Hi Rolf, I think the MLE should be 1.71, no? And yes, I am aware of the maximum=TRUE argument. I still feel something is wrong here.
Thanks! On Wed, Nov 18, 2015 at 6:23 PM, Rolf Turner <r.tur...@auckland.ac.nz> wrote: > On 19/11/15 11:31, C W wrote: > >> Dear R list, >> >> I am trying to find the MLE of the likelihood function. I will plot the >> log-likelihood to check my answer. >> >> Here's my R code: >> >> xvec <- c(2,5,3,7,-3,-2,0) >> >> fn <- function(theta){ >> >> sum(0.5 * (xvec - rep(theta, 7)) ^ 2 / 1 + 0.5 * log(1)) >> >> } >> >> gn <- Vectorize(fn) >> >> curve(gn, -5, 20) >> >> optimize(gn, c(-5, 20)) >> >> $minimum >> >> [1] 1.714286 >> >> $objective >> >> [1] 39.71429 >> >> >> The MLE using optimize() is 1.71, but what curve() gives me is the >> absolute >> minimum. >> >> I think 1.71 is the right answer, but why does the graph showing it's the >> minimum? What is going on here? >> > > Your graph shows that there is indeed a *minimum* at 1.71. And optimise() > is correctly finding that minimum. > > If you want optimise() to find the maximum, set maximum=TRUE. In which > case it will return "20" (or something very close to 20). > > Your function fn() appears not to be the log likelihood that you had in > mind. Perhaps you the negative of fn()??? > > cheers, > > Rolf Turner > > -- > Technical Editor ANZJS > Department of Statistics > University of Auckland > Phone: +64-9-373-7599 ext. 88276 > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.