similar to: Re: [R] chisq.test freezing on certain inputs (PR#5701)

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 returns (running > 10 hours so far), the process is unresponsive to SIGINT (but I

>>>>> "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:

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

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

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) -

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

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

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) +

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

Dear 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 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, The following distribution is known as Kumaraswamy binomial Distribution. http://r.789695.n4.nabble.com/file/n4636782/kb.png For a given data I need to estimate the paramters (alpha and beta) of this distribution(Known as Kumaraswamy binomial Distribution, A Binomial Like Distribution). For that, in order to use *optim()*, I first declared the Negative Log-likelihood of this distribution as

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

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

Hello, The code here https://github.com/gsliepen/tinc/blob/master/src/graph.c#L150-L233 looks like the SSSP for indirect data forwarding is generated by looking for the minimal number of hops. Is there any possibilities or plan to generate the SSSP by using the weights of edges. And, is there any plan to add an option to allow indirect data forwards if the direct UDP channel is worse than the

>>>>> Daniel Chen >>>>> on Fri, 12 Jul 2019 13:53:21 -0500 writes: > Hi everyone: > I?m one of the interns at RStudio this summer working on a project that > helps teachers grade student code. I found an unexpected behaviour with > the |==| operator when comparing |quote|d expressions. > Example 1: > |u <-

Hi everyone: I?m one of the interns at RStudio this summer working on a project that helps teachers grade student code. I found an unexpected behaviour with the |==| operator when comparing |quote|d expressions. Example 1: |u <- quote(tidyr::gather(key = key, value = value, new_sp_m014:newrel_f65, na.rm = TRUE)) s <- quote(tidyr::gather(key = key, value = value,

https://bugzilla.samba.org/show_bug.cgi?id=5701 Summary: deadlock on local rsyncing, bisected to commit f303b749f2843433c9acd8218a4b9096d0d1bb8d Product: rsync Version: 3.1.0 Platform: All OS/Version: Linux Status: NEW Severity: major Priority: P3 Component: core AssignedTo:

Hello everyone, does anybody know what the ntlmssp flag NTLMSSP_NEGOTIATE_IDENTIFY is used for? I looked in the samba sources and only found it in .idl but there as far as I can tell there is no implementation of that. I searched for some information on the web but did not really find something useful. Before anyone asks: Microsoft's HTML5 RDP Webclient uses that flag and insists that