similar to: Suggestion for the optimization code

Dear list, I'm currently writing a C code to compute the (composite) likelihood - well this is done but not really robust. The C code is wrapped in an R one which call the optimizer routine - optim or nlm. However, the fitting procedure is far from being robust as the parameter space depends on the parameter - I have a covariance matrix that should be a valid one for example. Currently,

Dear all, I'd like tweaking the ... arguments that one user can pass in my function for fitting a model. More precisely, my objective function is (really) problematic to optimize using the "optim" function. Consequently, I'd like to add in the "control" argument of the latter function a "ndeps = rep(something, #par)" and/or "parscale =

Dear list members, I've got a small question on matrix multiplications in a C code. Because of a really cpu demanding likelihood, I had to use a C code within an R function wrapper. I'm pretty sure that there is already one good code for matrix multiplication in C - maybe in the R source code itself - but I wasn't able to find it. Anyone as an idea on how to handle matrix

I think most of us would expect prod(0:1000) to return 0, and ... ... it does. However, many of us also expect prod(x1, x2) to be equivalent to prod(c(x1,x2)) the same as we can expect that for min(), max(), sum() and such members of the "Summary" group. Consequently, prod(0, 1:1000) should also return 0, but as you see, it gives NaN which may be a bit puzzling... The

Dear all, I'm currently experiencing big troubles with my C code called by .Call in a R function. I know this may not be the right place for such things but these errors are driving me crazy. And I hope other people may have already experienced these problems so that they could give me good suggestions. Sorry if I'm completely out of topic. Well let's go... I'm writing a

Dear list, I got an automatic email complaining than some of my packages didn't pass 'R CMD check' for R-2.10.0 alpha anymore. Both of them make use of the "cases" LaTeX environment. Inspecting the log outputs I got: LaTeX errors when creating PDF version. This typically indicates Rd problems. LaTeX errors found: ! Misplaced alignment tab

GENERAL REFERENCE ON NONLINEAR OPTIMIZATION? What are your favorite references on nonlinear optimization? I like Bates and Watts (1988) Nonlinear Regression Analysis and Its Applications (Wiley), especially for its key insights regarding parameter effects vs. intrinsic curvature. Before I spent time and money on several of the refences cited on the help pages for "optim",

Dear R-help group, I have to maximize a likelihood with 40 parameters and I want to compare the MLE given by "nlminb" (Splus2000, on Windows) with those given by "optim" (R, on Unix). 1) On Splus, The algorithm "nlminb" seems to converge (the parameters stabilize) , it stops after several iterations ( around 400) with the message :"FUNCTION EVALUATION LIMIT

I'm making the move of the survival package from my own environment to, and have stumbled into a vacuum. The R Extensions manual has really nice instructions about how to lay out the directories, order the files, and run tests for DISTRIBUTION of a product, but I can't find anything on how to set up a reasonable DEVELOPMENT environment. In my local world, I had the .c and .s files in

Hi, I was wondering if someone could give a brief, big picture overview of the difference between the two optimization functions nlm and nlminb. I'm not familiar with PORT routines, so I was hoping someone could give an explanation. Thanks, Angelo _________________________________________________________________ Instantly invite friends from Facebook and other social networks to join yo

Dear all, Now that R has OpenMP facilities, I'm trying to use it for my own package but I'm still wondering if it is safe to use random number generation within a OpenMP block. I looked at the R writing extension document both on the OpenMP and Random number generation but didn't find any information about that. Could someone tell me if it is safe or not please ? Best, Mathieu

Hello all, I am trying to get the variance-covariance (VCOV) matrix of the parameter estimates produced from the nlminb minimizing function, using vcov.nlminb, but it seems to have been expunged from the MASS library. The hessian from nlminb is also producing NaNs, although the estimates seems to be right, so I can't VCOV that way either. I also tried using the vcov function after minimizing

I use lmer to fit a mixed effect model.It give some warnings.what does this warnings mean? and what should I do? > (fm2.mlm <- lmer(qd ~ edu + jiankang + peixun +hunyin + cadcj + age + age2 + sex + dangyuan + Comp.1 + Comp.2+trust.cz1 +(trust.cz1|commid), data = individual,na.action = "na.exclude",family="quasibinomial")) Generalized linear mixed model fit using PQL

I have constructed the function mml2 (below) based on the likelihood function described in the minimal latex I have pasted below for anyone who wants to look at it. This function finds parameter estimates for a basic Rasch (IRT) model. Using the function without the gradient, using either nlminb or optim returns the correct parameter estimates and, in the case of optim, the correct standard

Dear R users, I am trying to fit a GLMM to the following dataset; tab a b c 1 1 0.6 199320100313 2 1 0.8 199427100412 3 1 0.8 199427202112 4 1 0.2 199428100611 5 1 1.0 199428101011 6 1 0.8 199428101111 7 0 0.8 199527103011 8 1 0.6 199527200711 9 0 0.8 199527202411 10 0 0.6 199529100412 11 1 0.2 199626201111 12 2 0.8 199627200612 13 1 0.4 199628100111 14 1 0.8

Dear all, there seems to be a problem with displayed legends when a multiple figure environment is used, see the following example: par(mfrow=c(1,2)) curve(dnorm,col=4,from=-4,to=4); legend(-4,0.3,legend="curve",lty=1,col=4) legend(-4,0.2,legend="curve",lty=1,col=4) On my machines the first time the command legend() is issued the legend box stretches over the curve.

I am using R 2.7.0 on a linux platform. I am trying to reproduce a 2002 example using lme from the nlme library. I want to change the otimizer from the default (nlminb) to optim. Specifically, this is what I am trying to do: R> library(nlme) R> library(car) # for data only R> data(Blackmoor) # from car R> Blackmoor$log.exercise <- log(Blackmoor$exercise + 5/60, 2) R>

Hi, I'm trying to fit some data using a logistic function defined as y ~ a * (1+m*exp(-x/tau)) / (1+n*exp(-x/tau) My data is below: x <- 1:100 y <- c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0, 0,0,0,0,0,1,1,1,2,2,2,2,2,3,4,4,4,5, 5,5,5,6,6,6,6,6,8,8,9,9,10,13,14,16,19,21, 24,28,33,40,42,44,50,54,69,70,93,96,110,127,127,141,157,169,

Dear R-users I am trying to find a value for the risk free rate minimizing the difference between a BS call value with impl. volatilities minus the market price of a call (assuming this is just the average bid ask price) Here is my data: http://r.789695.n4.nabble.com/file/n3747509/S%26P_500_calls%2C_jan-jun_2010.csv S%26P_500_calls%2C_jan-jun_2010.csv S0 <- 1136.03 q <- 0.02145608 S0

Hello, R 3.5.2 on ubuntu 18.04. sessionInfo() at the end. Works with me, same results, cannot reproduce the error. f <- function(x) sum( log(diff(x)^2+.01) + (x[1]-1)^2 ) opt <- nlminb(rep(0, 10), f, lower=-1, upper=3) str(opt) xhat <- rep(1, 10) all.equal(opt$par, xhat, tol=0) # good: 5.53 e-7 #[1] "Mean relative difference: 5.534757e-07" all.equal(opt$objective,