similar to: fundamental guide to use of numerical optimizers?

Oh Hi Arne, You may recall we visited with this before. I do not believe the problem is algorithm specific. The algorithms I use the most often are BFGS and BHHH (or maxBFGS and maxBHHH). For simple econometric models such as probit, Tobit, and evening sample selection models, old and new versions of R work equally well (I write my own programs and do not use ones from AER or sampleSekection).

Hi Steven Which optimisation algorithms in maxLik work better under R-3.0.3 than under the current version of R? /Arne On Thu, 8 Oct 2020 at 21:05, Steven Yen <styen at ntu.edu.tw> wrote: > > Hmm. You raised an interesting point. Actually I am not having problems with aod per se?-it is just a supporting package I need while using old R. The essential package I need, maxLik, simply

>>>>> Steven Yen >>>>> on Fri, 9 Oct 2020 05:39:48 +0800 writes: > Oh Hi Arne, You may recall we visited with this before. I > do not believe the problem is algorithm specific. The > algorithms I use the most often are BFGS and BHHH (or > maxBFGS and maxBHHH). For simple econometric models such > as probit, Tobit, and evening

Hi, I'm using maxlik with functions specified (L, his gradient & hessian). Now I would like determine some robust standard errors of my estimators. So I 'm try to use vcovHC, or hccm or robcov for example but in use one of them with my result of maxlik, I've a the following error message : Erreur dans terms.default(object) : no terms component Is there some attributes

Hi all, Could anybody point me to a good/robust numerical optimization program to use in R? I am doing some MLE fitting. Thanks!

Hi all; I recently have been used 'maxLik' function for maximizing G2StNV178 function with gradient function gradlik; for receiving this goal, I write the following program; but I have been seen an error  in calling gradient  function; The maxLik function can't enter gradlik function (definition of gradient function); I guess my mistake is in line ******** ,that the vector  ‘h’ is

Hi R-helpers, Is it possible that I have the estimates from each step/iteration shown on the computer screen in order to monitor the process while I am using Optim or MaxLik? Thanks for your help. Maomao [[alternative HTML version deleted]]

Hmm. You raised an interesting point. Actually I am not having problems with aod per se?-it is just a supporting package I need while using old R. The essential package I need, maxLik, simply works better under R-3.0.3, for reason I do not understand?specifically the numerical gradients of the likelihood function are not evaluated as accurately in newer versions of R in my experience, which is why

Dear: I am having problem with simulation. Sometimes for 100 iteration, my program works but sometimes give error message regarding some "built-in function" which I never used in my code. I have no idea about the problem. Any suggestion, comments or idea regarding this would be highly appreciable. Thanks. I have used ---- "maxLik()" and "BBsolve()" in my code. Error

Greetings, I use maxNR function under maxLik package to find the REML estimates of the parameters of variance components in heteroskedastic linear regression models. I assume that in the model there is additive/multiplicative/mixed heteroskedasticity and I need estimate the respective parameters of additive/multiplicative/mixed variance components. For my research purposes I make a

Hi all. Recently i have been used maxlik package for optimizing a function with 5 parameters but i couldn't define gradient argument in function maxLik; How i can define a command to receive my goal? Whether I can change the core of this package?   Thanks for your attention and reply A. kheradmandi [[alternative HTML version deleted]]

Dear list, I want to run a statistical program (using its .exe file) from R by writing a script. I know there are some packages that call WinBUGS, Mplus etc. form R. I just want to call the .exe extension of this program and run several times writing a code in R. Thus, I want to have the output inside R. I just don't know where to start. Does anyone have any idea about that? Is there a

Dear Rhelpers I have the problem with initial values, could you please tell me how to solve it? Thank you June > p = summary(maxLik(fr,start=c(0,0,0,1,0,-25,-0.2))) Error in maxRoutine(fn = logLik, grad = grad, hess = hess, start = start, : NA in the initial gradient > p = summary(maxLik(fr,start=c(0,0,0,1,0,-25,-0.2),method="BFGS")) Error in optim(start, func, gr =

Is it possible to fit a structural equation model with link functions in R? I am trying to build a logistic-regression-like model in sem, because incorporating the dichotomous variables linearly seems inappropriate. Mplus can do something similar by specifying a 'link' parameter, but I would like to be able to do it in R, ofcourse. I have explored the 'sem' package from John Fox,

Hi, I recently tried to estimate a linear unconditional latent growth curve on 7 repeated measures using lavaan (most recent version): modspec=' alpha =~ 1*read_g0 + 1*read_g1 + 1*read_g2 + 1*read_g3 + 1*read_g4 + 1*read_g5 + 1*read_g6 beta =~ 0*read_g0 + 1*read_g1 + 2*read_g2 + 3*read_g3 + 4*read_g4 + 5*read_g5 + 6*read_g6 ' gmod=lavaan(modspec, data=math, meanstructure=T,

Dear Sir\ Madam  I am trying to maximise a complicated loglikelihood function  via EM algorithm which consists of two step "E-step and M-step"and in this case I need to maximize the expected of like lihood function " which I get from E- step" and take those estimates of parameter to update the E-step and repate these till convargence has been met. So I need to know if I

Do I miss here something? dtaa = read.table("http://www.ats.ucla.edu/stat/mplus/examples/ma_snijders/mlbook1.dat", sep=",") head(dtaa) # shows the data as it should be save(dtaa,"dtaa",file="c:/dtaa") d = load("c:/dtaa") head(d) # all data is lost, it only shows [1] "dtaa" "dtaa" Thanks for your hint on this.

Hi R users, I am trying to restrct the range of two of the parameters in a maximization problem. Both parameters should be between -1 and 1. As far as I know, if I choose the estimation method ="L-BFGS-B" under Optim, I can restrict the parameter space. However, the "L-BFGS-B" always require finite values of the loglik function and cannot get around of the problem if an

Hi, I have been using maxLik to do some MLE of Geometric Brownian Motion Process and everything has been going fine, but know I have tried to do it with jumps. I have create a vector of jumps and then added this into my log-likelihood equation, know I am getting a message: NA in the initial gradient My codes is hear # n<-length(combinedlr) j<-c(1,2,3,4,5,6,7,8,9,10)

I have been trying to use lavaan (version 0.4-7) for a simple path model, but the program seems to be computing far less degrees of freedom for my model then it should have. I have 7 variables, which should give (7)(8)/2 = 28 covariances, and hence 28 DF. The model seems to only think I have 13 DF. The code to reproduce the problem is below. Have I done something wrong, or is this something I