PS:
Aim is to emulate calling protocol for current matlab/kalman/likelihood .m files.
I am currently adjusting the kalman_filter.cpp dll suite (kalman_filter.cpp to start with) to create internally H and Pinf 0 matrices of suitable size if empty or single 0 passed to them and so that non-diffuse on can take mf instead Z as C++ currently expects.
(The matlab*.cpp files have already been adjusted to return likelihood array as .m files do.)
in meantime one may use .m file to prepare those on the lines of the kalmandll_test.m I just enclosed in the matlab subdirectory of sources/kalman repository.
Best regards
George ----- Original Message ----- From: G. Perendia To: List for Dynare developers Sent: Wednesday, May 27, 2009 2:56 PM Subject: Re: [DynareDev] Kalman Filter
The filter routines there have names and should follow calling rules for the par matlab/kalman/likelihood ones but they do not yet take mf and still expect Z matrix of 1s to map system to observables instead and Pinf must not be empty but at least be initialised to a zeros matrix of Pstar size.
The smoother is generic as it was, not suitable for running at all
Best regards
George
----- Original Message ----- From: Stéphane Adjemian To: List for Dynare developers Sent: Wednesday, May 27, 2009 2:46 PM Subject: Re: [DynareDev] Kalman Filter
Hi George
2009/5/27 G. Perendia george@perendia.orangehome.co.uk
Hi
The C++ Kalman dll driver routines in /mex/kalman/matlab are still in development
Sure...
and the code there is still subject to developer testing
... But I'd like to play with it.
and the Makefile there is not yet complete but it should use blas/lapack from Matlab libraries.
Ok. I will adapt your Makefile for my platform.
Best, Stéphane.
Best regards
George Perendia Tel.: 02072815392 Mob: 07951415480 ----- Original Message ----- From: Stéphane Adjemian To: List for Dynare developers Sent: Wednesday, May 27, 2009 2:18 PM Subject: Re: [DynareDev] Kalman Filter
Oui, oui... I never use the presampling option... And with all the examples I have ever considered it takes much more than 10 iterations to get to the steady state kalman filter.
By the way, is there somewhere linux a Makefile for the cc kalman routines? Also, why do we need Atlas (if we also use matlab's lapack/blas libraries)?
Stéphane.
2009/5/27 Michel Juillard michel.juillard@ens.fr
Si le filtre converge a l'etat stationnaire a une date avant start (la date a partir de laquelle on cumule la vraisemblance), alors additionner tous les determinants des iterations dans le filtre stationnaire a la derniere periode fausse le calcul de la constante.
amicalement
Michel
Stéphane Adjemian wrote:
Thanks Michel. Your commit is ok for me. I do not yet understand the problem raised by George. I need to go through his example...
Stéphane.
2009/5/27 Michel Juillard <michel.juillard@ens.fr mailto:michel.juillard@ens.fr>
Thanks Stephane,
I just uploaded a new version of kalman_filter.m Tell me what you think
Best
Michel
Stéphane Adjemian wrote:
Hi all,
I agree, the matlab code is very unclear (even if I had fun writting it this way ;-) and prone to errors if one uses the vector lik (Marco is using it). I would rather prefer to add the constants outside of the loop with a (sub)vector operation, this should be more efficient. I will do it today or tomorrow.
Best, Stéphane.
2009/5/27 Michel Juillard <michel.juillard@ens.fr
mailto:michel.juillard@ens.fr <mailto:michel.juillard@ens.fr
mailto:michel.juillard@ens.fr>>
On closer inspection, I don't think that the expression pointed by George in kalman_filter.m is wrong:
1. reste = smpl-t or the number of periods during which the filter is stationary. This shouldn't be larger than T-start+1
2. it is problematic (see below) but not wrong to add all the determinants at once in the last period of the stationary filter
3. I don't think this explains the difference with the C++ version of the filter and we still have to look for it.
4. it remains that the current code is very unclear and that if LIK is correct the vector lik doesn't have the correct constants on each elements.
5. I would like to simplify the code and add the correct constant to each element of the lik vector. It would be a little bit less efficient in Matlab than the current code, but I doubt it would be noticeable. Stephane, what do you think?
