similar to: problems with loop

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

Hi, I'm trying to find the maximum (likelihood) of a function. Therefore, I'm trying to minimize the negative likelihood function: # params: vector containing values of mu and sigma # params[1] - mu, params[2]- sigma # dat: matrix of data pairs y_i and s_i # dat[,1] - column of y_i , dat[,2] column of s_i negll <- function(params,dat,constant=0) { for(i in 1:length(dat[,1])) {

Hi, I am using the NLSY79 data (longitudinal data from the Bureau of labour stats in the US). The extractor exctracts this data in a "wide" format and I need to reshape it into a long format. What I am doing right now is to do it in chuncks for each and evry variable that is varying and then I merge the data together. This is taking a long time. my question is: How do I specify that

Hi, I am using the sim1000G R package to simulate data for case/control study. I can not figure out how to manipulate this code to be able to generate 10% or 50% causal SNPs in R. This is whole code provided as example on GitHub: library(sim1000G) vcf_file = "region-chr4-357-ANK2.vcf.gz" #nvariants = 442, ss=1000 vcf = readVCF( vcf_file, maxNumberOfVariants = 442 ,min_maf =

Greetings listeRs - Given a data frame such as times time1 time2 time3 time4 1 70.408543 48.92378 7.399605 95.93050 2 17.231940 27.48530 82.962916 10.20619 3 20.279220 10.33575 66.209290 30.71846 4 NA 53.31993 12.398237 35.65782 5 9.295965 NA 48.929201 NA 6 63.966518 42.16304 1.777342 NA one can use "transform" to

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

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

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 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

Say you have a POSIX object that is in UTC. How do you change the values to another timezone? If I do this: times <- strptime(times, "%H:%M:%S") times1 <- as.POSIXct(times, tz="UTC") times2 <- as.POSIXct(times, tz="CDT6CST") times1 id UTC, but times2 is still UTC, not CTD. Why? Is the only was to change time zones to add seconds to POSIX objects?

Hi Berina, I'm not an expert on genetics. I haven't looked at the package. And I've only glanced at your question. So, this is probably not the best response. But as no one else has responded, here's some comments: (1) Have you checked if there's a function in the package to do what you want? The remainder of these questions assume that you have, and the answer is no. (2)

In my orgainzation, the people resonsible for the network are not that keen on setting up new software, so when I asked them to set up emacs or some other common R editor, I was told to have a look at ConText. This editor is avaliable in the network, and there is some R support. Special commands are highlighted and such, but the most important part, sending commands writtten in a ConText window

On Sat, 2024-08-03 at 21:33 +0300, Michael Tokarev wrote: > 31.07.2024 08:30, Douglas Bagnall via samba ?????: > > On 30/07/24 22:20, Michael Tokarev via samba wrote: > > > When building libldb as public library, its install target does not > > > install ldb_version.h header file, which is included from ldb.h, so > > > the resulting header files are unusable.

Hello: Ed Zaleski ran some remarkable and very impressive load tests on icecast reported on www.icecast.org (Home page). What wasn't mentioned in the test specifications was the type of internet line that was used which totally influences bandwidth and subesequent overall load characteristics. Questions: 1. Was it a T1 line, Verizon FIOS, or cable internet, or what? 2. What were the