On 30/04/2012 12:37, Jouni Helske wrote:
Dear all,
I'd like to discuss about a possible bug in function StructTS of stats
package. It seems that the function returns wrong value of the
log-likelihood, as the added constant to the relevant part of the
log-likelihood is misspecified. Here is an si
Thanks, Tom, for the reply as well as to the reference to Claeskens & Hjort.
Ravi
From: Thomas Lumley [tlum...@uw.edu]
Sent: Thursday, May 03, 2012 4:41 PM
To: Mark Leeds
Cc: Ravi Varadhan; r-devel@r-project.org
Subject: Re: [Rd] The constant part of
On Thu, May 3, 2012 at 3:36 AM, Mark Leeds wrote:
> Hi Ravi: As far as I know ( well , really read ) and Bert et al can say
> more , the AIC is not dependent on the models being nested as long as the
> sample sizes used are the same when comparing. In some cases, say comparing
> MA(2), AR(1), you
Ravi
>
> -Original Message-
> From: r-devel-boun...@r-project.org [mailto:r-devel-boun...@r-project.org]
> On Behalf Of Jouni Helske
> Sent: Tuesday, May 01, 2012 2:17 PM
> To: r-devel@r-project.org
> Subject: Re: [Rd] The constant part of the log-likelihood in S
-project.org] On
Behalf Of Jouni Helske
Sent: Tuesday, May 01, 2012 2:17 PM
To: r-devel@r-project.org
Subject: Re: [Rd] The constant part of the log-likelihood in StructTS
Ok, it seems that R's AIC and BIC functions warn about different constants, so
that's probably enough. The constan
Ok, it seems that R's AIC and BIC functions warn about different constants,
so that's probably enough. The constants are not irrelevant though, if you
compute the log-likelihood of one model using StructTS, and then fit
alternative model using other functions such as arima(), which do take
account
This is not a problem at all. The log likelihood function is a function of the
model parameters and the data, but it is defined up to an additive arbitrary
constant, i.e. L(\theta) and L(\theta) + k are completely equivalent, for any
k. This does not affect model comparisons or hypothesis tests
