: integrate(dnorm, lower=-Inf, upper=3, mean=-1, sd=7) Uwe

> version _ platform i686-pc-linux-gnu arch i686 os linux-gnu system i686, linux-gnu status major 1 minor 7.1 year 2003 month 06 day 16 language R Bug: integrate(f,lower,upper,extra_args) where f <- function(x,extra_args) { body } integrate doesn't pass the extra arguments when calling f. As a first check of this finding I integrated dnorm from

Hi, I'm having a problem converting a Matlab program into R. The R code works almost all the time, but about 4% of the time R's optim function gets stuck on a local minimum whereas matlab's fminsearch function does not (or at least fminsearch finds a better minimum than optim). My understanding is that both functions default to Nelder-Mead optimization, but what's different about

At the APL conference in Berlin on July 24 I am giving a talk about about a molecule-like notation for arrays for which some prototype code is available in R. It is a graphical notation for arrays of higher rank which makes the structure of arrays and their various concatenations intuitively apparent, and which, in my judgment, would make an excellent interface for array programming languages. I

I am trying to use the R API to call optim functions (nmmin, vmmin, lbfgsb, etc.) through a C program but I couldn't find the shared library to link under the R-2.6.0 build which is compiled under Linux (REL5). main.cpp:35: undefined reference to `Rf_initEmbeddedR(int, char**)' main.cpp:41: undefined reference to `nmmin' Thanks in advance for any help. ------------------------

Is there any real advantage to using 64 bit when I am right at the 4gb ram threshhold? Nice plans to add more ram. The machine will just be a backup machie (rsync). Thanks in advance. D

How to convert the following ms() in Splus to Optim in R? The "Calc" function is also attached. ms(~ Calc(a.init, B, v, off, d, P.a, lambda.a, P.y, lambda.y, 10^(-8), FALSE, 20, TRUE)$Bic, start = list(lambda.a = 0.5, lambda.y = 240), control = list(maxiter = 10, tol = 0.1)) Calc <- function(A.INIT., X., V., OFF., D., P1., LAMBDA1., P2., LAMBDA2., TOL., MONITOR.,

Hi everyone. I have a problem that I have been unable to determine either the best way to proceed and why the methods I'm trying to use sometimes fail. I'm using the pf() function in an optimization function to find a noncentrality parameter that leads to a specific value at a specified quantile. My goal is to have a general function that returns the noncentrality parameter that

Hello, what are they meaning? It could be something that would show a threshhold above which the result is indicating different meanings then just random noise. But there is no description on the definition of those lines, so it means nothing, if it is not clearly defined. Where can I find a detailed definiton? Ciao, Oliver

I've implemented a backups system and have come across a problem with delete-during and I/O errors. Currently I use a wrapper round rsync to create a LVM snapshot and rsync the snapshot, this works except that when the snapshot threshhold is exceeded LVM removes the snapshop, the mount fails and I/O errors happen. This is ok, except with delete-during I'm getting instances of rsync

Hi all, I've been working on improving R's optim() command, which does general purpose unconstrained optimization. Obviously, this is important for many statistics computations, such as maximum likelihood, method of moments, etc. I have focused my efforts of the BFGS method, mainly because it best matches my current projects. Here's a quick summary of what I've done: *

Your function is giving NaN's during the optimization. The R-forge version of optimx() has functionality specifically intended to deal with this. NOTE: the CRAN version does not, and the R-forge version still has some glitches! However, I easily ran the code you supplied by changing optim to optimx in the penultimate line. Here's the final output. KKT condition testing Number of

Hello, I am having trouble using "optim". I want to maximalise a function to its parameters [kind of like: univariate maximum likelihood estimation, but i wrote the likelihood function myself because of data issues ] When I try to optimize a function for only one parameter there is no problem: llik.expo<-function(x,lam){(length(x)*log(lam))-(length(x)*log(1-exp(-1*lam*

Hello, I have a very unusual situation with an SVM and wanted to get the group's opinion. We developed an experiment where we train the SVM with one set of data (train data) and then test with a completely independent set of data (test data). The results were VERY good. I found and error in how we generate one of or training variables. We discovered that it was indirectly influenced

Hi, Why, when I run the script below, is my y-axis range command being ignored? I.e., the y axis graphed consistently fits the line specified in the plot command, but never fits the line I'm trying to add in the subsequent line command. This is my first R script, so if I'm doing anything else wacky that jumps out, please let me know. I'm an advanced Stata user, but R is new to me.

On Jun 11, 2008, at 6:27 AM, Florian Brandner wrote: > On Thursday 08 May 2008 18:33:48 Adrian Prantl wrote: >> we noticed that llvmgcc4.2-2.2 sometimes generates non-natural loops >> when compiling to bytecode without any optimizations. Apparently what >> happens is that the loop header is duplicated, which results in two >> entry points for the loop. > > this is