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 that is a function only of betas and so to maximize it through maxLik for instance. Is that possible?
In order to be more clear I give an example of how it could be: Prob1 <- function(b, i) g.yj(b,y=1,h.np,i)/(g.yj(b,y=1,h.np,i)+g.yj(b,y=0,h.np,i)) loglik.i<- function(b, i) Y[i,]*log(Prob1(b,i))+(1-Y[i,])*log(1-Prob1(b,i)) where b denotes the betas, i the observations, Y is the response vector and g.yj(b,1,h.np,i) a function that I created previously, Prob1(b,i) is a function that gives the conditional probability for observation i and loglik.i(b,i) is function that gives the log-likelihood for observation i. How can I sum the loglik.i(b,i) for each i and remain as a function of b ONLY in order to maximize it??? For exemple this could be done manually by loglik<- function(b) loglik.i(b,1)+loglik.i(b,2)+loglik.i(b,3)+….+loglik.i(b,N) but how can I do it automatically for all observations? Thank you Dimitris -- View this message in context: http://r.789695.n4.nabble.com/sum-of-functions-tp3878448p3878448.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