Best
Michel
G. Perendia wrote:
Dear Michel
I think I found an error in Dynare Matlab kalman_filter. suite of utilities which affects the likelihood LIK results with start>1 (i.e. presampling>0):
the calculation speed-up construct which relies on converged covariance matrix
lik(t) = lik(t) + reste*log(dF);
adds reste * log(dF) to the last-1 (i.e. the smpl) member of lik (the last, the lik(smpl+1) one contains smpl*pp*log(2*pi)) but reste is usually larger than T-start+1 so that
LIK = .5*(sum(lik(start:end))-(start-1)*lik(smpl+1)/smpl)
has much more log(dF)s added than required since they are all concentrated in the last-1 (the T) member
For example, if I change the above construct to lik(t) = lik(t) + min(reste,(smpl-start+1))*log(dF);
the reported likelihood for presample=40 from Matlab KF is 1640935.5855267849 which is nearly the same as that from C++ KF below: 1640935.5854489324
Shall I make changes to kalman/likelihood/ KFs and upload the .m files? This problem affects also the older versions of DiffuseLikelihood**.m too.
Best regards
George artilogica@btconnect.com mailto:artilogica@btconnect.com
<mailto:artilogica@btconnect.com
mailto:artilogica@btconnect.com>
----- Original Message ----- From: "Michel Juillard" <michel.juillard@ens.fr mailto:michel.juillard@ens.fr
<mailto:michel.juillard@ens.fr mailto:michel.juillard@ens.fr>>
To: "G. Perendia" <george@perendia.orangehome.co.uk mailto:george@perendia.orangehome.co.uk <mailto:george@perendia.orangehome.co.uk mailto:george@perendia.orangehome.co.uk>>
Sent: Tuesday, May 26, 2009 10:32 AM Subject: Re: Kalman Filter+PS
Hi George,
Re 1) below: I modified C++ KF so that it reports log-likelihood for given start/preampling in same/similar manner as the Matlab KFs do and I am getting approximately close results, e.g.
ll= -1640935.5854489324 for C++ and (-) 1640482.4179242959 for Matlab KF (for start=41, i.e. presample=40). whilst they appear same for presample=0 (e.g.2.5906e+006), i.e. -2590556.989730841 vs 2590556.989778722
Are those results acceptably close or should I investigate further where the above difference may come form?
This indicates a problem . The difference should be the same with and without presample. It may come from the computation of the likelihood constant. This is done in a very obscure manner in Dynare Matlab.
_______________________________________________ Dev mailing list Dev@dynare.org mailto:Dev@dynare.org
<mailto:Dev@dynare.org mailto:Dev@dynare.org>
http://www.dynare.org/cgi-bin/mailman/listinfo/dev
-- Stéphane Adjemian CEPREMAP & Université du Maine
Tel: (33)1-43-13-62-39 ------------------------------------------------------------------------
_______________________________________________ Dev mailing list Dev@dynare.org mailto:Dev@dynare.org http://www.dynare.org/cgi-bin/mailman/listinfo/dev
_______________________________________________ Dev mailing list Dev@dynare.org mailto:Dev@dynare.org http://www.dynare.org/cgi-bin/mailman/listinfo/dev
-- Stéphane Adjemian CEPREMAP & Université du Maine
Tel: (33)1-43-13-62-39 ------------------------------------------------------------------------
_______________________________________________ Dev mailing list Dev@dynare.org http://www.dynare.org/cgi-bin/mailman/listinfo/dev
_______________________________________________ Dev mailing list Dev@dynare.org http://www.dynare.org/cgi-bin/mailman/listinfo/dev
-- Stéphane Adjemian CEPREMAP & Université du Maine
Tel: (33)1-43-13-62-39
------------------------------------------------------------------------
_______________________________________________ Dev mailing list Dev@dynare.org http://www.dynare.org/cgi-bin/mailman/listinfo/dev
_______________________________________________ Dev mailing list Dev@dynare.org http://www.dynare.org/cgi-bin/mailman/listinfo/dev
-- Stéphane Adjemian CEPREMAP & Université du Maine
Tel: (33)1-43-13-62-39
----------------------------------------------------------------------------
_______________________________________________ Dev mailing list Dev@dynare.org http://www.dynare.org/cgi-bin/mailman/listinfo/dev
Dear George,
the aim of the project is to build a whole DLL for estimation, including optimization and Metropolis. Don't loose to much time matching the calling conventions from the exiting *.m files. For example, the mf input arguments looses its utility if we always use the Schur transformation of the transition equation. Calling *.mex functions instead of *.m functions has an overhead cost. So it isn't informative to time a Kalman filter DLL called from a Matlab loop. For the timing exercise to make sense, we would need to code the calling loop inside the DLL.
Best
Michel
G. Perendia wrote:
PS:
Aim is to emulate calling protocol for current matlab/kalman/likelihood .m files.
I am currently adjusting the kalman_filter.cpp dll suite (kalman_filter.cpp to start with) to create internally H and Pinf 0 matrices of suitable size if empty or single 0 passed to them and so that non-diffuse on can take mf instead Z as C++ currently expects.
