Dear List, This problem is more a statistic one than a R one. Any one can recommend me some references website or online paper on maximum likelihood estimation?I'm now working on that,while still doubt how to prove that the estimated parameters are normal distributed. Thanks for your time and help! Best, Ning
Check out Casella and Berger's Statistical Inference. ISBN 978-81-315-0394-2 or http://en.wikipedia.org/wiki/Maximum_likelihood as an online reference. --Mark J. Lamias From: Ning Cheng <wakinchauemil@gmail.com> To: r-help@r-project.org Sent: Sunday, February 27, 2011 3:19 PM Subject: [R] MLE estimation Dear List, This problem is more a statistic one than a R one. Any one can recommend me some references website or online paper on maximum likelihood estimation?I'm now working on that,while still doubt how to prove that the estimated parameters are normal distributed. Thanks for your time and help! Best, Ning ______________________________________________ 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. [[alternative HTML version deleted]]
I am partial to Gary King's book: Unifying Political Methodology: The Likelihood Theory of Statistical Inference (University of Michigan Press, 1998) Cheers David Cross d.cross at tcu.edu www.davidcross.us On Feb 27, 2011, at 2:19 PM, Ning Cheng wrote:> Dear List, > This problem is more a statistic one than a R one. > > Any one can recommend me some references website or online paper on > maximum likelihood estimation?I'm now working on that,while still > doubt how to prove that the estimated parameters are normal > distributed. > > Thanks for your time and help! > > Best, > Ning > > ______________________________________________ > R-help at 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.