search for: negllh

...uld like to include a weighted likelihood estimation proceedure where the observations have an exponentially decaying weighting rather than the equal weighting implied by a standard MLE approach. The optimization function which leads to my parameter estimates is given by; gh.fit = try(optim(vega, negllh,hessian = se,pdf = gh.pdf, tmp.data = data, transf = transform, const.pars = vars[!opt.pars], silent = silent, par.names = names(vars), ...)) param.est = gh.fit$par In the above, vega are the parameters to estimate and pdf is the GH pdf. This seems to work well for the case wher...

...I've put together some script which gives me the parameters of a modified NIG distribution. Now I'd like to include a weighted vector within the maximization function. The code below gives me parameter estimates which are implicitly equally weighted. nig.par.fit <- try(optim(vega, negllh, hessian = se, pdf = density.nig, tmp.data = data, transf = transform, const.pars = vars[!opt.pars], silent = silent, par.names = names(vars), ...)) vega are the parameters to be fitted. This seems to work reasonably for my equally weighted observatio...