(The matlab*.cpp files have already been adjusted to return likelihood array as .m files do.)
in meantime one may use .m file to prepare those on the lines of the kalmandll_test.m I just enclosed in the matlab subdirectory of sources/kalman repository.
Best regards
George ----- Original Message -----
*From:* G. Perendia <mailto:george@perendia.orangehome.co.uk> *To:* List for Dynare developers <mailto:dev@dynare.org> *Sent:* Wednesday, May 27, 2009 2:56 PM *Subject:* Re: [DynareDev] Kalman Filter The filter routines there have names and should follow calling rules for the par matlab/kalman/likelihood ones but they do not yet take mf and still expect Z matrix of 1s to map system to observables instead and Pinf must not be empty but at least be initialised to a zeros matrix of Pstar size. The smoother is generic as it was, not suitable for running at all Best regards George ----- Original Message ----- *From:* Stéphane Adjemian <mailto:stephane.adjemian@gmail.com> *To:* List for Dynare developers <mailto:dev@dynare.org> *Sent:* Wednesday, May 27, 2009 2:46 PM *Subject:* Re: [DynareDev] Kalman Filter *Hi George* 2009/5/27 G. Perendia <george@perendia.orangehome.co.uk <mailto:george@perendia.orangehome.co.uk>> Hi The C++ Kalman dll driver routines in /mex/kalman/matlab are still in development *Sure... * and the code there is still subject to developer testing *... But I'd like to play with it.* and the Makefile there is not yet complete but it should use blas/lapack from Matlab libraries. *Ok. I will adapt your Makefile for my platform.** Best, Stéphane.* Best regards George Perendia Tel.: 02072815392 Mob: 07951415480 ----- Original Message ----- *From:* Stéphane Adjemian <mailto:stephane.adjemian@gmail.com> *To:* List for Dynare developers <mailto:dev@dynare.org> *Sent:* Wednesday, May 27, 2009 2:18 PM *Subject:* Re: [DynareDev] Kalman Filter Oui, oui... I never use the presampling option... And with all the examples I have ever considered it takes much more than 10 iterations to get to the steady state kalman filter. By the way, is there somewhere linux a Makefile for the cc kalman routines? Also, why do we need Atlas (if we also use matlab's lapack/blas libraries)? Stéphane. 2009/5/27 Michel Juillard <michel.juillard@ens.fr <mailto:michel.juillard@ens.fr>> Si le filtre converge a l'etat stationnaire a une date avant start (la date a partir de laquelle on cumule la vraisemblance), alors additionner tous les determinants des iterations dans le filtre stationnaire a la derniere periode fausse le calcul de la constante. amicalement Michel Stéphane Adjemian wrote: Thanks Michel. Your commit is ok for me. I do not yet understand the problem raised by George. I need to go through his example... Stéphane. 2009/5/27 Michel Juillard <michel.juillard@ens.fr <mailto:michel.juillard@ens.fr> <mailto:michel.juillard@ens.fr <mailto:michel.juillard@ens.fr>>> Thanks Stephane, I just uploaded a new version of kalman_filter.m Tell me what you think Best Michel Stéphane Adjemian wrote: Hi all, I agree, the matlab code is very unclear (even if I had fun writting it this way ;-) and prone to errors if one uses the vector lik (Marco is using it). I would rather prefer to add the constants outside of the loop with a (sub)vector operation, this should be more efficient. I will do it today or tomorrow. Best, Stéphane. 2009/5/27 Michel Juillard <michel.juillard@ens.fr <mailto:michel.juillard@ens.fr> <mailto:michel.juillard@ens.fr <mailto:michel.juillard@ens.fr>> <mailto:michel.juillard@ens.fr <mailto:michel.juillard@ens.fr> <mailto:michel.juillard@ens.fr <mailto:michel.juillard@ens.fr>>>> On closer inspection, I don't think that the expression pointed by George in kalman_filter.m is wrong: 1. reste = smpl-t or the number of periods during which the filter is stationary. This shouldn't be larger than T-start+1 2. it is problematic (see below) but not wrong to add all the determinants at once in the last period of the stationary filter 3. I don't think this explains the difference with the C++ version of the filter and we still have to look for it. 4. it remains that the current code is very unclear and that if LIK is correct the vector lik doesn't have the correct constants on each elements. 