Dear all, How can I compute the log likelihood of a gamma distributions of a vector. I tried the following. But it doesn't seem to work: samples<-c(6.1, 2.2, 14.9, 9.9, 24.6, 13.2) llgm <- dgamma(samples, scale=1, shape=2, log = TRUE) It gives [1] -4.291711 -1.411543 -12.198639 -7.607465 -21.397254 -10.619783 I expect it only returns "one" value instead of vector. What's wrong with my command above? - Edward
The scale of log-likelihood depends on the number of your data samples, you should sum over the log-densities from individual points: sum(llgm) Xiaohui Edward Wijaya ??:> Dear all, > > How can I compute the log likelihood of a gamma > distributions of a vector. > > I tried the following. But it doesn't seem to work: > > samples<-c(6.1, 2.2, 14.9, 9.9, 24.6, 13.2) > llgm <- dgamma(samples, scale=1, shape=2, log = TRUE) > > It gives > > [1] -4.291711 -1.411543 -12.198639 -7.607465 -21.397254 -10.619783 > > I expect it only returns "one" value instead of vector. > What's wrong with my command above? > > - Edward > > ______________________________________________ > R-help at r-project.org mailing list > stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > >