similar to: Use of cfortran.h?

Subject: Non-GPL packages for R Packages that are not licensed in a way that permits re-distribution on CRAN are frequently a source of comment and concern on R-help and other lists. A good example of this problem is the Rdonlp2 package that has caused a lot of annoyance for a number of optimization users in R. They are also an issue for efforts like Dirk Eddelbuettel's cran2deb. There

Hi, I would also be in favor of a stronger stance on licenses. In industry, where we can really get in big trouble for violating a license, we often maintain internal repositories, or need to be careful about filtering what is used from CRAN. I think that is should really be a requirement the package authors commit to stating what the restrictions are on their packages. Nicholas On 10

I am running a multilevel growth curve model to examine predictors of social anhedonia (SA) trajectory through ages 12, 15 and 18. SA is a continuous numeric variable. The age variable (Index1) has been coded as 0 for age 12, 1 for age 15 and 2 for age 18. I am currently using a time varying predictor, stress (LSI), which was measured at ages 12, 15 and 18, to examine whether trajectory/variation

I am running a multilevel growth curve model to examine predictors of social anhedonia (SA) trajectory through ages 12, 15 and 18. SA is a continuous numeric variable. The age variable (Index1) has been coded as 0 for age 12, 1 for age 15 and 2 for age 18. I am currently using a time varying predictor, stress (LSI), which was measured at ages 12, 15 and 18, to examine whether trajectory/variation

Hi, Currently I am trying to solve a minimization problem using optim as method Nelder-Mead. However, Neldel-Mead needs many iterations until it finally converges. I have set $control.trace and $control.report such that I can see the value of the function at each iteration. I do see that I set the convergence criteria to strict in the sense that the function value does not change much. However,

Full_Name: Ricardo Luiz de Andrade Abrantes Version: 2.1.1 OS: Debian Linux, kernel 2.6.8 Submission from: (NULL) (201.6.83.153) The problem can be well explained with the following example: Suppose I made a program in fortran, and a C interfacece to it. Now I want to use this C interface in R to call my fortran program. Then I modified my C file to deal with SEXPs and compile it as a shared

Hello: The development version of Ecdat on R-Forge contains a vignette in which optim(?, method=?L-BFGS-B?) stops with an error message while violating the lower bound. To see all the details, try the following: install.packages("Ecdat", repos="http://R-Forge.R-project.org") Then do "help(pac=Ecdat)" -> "User guides, package

Hi, I would like to write a function that finds parameters of a log-normal distribution with a 1-alpha CI of (x_lcl, x_ucl): However, I don't know how to optimize for the two unknown parameters. Here is my unsuccessful attempt to find a lognormal distribution with a 90%CI of 1,20: prior <- function(x_lcl, x_ucl, alpha, mean, var) { a <- (plnorm(x_lcl, mean, var) - (alpha/2))^2 b

Hi i´m starting to work with free software (with free as in freedom) i've been working with GAMS (General Algebraic Modeling System) to solve static and dynamic optimization problems and non-linear large systems of equations i'm wondering if there is any free software and documentation on the subject, wether in R, Maxima, or something else i will appreciate any help and any references

Folks, Has anyone implemented Powell's Method for minimisation in R ? Many thanks, Tolga

Dear all, I am writing as I would really need your help on the problem with gamm4. I have tried to find a solution online but I wasn't very successful. I am running a gamm4 model with an interaction between two variable using the tensor term, t2. I have a group variable (super end group) with six factors; I would like to run the model to see the how the interaction term varies across the

Hello! I am trying to create an R optimization routine for a task that's currently being done using Excel (lots of tables, formulas, and Solver). However, otpim seems to be finding a local minimum. Example data, functions, and comparison with the solution found in Excel are below. I am not experienced in optimizations so thanks a lot for your advice! Dimitri ### 2 Inputs:

I am making my first attempts at using some Fortran code with R, and so far it's going OK. To print from my Fortran programs, it seems I need subroutines dblepr, realpr and intpr. From the excellent "Writing R Extensions" document: "Three subroutines are provided to ease the output of information from FORTRAN code. subroutine dblepr(label, nchar, data, ndata)

SAS has DUD (Does not Use Derivatives)/Secant Method for nonlinear regression, does R offer this option for nonlinear regression? I have read the helpfile for nls() and could not find such option, any suggestion? Thanks, Derek [[alternative HTML version deleted]]

Apologies if this is off-topic and if you could point me to the right place to ask this questions, I would greatly appreciate it. I have just taken over our department's system where we have a couple of UNIX servers running samba to share user home directories on NT clients. My system admin is trying to upgrade to WINS server and had trouble with my UNIX server host name that have

Dear Srinidhi, You are trying to fit 1 random intercept and 2 random slopes per individual, while you have at most 3 observations per individual. You simply don't have enough data to fit the random slopes. Reduce the random part to (1|ID). Best regards, Thierry ir. Thierry Onkelinx Statisticus / Statistician Vlaamse Overheid / Government of Flanders INSTITUUT VOOR NATUUR- EN BOSONDERZOEK

Dear Srinidhi, You are trying to fit 1 random intercept and 2 random slopes per individual, while you have at most 3 observations per individual. You simply don't have enough data to fit the random slopes. Reduce the random part to (1|ID). Best regards, Thierry ir. Thierry Onkelinx Statisticus / Statistician Vlaamse Overheid / Government of Flanders INSTITUUT VOOR NATUUR- EN BOSONDERZOEK

Dear R-er, For a non-linear optimisation, I used optim() with BFGS method but it stopped regularly before to reach a true mimimum. It was not a problem with limit of iterations, just a local minimum. I was able sometimes to reach better minimum using several rounds of optim(). Then I moved to optimx() to do the different optim rounds automatically using "Nelder-Mead" and

> Date: Tue, 2 Apr 2013 06:59:13 -0500 > From: Paul Johnson <pauljohn32 at gmail.com> > To: qi A <send2aqi at gmail.com> > Cc: R-help <r-help at r-project.org> > Subject: Re: [R] DUD (Does not Use Derivatives) for nonlinear > regression in R? > Message-ID: > <CAErODj_1pK8raHyAme_2Wt5zQZ_HqOhRjQ62bChhkORWbW=o2A at mail.gmail.com> > Content-Type:

Good evening! I have a multi-dimensional minimization problem whose gradient is pretty hard to code. I tried Nelder and Mead method implemented in function optim and it does not work well. I also tried the quasi Newton method in optim using difference as approximate derivative. It does not work well either. I just went through Numerical Recipes book. The book discusses another method without