5. I would like to simplify the code and add the correct constant to each element of the lik vector. It would be a little bit less efficient in Matlab than the current code, but I doubt it would be noticeable. Stephane, what do you think? Best Michel G. Perendia wrote: Dear Michel I think I found an error in Dynare Matlab kalman_filter. suite of utilities which affects the likelihood LIK results with start>1 (i.e. presampling>0): the calculation speed-up construct which relies on converged covariance matrix lik(t) = lik(t) + reste*log(dF); adds reste * log(dF) to the last-1 (i.e. the smpl) member of lik (the last, the lik(smpl+1) one contains smpl*pp*log(2*pi)) but reste is usually larger than T-start+1 so that LIK = .5*(sum(lik(start:end))-(start-1)*lik(smpl+1)/smpl) has much more log(dF)s added than required since they are all concentrated in the last-1 (the T) member For example, if I change the above construct to lik(t) = lik(t) + min(reste,(smpl-start+1))*log(dF); the reported likelihood for presample=40 from Matlab KF is 1640935.5855267849 which is nearly the same as that from C++ KF below: 1640935.5854489324 Shall I make changes to kalman/likelihood/ KFs and upload the .m files? This problem affects also the older versions of DiffuseLikelihood**.m too. Best regards George artilogica@btconnect.com <mailto:artilogica@btconnect.com> <mailto:artilogica@btconnect.com <mailto:artilogica@btconnect.com>> <mailto:artilogica@btconnect.com <mailto:artilogica@btconnect.com> <mailto:artilogica@btconnect.com <mailto:artilogica@btconnect.com>>> ----- Original Message ----- From: "Michel Juillard" <michel.juillard@ens.fr <mailto:michel.juillard@ens.fr> <mailto:michel.juillard@ens.fr <mailto:michel.juillard@ens.fr>> <mailto:michel.juillard@ens.fr <mailto:michel.juillard@ens.fr> <mailto:michel.juillard@ens.fr <mailto:michel.juillard@ens.fr>>>> To: "G. Perendia" <george@perendia.orangehome.co.uk <mailto:george@perendia.orangehome.co.uk> <mailto:george@perendia.orangehome.co.uk <mailto:george@perendia.orangehome.co.uk>> <mailto:george@perendia.orangehome.co.uk <mailto:george@perendia.orangehome.co.uk> <mailto:george@perendia.orangehome.co.uk <mailto:george@perendia.orangehome.co.uk>>>> Sent: Tuesday, May 26, 2009 10:32 AM Subject: Re: Kalman Filter+PS Hi George, Re 1) below: I modified C++ KF so that it reports log-likelihood for given start/preampling in same/similar manner as the Matlab KFs do and I am getting approximately close results, e.g. ll= -1640935.5854489324 for C++ and (-) 1640482.4179242959 for Matlab KF (for start=41, i.e. presample=40). whilst they appear same for presample=0 (e.g.2.5906e+006), i.e. -2590556.989730841 vs 2590556.989778722 Are those results acceptably close or should I investigate further where the above difference may come form? This indicates a problem . The difference should be the same with and without presample. It may come from the computation of the likelihood constant. This is done in a very obscure manner in Dynare Matlab. _______________________________________________ Dev mailing list Dev@dynare.org <mailto:Dev@dynare.org> <mailto:Dev@dynare.org <mailto:Dev@dynare.org>> <mailto:Dev@dynare.org <mailto:Dev@dynare.org> <mailto:Dev@dynare.org <mailto:Dev@dynare.org>>> http://www.dynare.org/cgi-bin/mailman/listinfo/dev -- Stéphane Adjemian CEPREMAP & Université du Maine Tel: (33)1-43-13-62-39 ------------------------------------------------------------------------ _______________________________________________ Dev mailing list Dev@dynare.org <mailto:Dev@dynare.org> <mailto:Dev@dynare.org <mailto:Dev@dynare.org>> http://www.dynare.org/cgi-bin/mailman/listinfo/dev _______________________________________________ Dev mailing list Dev@dynare.org <mailto:Dev@dynare.org> <mailto:Dev@dynare.org <mailto:Dev@dynare.org>> http://www.dynare.org/cgi-bin/mailman/listinfo/dev -- Stéphane Adjemian CEPREMAP & Université du Maine Tel: (33)1-43-13-62-39 ------------------------------------------------------------------------ _______________________________________________ Dev mailing list Dev@dynare.org <mailto:Dev@dynare.org> http://www.dynare.org/cgi-bin/mailman/listinfo/dev _______________________________________________ Dev mailing list Dev@dynare.org <mailto:Dev@dynare.org> http://www.dynare.org/cgi-bin/mailman/listinfo/dev -- Stéphane Adjemian CEPREMAP & Université du Maine Tel: (33)1-43-13-62-39 ------------------------------------------------------------------------ _______________________________________________ Dev mailing list Dev@dynare.org <mailto:Dev@dynare.org> http://www.dynare.org/cgi-bin/mailman/listinfo/dev _______________________________________________ Dev mailing list Dev@dynare.org <mailto:Dev@dynare.org> http://www.dynare.org/cgi-bin/mailman/listinfo/dev -- Stéphane Adjemian CEPREMAP & Université du Maine Tel: (33)1-43-13-62-39 ------------------------------------------------------------------------ _______________________________________________ Dev mailing list Dev@dynare.org http://www.dynare.org/cgi-bin/mailman/listinfo/dev
Dev mailing list Dev@dynare.org http://www.dynare.org/cgi-bin/mailman/listinfo/dev
Dear Michel
1) Shall we then, for start, have only all-in-one driving cc/dll called kalman_filters.c/dll (i.e rather than emulating 4 or more as in matlab/kalman/likelihood)? It would contain combination of all: univariate and multivariate, non diffuse and diffuse and it is easier to maintain.
