similar to: chisq.test freezing on certain inputs

On Thu, 11 Dec 2003, Jeffrey Chang wrote: > Hello everybody, > > I'm running R 1.8.1 on both Linux and OS X compiled with gcc 3.2.2 and > 3.3, respectively. The following call seems to freeze the interpreter > on both systems: > > chisq.test(matrix(c(233, 580104, 3776, 5786104), 2, 2), > simulate.p.value=TRUE) > > By freeze, I mean, the function call never

>>>>> "Torsten" == Torsten Hothorn <torsten@hothorn.de> >>>>> on Thu, 11 Dec 2003 18:03:07 +0100 (CET) writes: Torsten> On Thu, 11 Dec 2003, Jeffrey Chang wrote: >> Hello everybody, >> >> I'm running R 1.8.1 on both Linux and OS X compiled with >> gcc 3.2.2 and 3.3, respectively. The following

>>>>> "MM" == Martin Maechler <maechler@stat.math.ethz.ch> >>>>> on Thu, 11 Dec 2003 18:29:05 +0100 (CET) writes: >>>>> "Torsten" == Torsten Hothorn <torsten@hothorn.de> >>>>> on Thu, 11 Dec 2003 18:03:07 +0100 (CET) writes: Torsten> On Thu, 11 Dec 2003, Jeffrey Chang wrote:

Hello, I am trying to use nlm to estimate the parameters that minimize the following function: Predict<-function(M,c,z){ + v = c*M^z + return(v) + } M is a variable and c and z are parameters to be estimated. I then write the negative loglikelihood function assuming normal errors: nll<-function(M,V,c,z,s){ n<-length(Mean) logl<- -.5*n*log(2*pi) -.5*n*log(s) -

Dear R experts, I have been encountering problems with the "optim" routine using "for" loops. I am determining the optimal parameters of several nested models by minimizing the negative Log-Likelihood (NLL) of a dataset. The aim is to find the model which best describes the data. To this end, I am simulating artificial data sets based on the model with the least number

Dear all, I am trying to evaluate the optimisation behaviour of a function. Originally I have optimised a model with real data and got a set of parameters. Now I am creating simulated data sets based on these estimates. With these simulations I am estimating the parameters again to see how variable the estimation is. To this end I have written a loop which should generate a new simulated data

Hi all, I am trying to find estimates for 7 parameters of a model which should fit real data. I have a function for the negative log likelihood (NLL) of the data. With optim(method="L-BFGS-B",lower=0) I am now minimizing the NLL to find the best fitting parameters. My problem is that the algorithm does not converge for certain data sets. I have read that one should scale the fn

Hi everyone! I am using the mle {stats4} to estimate the parameters of distributions by MLE method. I have a problem with the examples they provided with the mle{stats4} html files. Please check the example and my question below! *Here is the mle html help file * http://stat.ethz.ch/R-manual/R-devel/library/stats4/html/mle.html http://stat.ethz.ch/R-manual/R-devel/library/stats4/html/mle.html

for learning purposes and also to help someone, i used roger peng's document to get the mle's of the gamma where the gamma is defined as f(y_i) = (1/gammafunction(shape)) * (scale^shape) * (y_i^(shape-1)) * exp(-scale*y_i) ( i'm defining the scale as lambda rather than 1/lambda. various books define it differently ). i found the likelihood to be n*shape*log(scale) +

I am using the Ben bolker's R package "bbmle" to estimate the parameters of a binomial mixture distribution via Maximum Likelihood Method. For some data sets, I got the following warning messages: *Warning: optimization did not converge (code 1: ) There were 50 or more warnings (use warnings() to see the first 50)* Also, warnings() results the following: *In 0:(n - x) : numerical

Hello, I have a log likelihood function that I was able to optimize using mle2. I have two years of the data used to fit the function and I would like to fit both years simultaneously to test if the model parameter estimates differ between years, using likelihood ratio tests and AIC. Can anyone give advice on how to do this? My likelihood functions are long so I'll use the tadpole

Hello R Help, I am trying solve an MLE convergence problem: I would like to estimate four parameters, p1, p2, mu1, mu2, which relate to the probabilities, P1, P2, P3, of a multinomial (trinomial) distribution. I am using the mle2() function and feeding it a time series dataset composed of four columns: time point, number of successes in category 1, number of successes in category 2, and

Dear all, I am trying to compile R version 1.0.1 under Solaris on a SUNsparcUltra10. Note that I'm doing this in my home directory as I cannot do it as root. The configure script seems to run correctly and issues as the last few lines: ----------------------------------------------- ... R is now configured for sparc-sun-solaris2.7 Source directory: . Installation directory:

Dear R developers, I noticed a bug in the stats4 package, specifically in the confint method applied to ?mle? objects. In particular, when some ?fixed? parameters define the log likelihood, these parameters are stored within the mle object but they are not used by the ?confint" method, which retrieves their value from the global environment (whenever they still exist). Sample code: >

Hi Can anyone please suggest me a package where I can estimate a non-linear regression model? One of the independent variables is latent or unobserved. I have an indicator variable for this unobserved variable; however the relationship is known to be non-linear also. In terms of equations my problem is y=f(latent, fixed) q=g(latent) where q is the indicator variable For me both f and g are

Hi, I'm trying to compile R-1.7.1 from source (on a RedHat 8.0) instead of using the binary version, as it has often been advised. However I don't manage to find a solution to the following error which occurs during the make procedure : /!\-------------------------------------------/!\ building package 'ctest' mkdir -p -- ../../../library/ctest/R mkdir -p --

For the longest time PartialRenderer#partial_path has prefixed the prefix of the current controller when it is nested in a module. This hasn''t been a problem (because nesting controllers wasn''t that common) but with 3.1 striving for better engine support, this problem is now larger because all of your controllers for an engine will be nested and it makes doing <%= render

Hi, I've been trying to install R on Solaris, I've been following the instruction for configuring & compiling R (I have gcc and f77 installed)- but I get Error messages. I'd appreciate it if you could look at the output, (pasted below) and give me some advice on what to do. I've attached the R install 'readme'. Thanks, a quick reply would be greatly appreciated,

I have determined why there are many "WARNING: Duplicate symbol:" messages. *** My apologies for the length *** There is a lot of detail - but I hope the detail will help R - and others - setup correct options for shared libraries. *** As I press send, I have not stopped testing (my final trial here might not even work) - but! *** the message is that shared libraries do not need to have

The changelog action needs to checkout git2cl as a submodule. For some reason, when called through the Git module, command('submodule', 'update') was doing something unfathomable, and different to just calling 'git submodule update'. As Git is just a command line wrapper anyway, I've sidestepped this by just calling the command directly. --- Build.PL | 18