search for: bhhh

Dear R users, Could you tell me where a I find some references of BHHH algorithm ? I need write it in R. Thank you.

I am currently trying to find MLE of a function with four parameters. My codes run well but i don't get the results. I get the following message: BHHH maximisation Number of iterations: 0 Return code: 100 Initial value out of range. I don't know this is so because of the way i have written my loglikelihood or what. The loglikelihood LogLik<-function(param){ beta_1<-param[1] beta_2<-param[2] beta_3<-param[3] beta_4<-param[4]...

Hello all, I have a problem estimating Random Effects model using censReg function. small part of code: UpC <- censReg(Power ~ Windspeed, left = -Inf, right = 2000,data=PData_In,method="BHHH",nGHQ = 4) Error in maxNRCompute(fn = logLikAttr, fnOrig = fn, gradOrig = grad, hessOrig = hess, : NA in the initial gradient ...then I tried to set starting values myself and here is the error what I got: UpC <- censReg(Power ~ Windspeed, left = -Inf, right = 2000,data=PData_In,met...

...tion data comprising 148 entries: fn<-function(c,psi,alpha) { s1<-sum(for(i in 1:n){(c[i]-(psi^(-1/alpha)*(lag(c[i],-1))))^2* (lag(c[i],-1)^((-2)*(alpha+1)) )}); s2<- sum(for(m in 1:n){log(lag(c[m],-1)^(((2)*alpha)+2))}); constant-(74*s1)-(1/2)*s2} In particular I want to use the BHHH and the BFGS algorithms. I have found the following packages that can be used for the task: *mle{stats4}, optim{stats}, maxBHHH{micEcon}, maxBFGS{micEcon}*. I have documented some of my attempts below ((a) package name (b) usage (c) my attempt and corresponding error). In all humility I apologise...

Hello R community, I have been using R's inbuilt maximum likelihood functions, for the different methods (NR, BFGS, etc). I have figured out how to use all of them except the maxBHHH function. This one is different from the others as it requires an observation level gradient. I am using the following syntax: maxBHHH(logLik,grad=nuGradient,finalHessian="BHHH",start=prm,iterlim=2) where logLik is the likelihood function and returns a vector of observation level likel...

Have a look at ?optim. I don't think it has the BHHH algorithm as an option, though. =========================================== David Barron Jesus College University of Oxford -----Original Message----- From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-bounces at stat.math.ethz.ch]On Behalf Of Harold Doran Sent: 10 July 2003 15:43 To: Fohr...

...sets the model does not converge. I am interested if there are any methods, based on the gradients or (an approximation of) the hessian which helps to determine what is the problem. Can anybody recommend a good textbook about numerical optimisation? Currently I am using 100 BFGS iterations + 100 BHHH iterations and I have programmed analytic gradients. The fool-proof method of excluding the variables one-by-one and simplifying the structure is quite a slow and not particularily insightsful. Thanks in advance Ott

...= S-1, b3= S-1, b4= S-1, dum = S-1, alpha0 = S^2, alpha = S, beta = S) upperB = c(a = 10*abs(Mean), di = 1-S, mi = 1-S, do = 1-S, fr =1-S, b1 = 1-S, b2 = 1-S,b3 = 1-S, b4 = 1-S, dum = 1-S, alpha0 = 100*Var, alpha = 1-S, beta = 1-S) fitt<-maxLik(start=param, logLik=garch2,method="BHHH", x=dat2$r_csi,Di=dat2$Di,Mi=dat2$Mi,Do=dat2$Do,Fr=dat2$Fr,y=dat2$r_t,z=dat2$r_sp,d=dat2$f) Note that optim always breaks down: nlminb and the BFGS and BHHH algorithmus from the maxLik-package work fine. The estimated coefficients are similiar to those of the EVIEWS Estimation. So I guess,...

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). For more complicated models the newer R would converge with not...

>>>>> 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 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). For more complicate...

Dear all, I would like to create a code for semiparametric Klein and Spady's estimator. For that I created a function that provides the log-likelihood function for each observation (so it is a function of betas and i, where i denotes the observation). Now, in order to maximize the log-likelihood function, I have to sum these log-likelihood functions for each i and so to get another function

Hi there, I need to run a Tobit Fixed Effects in a panel data with 4500 units for 8 years. It is a huge data set, my dependent variable is left truncated at zero, the distribution is skewed and my panel is balanced. Any suggestions on how to do that in R? I tried stuff like survreg, censReg, and tobit but none of them were satisfactory. Thanks, *Felipe Nunes* CAPES/Fulbright Fellow PhD

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

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