[R] maximum likelihood

From: Alexandre Bonnet <bonnet_at_gmail.com>
Date: Sat 29 Jul 2006 - 10:39:36 EST


*hi,*

*using articial data, i'm supposed to estimate model*

*y(t) = beta(1) + beta(2)*x(t) + u(t), u(t) = gamma*u(t-1) + v(t), t =
1,...,100*

*which is correctly specified in two ways: ML ommiting the first
observation, and ML using all 100 observation.*

*since i'm still learning how to use R, i would like to know how MLE works.*

*there is neither information about the distribution of v(t) nor if u(t)
follows a stationary process.*

*suppose that v(t) is normaly distributed - so we want to estimate beta(1),
beta(2) and sigma2 (the variance of v(t)).*

*thanks in advance!*

*alexandre bonnet

getulio vargas foundation, brazil*

-- 
Alexandre Bonnet

	[[alternative HTML version deleted]]

______________________________________________
R-help@stat.math.ethz.ch 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.
Received on Sat Jul 29 10:44:56 2006

Archive maintained by Robert King, hosted by the discipline of statistics at the University of Newcastle, Australia.
Archive generated by hypermail 2.1.8, at Sun 30 Jul 2006 - 02:16:45 EST.

Mailing list information is available at https://stat.ethz.ch/mailman/listinfo/r-help. Please read the posting guide before posting to the list.