It will handle presampling/start like Matlab Dynare and returning full likelihood array for comparing and testing KF results (and as new Dynare matlab KFs do).
For the time being and prototype testing then the full-size Z, H and Pinf matrices will be created by matlab driver file such as kalmandll_test.m
2) Are we going to cater for missing observation/time-variable state matrices KFs too?
Best regards
George
----- Original Message ----- From: "Michel Juillard" michel.juillard@ens.fr To: "List for Dynare developers" dev@dynare.org Sent: Wednesday, May 27, 2009 5:51 PM Subject: Re: [DynareDev] Kalman Filter
Dear George,
the aim of the project is to build a whole DLL for estimation, including optimization and Metropolis. Don't loose to much time matching the calling conventions from the exiting *.m files. For example, the mf input arguments looses its utility if we always use the Schur transformation of the transition equation. Calling *.mex functions instead of *.m functions has an overhead cost. So it isn't informative to time a Kalman filter DLL called from a Matlab loop. For the timing exercise to make sense, we would need to code the calling loop inside the DLL.
Best
Michel
G. Perendia wrote:
PS:
Aim is to emulate calling protocol for current matlab/kalman/likelihood .m files.
I am currently adjusting the kalman_filter.cpp dll suite (kalman_filter.cpp to start with) to create internally H and Pinf 0 matrices of suitable size if empty or single 0 passed to them and so that non-diffuse on can take mf instead Z as C++ currently expects.
(The matlab*.cpp files have already been adjusted to return likelihood array as .m files do.)
in meantime one may use .m file to prepare those on the lines of the kalmandll_test.m I just enclosed in the matlab subdirectory of sources/kalman repository.
Best regards
George ----- Original Message -----
*From:* G. Perendia <mailto:george@perendia.orangehome.co.uk> *To:* List for Dynare developers <mailto:dev@dynare.org> *Sent:* Wednesday, May 27, 2009 2:56 PM *Subject:* Re: [DynareDev] Kalman Filter The filter routines there have names and should follow calling rules for the par matlab/kalman/likelihood ones but they do not yet take mf and still expect Z matrix of 1s to map system to observables instead and Pinf must not be empty but at least be initialised to a zeros matrix of Pstar size. The smoother is generic as it was, not suitable for running at all Best regards George ----- Original Message ----- *From:* Stéphane Adjemian <mailto:stephane.adjemian@gmail.com> *To:* List for Dynare developers <mailto:dev@dynare.org> *Sent:* Wednesday, May 27, 2009 2:46 PM *Subject:* Re: [DynareDev] Kalman Filter *Hi George* 2009/5/27 G. Perendia <george@perendia.orangehome.co.uk <mailto:george@perendia.orangehome.co.uk>> Hi The C++ Kalman dll driver routines in /mex/kalman/matlab are still in development *Sure... * and the code there is still subject to developer testing *... But I'd like to play with it.* and the Makefile there is not yet complete but it should use blas/lapack from Matlab libraries. *Ok. I will adapt your Makefile for my platform.** Best, Stéphane.* Best regards George Perendia Tel.: 02072815392 Mob: 07951415480 ----- Original Message ----- *From:* Stéphane Adjemian <mailto:stephane.adjemian@gmail.com> *To:* List for Dynare developers <mailto:dev@dynare.org> *Sent:* Wednesday, May 27, 2009 2:18 PM *Subject:* Re: [DynareDev] Kalman Filter Oui, oui... I never use the presampling option... And with all the examples I have ever considered it takes much more than 10 iterations to get to the steady state kalman filter. By the way, is there somewhere linux a Makefile for the cc kalman routines? Also, why do we need Atlas (if we also use matlab's lapack/blas libraries)? Stéphane. 2009/5/27 Michel Juillard <michel.juillard@ens.fr <mailto:michel.juillard@ens.fr>> Si le filtre converge a l'etat stationnaire a une date avant start (la date a partir de laquelle on cumule la vraisemblance), alors additionner tous les determinants des iterations dans le filtre stationnaire a la derniere periode fausse le calcul de la constante. amicalement Michel Stéphane Adjemian wrote: Thanks Michel. Your commit is ok for me. I do not yet understand the problem raised by George. I need to go through his example... Stéphane. 