In model 1 (without the constant in the log-l), the value of the
maximized log-likelihood is -447.
If one wants to arrive at the actual full value of the log-likelihood
one should add to this nobs*ln(4/sqrt(2/$pi)) = 595*0.46.. = 274, and
obtain -447 + 274 = -173.
Now in model 2, parameter estimates are virtually identical with model
1, so one would expect that, since here the constant is already included
in the logl eq., it would arrive at a comparable result with the
corrected full value (i.e. -173), and not +511, which is the value for
the logl given by the code in model 2.
Alecos Papadopoulos
Athens University of Economics and Business, Greece
Department of Economics
cell:+30-6945-378680
fax: +30-210-8259763
skype:alecos.papadopoulos
On 10/7/2013 19:00, gretl-users-request(a)lists.wfu.edu wrote:
------------------------------ Message: 2 Date: Wed, 10 Jul 2013
09:05:57 +0200 (CEST)
From: "Riccardo (Jack) Lucchetti"
<r.lucchetti(a)univpm.it>
Subject: Re: [Gretl-users] Graph two densities together and Constant
in Log Likelihood To: Gretl list <gretl-users(a)lists.wfu.edu>
Message-ID:
<alpine.DEB.2.10.1307100904510.23263(a)ec-4.econ.univpm.it>
Content-Type: text/plain; charset="iso-8859-15" On Wed, 10 Jul 2013,
Alecos Papadopoulos wrote:
> Just a note that
> in model 2 (that is virtually identical to model 1 as regards to
> estimates and final gradient values), the value of the logl appears
> positive.
Since you add a positive constant to each observation, why would that be
surprising?
-------------------------------------------------------
Riccardo (Jack) Lucchetti
Dipartimento di Scienze Economiche e Sociali (DiSES)
Universit? Politecnica delle Marche
(formerly known as Universit? di Ancona)
r.lucchetti(a)univpm.it
http://www2.econ.univpm.it/servizi/hpp/lucchetti
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