similar to: Question about mle function

Following the recommendation of Prof. Ripley, I have created the Makevars file with the line: PKG_LIBS="-L/usr/lib/libm -lm -L/usr/local/lib/libgsl -lgsl -L/usr/local/lib /libgslcblas -lgslcblas" in the working directory. Now I have the code file Example3.c which computes the Bessel function value (the example is taken from the GSL reference book). I am running: R CMD SHLIB Example3.c

Dear all, I think that my question is very simple but I failed to solve it. I have a list which elements are matrices like this: >mylist [[1]] [,1] [,2] [,3] [1,] 1 3 5 [2,] 2 4 6 [[2]] [,1] [,2] [,3] [1,] 7 9 11 [2,] 8 10 12 I'd like to create a matrix M<-mylist[[1]]+mylist[[2]] [,1] [,2] [,3] [1,] 8 12 16 [2,] 10 14 18

Dear experts! I have a minimization problem with non-linear constraint and Objective function(theta)=lambda*(Constr)^2-f(x,theta). Theta is a vector of parameters. I'd like to stop the optimization after the value of the constraint is less or equal some constant value, say d, and save the last computed value of the function. For this purpose, I thought to define the Objective function like

Dear all, I'd like to find a minimum of (-loglik) function which is a function of k parameters. I'd like to run the minimization algorithm for the different subsets of the parameters and assign the fixed values to the complementary subset. How should I define my (-loglik) function such that it can be passed to the optim or other optimization function? Much thanks for any suggestions.

What is 1. par.ests <- optimfit$par 2. fisher <- hessb(negloglik, par.ests, maxvalue=maxima); 3. varcov <- solve(fisher); 4. par.ses <- sqrt(diag(varcov)); Thanks a lot, fit.GEV <- function(maxima) { sigma0 <- sqrt((6. * var(maxima))/pi) mu0 <- mean(maxima) - 0.57722 * sigma0 xi0 <- 0.1 theta <- c(xi0, mu0, sigma0) #10/5/2007: removed assign() for maxima.nl

Dear Specialists in R, May be somebody has experiment in using pakage for the book Quantitative Risk Management by McNeil? This package is writen in R. I have run this package for fitting the data to Nornal Inverse Gaussian distribution and fased with following problem. > Return<-read.csv("data.csv") > Transpose<-t(Return) > fit.NH(Transpose, case="NIG",

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'm getting unexpected results from the coxph function when using weights from counter-matching. For example, the following code produces a parameter estimate of -1.59 where I expect 0.63: d2 = structure(list(x = c(1, 0, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 1, 0, 0, 1, 0, 1, 0, 1, 0, 1), wt = c(5, 42, 40, 4, 43, 4, 42, 4, 44, 5, 38, 4, 39, 4, 4, 37, 40, 4, 44, 5, 45, 5, 44, 5), riskset =

Dear experts! Is there a package that enables to create the bivariate log-normal variables? Thanks a lot, Vicky Landsman. [[alternative HTML version deleted]]

Dear RUsers, I am new to R. I am learning how to use R. I am a PC user and run R on windows. I would appreciate if some one could guide me on a few questions I have: 1) I have 4 cel files (2 replicates for NORM and Disease resp). I have been able to run siggenes on this dataset where I have 4 labels in the class file groupsnhi.cl op-> (0,0,1,1) and my data has been read into datrmanhi after

Full_Name: Rod Montgomery Version: 1.1.0 OS: Windows-95 Submission from: (NULL) (38.26.56.3) File R-1.1.0/src/appl/lbfgsb.c -- Comment in code says two papers describing underlying math are in ftp://ece.nwu.edu/pub/lbfgs/lbfgs_bcm/ but that directory seems not to exist. (Actually, the comment does not give a URL - it just says to look in that directory on that FTP server.) Paper [1] does

Dear R-experts, I am running a large simulation exercise where the enough complicated integration is required. The integral is computed within a C-function called Denom by use of function qags from the gsl library. Here is a piece of R-code: denom<-try(.C("Denom",as.double(x),as.integer(n), as.integer(p), as.double(param),

Couldn't you do this by subtracting 0.5 + x from your y values and checking for normality with mean 0 and sd = 1 (using ks.test or another test of normality). If you fail, you'll have to do additional work to find out whether pairs with some particular x value (or range of x values) is causing the problem, but I think this fits the question as stated. Of course, if you have discrete x

Hello everyone, Anybody had the chance to test out this setup and reproduce the problem? I assumed it would be something that's used often these days and a solution would benefit a lot of users. If can be of any assistance please contact me. -- Met vriendelijke groet, Richard Landsman http://rimote.nl T: +31 (0)50 - 763 04 07 (ma-vr 9:00 tot 18:00) 24/7 bij storingen: +31 (0)6 - 4388

Dear all, I need an advice in the following problem. I have to maximize two functions of the form f1(x)=f(y1,x,alpha1,beta1) and f2(x)=(y2,x,alpha2,beta2), the maximization is with respect to alpha1, alpha2, beta1, beta2. I can maximize each function separately using nlm. The problem is that I have to add the constraint of the form g(alpha1)=g(alpha2). The total number of parameters is

>From the `R Data Import/Export' manual, shipped with R, as well as available from the official R web site (last three paragraphs of Section 3.1, describing functions in the `foreign' package): Function read.S which can read binary objects produced by S-PLUS 3.x, 4.x or 2000 on (32-bit) Unix or Windows (and can read them on a di erent OS). This is able to read many but not all S

Hi, I want to automatically fit variograms to a large number of different sample data sets, and call the funtion "likfit" (in package geoR) from within a for-loop. "likfit" does again call "optim". After ssuccessfully fitting variograms to some of the data sets, the procedure crashes and I get the error message: Error in optim(par = ini, fn = negloglik.GRF,

I have found the use of save( ) and attach( ) when supported by a pair of functions written by my colleague John Miyamoto, move( ) and rm.sv( ) quite useful in managing (1) collections of useful homebrew functions, (2) project workspaces, and (3) "packages" under development. An .Rdata file containing these and other handy functions together with a brief supporting document can be

Deall all, We need to perform a statistical analysis of a large database (40,000 entries with approximately 500 fields in each entry) currently handled in Oracle. The data contains categorical variables only. At the current stage we suggest classification and clustering analysis. We are planning to perform the analysis in R and would be very grateful for any

Dear RUsers, I am new to R. I am learning how to use R. I am a PC user and run R on windows. I would appreciate if some one could guide me on a few questions I have: 1) I have 4 cel files (2 replicates for NORM and Disease resp). I have been able to run siggenes on this dataset where I have 4 labels in the class file groupsnhi.cl op-> (0,0,1,1) and my data has been read into datrmanhi after