2009/5/27 Michel Juillard <michel.juillard@ens.fr <mailto:michel.juillard@ens.fr> <mailto:michel.juillard@ens.fr <mailto:michel.juillard@ens.fr>>> Thanks Stephane, I just uploaded a new version of kalman_filter.m Tell me what you think Best Michel Stéphane Adjemian wrote: Hi all, I agree, the matlab code is very unclear (even if I had fun writting it this way ;-) and prone to errors if one uses the vector lik (Marco is using it). I would rather prefer to add the constants outside of the loop with a (sub)vector operation, this should be more efficient. I will do it today or tomorrow. Best, Stéphane. 2009/5/27 Michel Juillard <michel.juillard@ens.fr <mailto:michel.juillard@ens.fr> <mailto:michel.juillard@ens.fr <mailto:michel.juillard@ens.fr>> <mailto:michel.juillard@ens.fr <mailto:michel.juillard@ens.fr> <mailto:michel.juillard@ens.fr <mailto:michel.juillard@ens.fr>>>> On closer inspection, I don't think that the expression pointed by George in kalman_filter.m is wrong: 1. reste = smpl-t or the number of periods during which the filter is stationary. This shouldn't be larger than T-start+1 2. it is problematic (see below) but not wrong to add all the determinants at once in the last period of the stationary filter 3. I don't think this explains the difference with the C++ version of the filter and we still have to look for it. 4. it remains that the current code is very unclear and that if LIK is correct the vector lik doesn't have the correct constants on each elements. 5. I would like to simplify the code and add the correct constant to each element of the lik vector. It would be a little bit less efficient in Matlab than the current code, but I doubt it would be noticeable. Stephane, what do you think? Best Michel G. Perendia wrote: Dear Michel I think I found an error in Dynare Matlab kalman_filter. suite of utilities which affects the likelihood LIK results with start>1 (i.e. presampling>0): the calculation speed-up construct which relies on converged covariance matrix lik(t) = lik(t) + reste*log(dF); adds reste * log(dF) to the last-1 (i.e. the smpl) member of lik (the last, the lik(smpl+1) one contains smpl*pp*log(2*pi)) but reste is usually larger than T-start+1 so that LIK =
.5*(sum(lik(start:end))-(start-1)*lik(smpl+1)/smpl)
has much more log(dF)s added than required since they are all concentrated in the last-1 (the T) member For example, if I change the above construct to lik(t) = lik(t) + min(reste,(smpl-start+1))*log(dF); the reported likelihood for presample=40 from Matlab KF is 1640935.5855267849 which is nearly the same as that from C++ KF below: 1640935.5854489324 Shall I make changes to kalman/likelihood/ KFs and upload the .m files? This problem affects also the older versions of DiffuseLikelihood**.m too. Best regards George artilogica@btconnect.com <mailto:artilogica@btconnect.com> <mailto:artilogica@btconnect.com <mailto:artilogica@btconnect.com>> <mailto:artilogica@btconnect.com <mailto:artilogica@btconnect.com> <mailto:artilogica@btconnect.com <mailto:artilogica@btconnect.com>>> ----- Original Message ----- From: "Michel Juillard" <michel.juillard@ens.fr <mailto:michel.juillard@ens.fr> <mailto:michel.juillard@ens.fr <mailto:michel.juillard@ens.fr>> <mailto:michel.juillard@ens.fr <mailto:michel.juillard@ens.fr> <mailto:michel.juillard@ens.fr <mailto:michel.juillard@ens.fr>>>> To: "G. Perendia" <george@perendia.orangehome.co.uk <mailto:george@perendia.orangehome.co.uk> <mailto:george@perendia.orangehome.co.uk <mailto:george@perendia.orangehome.co.uk>> <mailto:george@perendia.orangehome.co.uk <mailto:george@perendia.orangehome.co.uk> <mailto:george@perendia.orangehome.co.uk <mailto:george@perendia.orangehome.co.uk>>>> Sent: Tuesday, May 26, 2009 10:32
AM
Subject: Re: Kalman Filter+PS Hi George, Re 1) below: I modified C++ KF so that it reports log-likelihood for given start/preampling in same/similar manner as the Matlab KFs do and I am getting approximately close results, e.g. ll= -1640935.5854489324 for C++ and (-) 1640482.4179242959 for Matlab KF (for start=41, i.e. presample=40). whilst they appear same for presample=0 (e.g.2.5906e+006), i.e. -2590556.989730841 vs 2590556.989778722 Are those results acceptably close or should I investigate further where the above difference may come form? This indicates a problem . The difference should be the same with and without presample. It may come from the computation of the likelihood constant. This is done in a very obscure manner in Dynare Matlab. _______________________________________________ Dev mailing list Dev@dynare.org <mailto:Dev@dynare.org> <mailto:Dev@dynare.org <mailto:Dev@dynare.org>> <mailto:Dev@dynare.org <mailto:Dev@dynare.org> <mailto:Dev@dynare.org <mailto:Dev@dynare.org>>>
