http://r.789695.n4.nabble.com/file/n3018477/JEC.dta JEC.dta
This is the data.
http://r.789695.n4.nabble.com/file/n3018477/A_Study_of_Cartel_Stability_The_Joint_Executive_Committee.pdf
A_Study_of_Cartel_Stability_The_Joint_Executive_Committee.pdf
This is the original paper.
The variable S is brea
- Original Message -
From: roach
Date: Saturday, October 23, 2010 4:41 am
Subject: Re: [R] Help: Maximum likelihood estimation
To: r-help@r-project.org
> I'm not quite familiar with E-M algorithm, but I think what I did was
> the
> first step of the iteration.
> The m
I'm not quite familiar with E-M algorithm, but I think what I did was the
first step of the iteration.
The method used in the original article is as follow:
http://r.789695.n4.nabble.com/file/n3008241/untitled.png
I gave lamda an initial value, and maximized the likelihood function.
This is the
Actually it is not that difficult to parameterize the covariance matrix
so that the
optimization is unconstrained. first parameterize the correlation matrix
and the
standard deviations separately. the std devs can be parameterized as
sigma_i=exp(x_i) 1<=i<=n
For the correlation matri
avi.
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf Of roach
Sent: Thursday, October 21, 2010 10:24 PM
To: r-help@r-project.org
Subject: [R] Help: Maximum likelihood estimation
I was trying to reproduce a result in a published jour
I was trying to reproduce a result in a published journal, and I have come
across some difficulties.
I have the following equation, which is two equations combined together.
http://r.789695.n4.nabble.com/file/n3006584/Screenshot.png
where
http://r.789695.n4.nabble.com/file/n3006584/Screenshot-1.p
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