similar to: nlm / fscale

I have just began to use R. I would like to know where I can find in R the equivalent of the LSMEANS of SAS when I realise a lm.. In the summary, there is the estimate but it's different of the LSMEANS. In advance, thank you. Martial Laurans Laboratoire Halieutique de Rennes ENSAR 65 rue de St Brieuc CS 84215 35042 Rennes

Dear R list members, I have a question about the proper use of the typsize and fscale arguments to nlm. I use nlm in my sem package to fit general structural-equation models, which entails maximizing a multinormal likelihood with respect to parameters that represent regression coefficients and covariances of variables. The magnitudes of these parameters can be very different. The

Dear all, I use a nested design with lm and glm, with factor2 nested within factor1. In order to test for the significance of both factors, I use anova tables on the obtained models such as follows: /> mod1<-lm(A~factor1/factor2) > amod1<-anova(mod1, test="F") Analysis of Variance Table Response: A Df Sum Sq Mean Sq F value Pr(>F) factor1

Dear members of the R user community, I am pleased to inform you that the program of the useR! 2009 conference (Rennes, France, July 8 to 10, 2009) is available online: http://www.agrocampus-ouest.fr/math/useR-2009/program.html You can register from the link below: http://www.agrocampus-ouest.fr/math/useR-2009/formulaires/registration.php The conference web page:

Dear members of the R user community, I am pleased to inform you that the program of the useR! 2009 conference (Rennes, France, July 8 to 10, 2009) is available online: http://www.agrocampus-ouest.fr/math/useR-2009/program.html You can register from the link below: http://www.agrocampus-ouest.fr/math/useR-2009/formulaires/registration.php The conference web page:

Hi all, I try to build a model using lmer, with 2 crossed fixed factors (poptype and matingtype) and 2 random factors (pop and family) which I want to nest within poptype. Which of these formulae should I use ? 1. lmer(y~poptype*matingtype + (1|poptype/pop/fam)) 2. lmer(y~poptype*matingtype + (poptype|/pop/fam)) thanks in advance Agnes -- Marie-Agn?s Coutellec UMR INRA-Agrocampus Ouest 985

It would be really nice if nlm took a set of "..." optional arguments that were passed through to the objective function. This level of hacking is probably slightly beyond me: is there a reason it would be technically difficult/inefficient? (I have a vague memory that it used to work this way either in S-PLUS or in some previous version of R, but I could easily be wrong.) Here's

Hi all, When upgrading to 2.11.1 recently I noticed different results being produced by my code. After much digging I have finally narrowed it to a call to nlm(). This can be replicated by: FixedRemovals<-1836180125888 AbStageInitial<-2223033830403 Rates<- 0.3102445 nlm(function(rootM,Abund,Loss,OtherM) {(Loss-(rootM/(rootM+OtherM)* (1-exp(-(rootM+OtherM)))*

Having worked with optim() and related programs for years, it surprised me that I haven't noticed this before, but optim() is inconsistent in how it deals with bounds constraints specified at infinity. Here's an example: # optim-glitch-Ex.R x0<-c(1,2,3,4) fnt <- function(x, fscale=10){ yy <- length(x):1 val <- sum((yy*x)^2)*fscale } grt <- function(x, fscale=10){ nn

Hi everyone. I have a problem that I have been unable to determine either the best way to proceed and why the methods I'm trying to use sometimes fail. I'm using the pf() function in an optimization function to find a noncentrality parameter that leads to a specific value at a specified quantile. My goal is to have a general function that returns the noncentrality parameter that

Dear R users, I am using the nlm function for minimization of the very non-linear function of four parameters. I am running 100 simulations and almost always I get the convergence code =2 (Successive iterates within tolerance. Current iterate is probably solution.) [about 75 times of 100]. Frequently, 3 of 4 relative gradients are close to zero and the fourth is huge but there are also cases

Hi Everyone, Is there a simple way to force nlm to take larger initial steps? Setting print.level = 2 allows me to inspect the step size at each iteration, but I appear not to have made any appreciable impact on it by changing values of typsize, fscale, steptol or stepmax. The steps repeatedly come out tiny, 1e-9 typically, and the algorithm is terminating not because the gradient is zero (it

hi everybody I have to do a lot of Anova with R and I would like to have another type of coefficients coding.. I explain. by default if I have 2 temperatures for an experience. 100°C or 130°C and I want to see the temperature effect on the presure I want to estimate the coefficient of each temperature. I will obtain ,with the anova, juste one coefficients for example +3,56 (for 100°C), and the

Hi ALL, With the pakage gstat How can one create a grid of points as in the meuse.grid example, from measuring sites as in the Meuse example Thanks in advance! Alain PONSERO Conservateur Réserve Naturelle de la Baie de Saint-Brieuc site de l'Etoile 22120 HILLION tel/fax : 02.96.32.31.40 <mailto:aponsero@cabri22.com> aponsero@cabri22.com

I am trying to view the source code of the function nlm in the stats package of R 2.4.1. I downloaded the source from CRAN and opened nlm.R, and it calls a .Internal function: .Internal(nlm(function(x) f(x, ...), p, hessian, typsize, fscale, msg, ndigit, gradtol, stepmax, steptol, iterlim)) This is the same thing I saw when entering the function name at the R command

Dear R users, Please help me on using "mix" function under package "mixdist". My data distribution shows there are two components for the mixture distribution: left part is an exponential and right part is a normal. So I plan to use "gamma" mixture distribution to estimate the parameters. Here is what I am using for the "mix" function. Test<-mix(x,

Hi R-listers, I am new to R and programming. I have a large dataframe composed of two grouping variables (species, population, with populations nested in species) and tens of continuously numeric variables. For each numeric variable, I want to make a boxplot with population as the X axis and the boxes filled according to which species it is belonging to. But, that is a definitely tedious work. I

Dear R-helpers, I want to make a series of boxplots on several numeric univariates with two group variables (species and population, population nested in species, and with population as the X-axis). In order to get a proper order of the individual populations in X-axis, I need to assign a wanted order to the factor (population). I used the levels() function to do this assignment, but it seemed

When I add the following instruction : make.link(log) I have an error that I don''t understand. model<-glm(spa~an, family=gaussian, make.link(log)) error in as.vector(x, "double"): cannot coerce to vector) If someone can help, thanks Martial -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Hi everyone, I am interested in using the SSYEV Lapack subroutine in a R package. Unfortunately I am not familiar with the all Lapack library and I was wondering why the routine SSYEV is not part of the R-LAPACK interface module. Is there any plan to extend the R-Lapack module in the next R release? Should I try to directly call the SSYEV routine of the external Lapack library from my R