http://www.dynare.org/cgi-bin/mailman/listinfo/dev
-- Stéphane Adjemian CEPREMAP & Université du Maine Tel: (33)1-43-13-62-39
------------------------------------------------------------------------
_______________________________________________ Dev mailing list Dev@dynare.org <mailto:Dev@dynare.org> <mailto:Dev@dynare.org <mailto:Dev@dynare.org>>
http://www.dynare.org/cgi-bin/mailman/listinfo/dev
_______________________________________________
Dev mailing list Dev@dynare.org <mailto:Dev@dynare.org> <mailto:Dev@dynare.org <mailto:Dev@dynare.org>>
http://www.dynare.org/cgi-bin/mailman/listinfo/dev
-- Stéphane Adjemian CEPREMAP & Université du Maine Tel: (33)1-43-13-62-39
------------------------------------------------------------------------
_______________________________________________ Dev mailing list Dev@dynare.org <mailto:Dev@dynare.org>
http://www.dynare.org/cgi-bin/mailman/listinfo/dev
_______________________________________________ Dev mailing list Dev@dynare.org <mailto:Dev@dynare.org> http://www.dynare.org/cgi-bin/mailman/listinfo/dev -- Stéphane Adjemian CEPREMAP & Université du Maine Tel: (33)1-43-13-62-39
------------------------------------------------------------------------
_______________________________________________ Dev mailing list Dev@dynare.org <mailto:Dev@dynare.org> http://www.dynare.org/cgi-bin/mailman/listinfo/dev _______________________________________________ Dev mailing list Dev@dynare.org <mailto:Dev@dynare.org> http://www.dynare.org/cgi-bin/mailman/listinfo/dev -- Stéphane Adjemian CEPREMAP & Université du Maine Tel: (33)1-43-13-62-39
------------------------------------------------------------------------
_______________________________________________ Dev mailing list Dev@dynare.org http://www.dynare.org/cgi-bin/mailman/listinfo/dev
Dev mailing list Dev@dynare.org http://www.dynare.org/cgi-bin/mailman/listinfo/dev
Dev mailing list Dev@dynare.org http://www.dynare.org/cgi-bin/mailman/listinfo/dev
Hi George,
- Shall we then, for start, have only all-in-one driving cc/dll called
kalman_filters.c/dll (i.e rather than emulating 4 or more as in matlab/kalman/likelihood)? It would contain combination of all: univariate and multivariate, non diffuse and diffuse and it is easier to maintain.
It will handle presampling/start like Matlab Dynare and returning full likelihood array for comparing and testing KF results (and as new Dynare matlab KFs do).
For the time being and prototype testing then the full-size Z, H and Pinf matrices will be created by matlab driver file such as kalmandll_test.m
yes, what ever is the simpler from your point of view. My objective is first to build the entire estimation chain for the simple case, without diffuse filter. Don't spend much time writing mex functions interfaces to call individual functions from Matlab, only what is needed to test simple cases. When the entire library is built, we may use the loadlibrary¨ interface rather than mex functions.
- Are we going to cater for missing observation/time-variable state
matrices KFs too?
Only in a second stage.
All the best,
Michel
Best regards
George
----- Original Message ----- From: "Michel Juillard" michel.juillard@ens.fr To: "List for Dynare developers" dev@dynare.org Sent: Wednesday, May 27, 2009 5:51 PM Subject: Re: [DynareDev] Kalman Filter
Dear George,
the aim of the project is to build a whole DLL for estimation, including optimization and Metropolis. Don't loose to much time matching the calling conventions from the exiting *.m files. For example, the mf input arguments looses its utility if we always use the Schur transformation of the transition equation. Calling *.mex functions instead of *.m functions has an overhead cost. So it isn't informative to time a Kalman filter DLL called from a Matlab loop. For the timing exercise to make sense, we would need to code the calling loop inside the DLL.
Best
Michel
G. Perendia wrote:
PS:
Aim is to emulate calling protocol for current matlab/kalman/likelihood .m files.
I am currently adjusting the kalman_filter.cpp dll suite (kalman_filter.cpp to start with) to create internally H and Pinf 0 matrices of suitable size if empty or single 0 passed to them and so that non-diffuse on can take mf instead Z as C++ currently expects.
