similar to: Creating an S3 method when the generic function is defined in another (imported) package

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

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 Saurav! On Sun, Jul 12, 2009 at 6:06 PM, Pathak, Saurav<s.pathak08 at imperial.ac.uk> wrote: > I am new to R, I have to do a 2 step Heckman model, my selection equation is > below which I was successful in running but I am unable to proceed further, > > > > I have so far used the following command > > glm(formula = s ~ age + gender + gemedu + gemhinc + es_gdppc +

Dear R Users: The functions of our "micEcon" package [1,2] can be subdivided into three categories: - microeconomic demand and firm models - sample selection models (mainly selection()) - routines for (likelihood) maximisation (e.g. maxLik(), maxNR(), maxBHHH()) (mainly used for ML estimation of sample selection models) Although sample selection models are often used in

I am trying to build a package (GWASTools, submitted to Bioconductor) that uses the "sandwich" package. I have references to "sandwich" in DESCRIPTION: Imports: methods, DBI, RSQLite, sandwich, survival, DNAcopy and NAMESPACE: import(sandwich) In the code itself is a call to vcovHC: Vhat <- vcovHC(mod, type="HC0") I have sandwich version 2.2-7 installed.

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 =

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

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]]

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

Hello everyone... We were trying to implement the Newton-Raphson method in R, and estimate the parameters a and b, of a function, F, however we can't seem to implement this the right way. Hope you can show me the right way to do this. I think what we want R to do is to read the data from the website and then peform maxNR on the function, F. Btw the version of R being used is "RGui for

Hi R-users, Recently, I use maxNR function to find maximizer. I have error appears as follows Error in maxNRCompute(fn = fn, grad = grad, hess = hess, start = start, : NA in the initial gradient My code is mu=2 s=1 n=300 library(maxLik) set.seed(1004) x<-rcauchy(n,mu,s) loglik<-function(mu) { log(prod(dcauchy(x,mu,s))) } maxNR(loglik,start=median(x))$estimate Does anyone know how

Dear R help archive group, I am looking for a maximization routine that I can use to maximize a large variety of relatively complex likelihoods. I undertand (from previous posts) that coding the objective function more efficiently can help. However, the optimization routine employed seems important too. So far, I have tried the optimization routines optim, maxlik, trust and nlminb. The latter two

Hi, I am relatively new to R; when creating functions, I run into problems with missing values. I would like my functions to ignore rows with missing values for arguments of my function) in the analysis (as for example is the case in STATA). Note that I don't want my function to drop rows if there are missing arguments elsewhere in a row, ie for variables that are not arguments of my

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 - First post, so excuse any errors in protocol: Wanted to ask if there's an easy way to use 'predict' with objects of class 'censReg', 'maxLik', 'maxim' or 'list'. Have a left-censored dataset, attempting to use a Tobit model and am working with the censReg package. I like how easy it is to move from glm models to predictions with

Hi Dirk! It would be great if you could upload a (Debian) package "r-cran-matrix" that includes the latest version of the R package "Matrix" to http://cran.r-project.org/bin/linux/ubuntu/intrepid/ "r-recommended" depends on "r-cran-matrix", but only the (outdated) version that shipped with intrepid (0.999375-10-1) is currently available. Note:

Might this be related to the Linux version? I'm testing on one of our university servers, and they tend to be deprived of regular updates sometimes... (Dirk, sorry for sending you this twice.) > Sys.info() sysname "Linux" release

Dear all I am happy that summary.default() no longer rounds since R 3.4.0. However, in R 3.4.0, in a few cases, print.summaryDefault() rounds the mean value (and the median value) differently on my GNU/Linux machine and on my colleague's MS-Windows machine. Here is a small (simplified) reproducible example: R> a <- 1234568.01 + c(0:1) R> summary(a) Output on MS-Windows (expected