[R] Maximum Likelihood estimation of KB distribution
chamilka
cmanoj4 at gmail.com
Tue Jul 17 20:24:01 CEST 2012
Hi, The following distribution is known as Kumaraswamy binomial Distribution.
http://r.789695.n4.nabble.com/file/n4636782/kb.png
For a given data I need to estimate the paramters (alpha and beta) of this
distribution(Known as Kumaraswamy binomial Distribution, A Binomial Like
Distribution). For that, in order to use *optim()*, I first declared the
Negative Log-likelihood of this distribution as follows;
*Loglik.newdis2<-function(x,a,b,n,imax) {
term<-0
for (i in 0:imax) {
term=term+(((-1)**i)*(choose(b-1,i))*(beta(x+a+a*i,n-x+1)))
}
dens=a*b*choose(n,x)*term
KBLL2<-sum(log(dens))
return(-KBLL2)
} *
since there is an infinite convergent series in this PMF, I decided to
specify a maximum value as imax instead of infinity without loss of any
information, and n is the binomial trials.
Please tell me whether the declared negative loglikelihood (NLL) is correct
for this distribution?
***I couldn't get the result of this
paper(http://aps.ecnu.edu.cn/EN/abstract/abstract8722.shtml) with my NLL
Thanks in advance.
--
View this message in context: http://r.789695.n4.nabble.com/Maximum-Likelihood-estimation-of-KB-distribution-tp4636782.html
Sent from the R help mailing list archive at Nabble.com.
More information about the R-help
mailing list