(The matlab*.cpp files have already been adjusted to return likelihood array as .m files do.)
in meantime one may use .m file to prepare those on the lines of the kalmandll_test.m I just enclosed in the matlab subdirectory of sources/kalman repository.
Best regards
George ----- Original Message -----
*From:* G. Perendia <mailto:george@perendia.orangehome.co.uk> *To:* List for Dynare developers <mailto:dev@dynare.org> *Sent:* Wednesday, May 27, 2009 2:56 PM *Subject:* Re: [DynareDev] Kalman Filter The filter routines there have names and should follow calling rules for the par matlab/kalman/likelihood ones but they do not yet take mf and still expect Z matrix of 1s to map system to observables instead and Pinf must not be empty but at least be initialised to a zeros matrix of Pstar size. The smoother is generic as it was, not suitable for running at all Best regards George ----- Original Message ----- *From:* Stéphane Adjemian <mailto:stephane.adjemian@gmail.com> *To:* List for Dynare developers <mailto:dev@dynare.org> *Sent:* Wednesday, May 27, 2009 2:46 PM *Subject:* Re: [DynareDev] Kalman Filter *Hi George* 2009/5/27 G. Perendia <george@perendia.orangehome.co.uk <mailto:george@perendia.orangehome.co.uk>> Hi The C++ Kalman dll driver routines in /mex/kalman/matlab are still in development *Sure... * and the code there is still subject to developer testing *... But I'd like to play with it.* and the Makefile there is not yet complete but it should use blas/lapack from Matlab libraries. *Ok. I will adapt your Makefile for my platform.** Best, Stéphane.* Best regards George Perendia Tel.: 02072815392 Mob: 07951415480 ----- Original Message ----- *From:* Stéphane Adjemian <mailto:stephane.adjemian@gmail.com> *To:* List for Dynare developers <mailto:dev@dynare.org> *Sent:* Wednesday, May 27, 2009 2:18 PM *Subject:* Re: [DynareDev] Kalman Filter Oui, oui... I never use the presampling option... And with all the examples I have ever considered it takes much more than 10 iterations to get to the steady state kalman filter. By the way, is there somewhere linux a Makefile for the cc kalman routines? Also, why do we need Atlas (if we also use matlab's lapack/blas libraries)? Stéphane. 2009/5/27 Michel Juillard <michel.juillard@ens.fr <mailto:michel.juillard@ens.fr>> Si le filtre converge a l'etat stationnaire a une date avant start (la date a partir de laquelle on cumule la vraisemblance), alors additionner tous les determinants des iterations dans le filtre stationnaire a la derniere periode fausse le calcul de la constante. amicalement Michel Stéphane Adjemian wrote: Thanks Michel. Your commit is ok for me. I do not yet understand the problem raised by George. I need to go through his example... Stéphane. 2009/5/27 Michel Juillard <michel.juillard@ens.fr <mailto:michel.juillard@ens.fr> <mailto:michel.juillard@ens.fr <mailto:michel.juillard@ens.fr>>> Thanks Stephane, I just uploaded a new version of kalman_filter.m Tell me what you think Best Michel Stéphane Adjemian wrote: Hi all, I agree, the matlab code is very unclear (even if I had fun writting it this way ;-) and prone to errors if one uses the vector lik (Marco is using it). I would rather prefer to add the constants outside of the loop with a (sub)vector operation, this should be more efficient. I will do it today or tomorrow. Best, Stéphane. 2009/5/27 Michel Juillard <michel.juillard@ens.fr <mailto:michel.juillard@ens.fr> <mailto:michel.juillard@ens.fr <mailto:michel.juillard@ens.fr>> <mailto:michel.juillard@ens.fr <mailto:michel.juillard@ens.fr> <mailto:michel.juillard@ens.fr <mailto:michel.juillard@ens.fr>>>> On closer inspection, I don't think that the expression pointed by George in kalman_filter.m is wrong: 1. reste = smpl-t or the number of periods during which the filter is stationary. This shouldn't be larger than T-start+1 2. it is problematic (see below) but not wrong to add all the determinants at once in the last period of the stationary filter 3. I don't think this explains the difference with the C++ version of the filter and we still have to look for it. 4. it remains that the current code is very unclear and that if LIK is correct the vector lik doesn't have the correct constants on each elements. 5. I would like to simplify the code and add the correct constant to each element of the lik vector. It would be a little bit less efficient in Matlab than the current code, but I doubt it would be noticeable. Stephane, what do you think? Best Michel G. Perendia wrote: Dear Michel I think I found an error in Dynare Matlab kalman_filter. suite of utilities which affects the likelihood LIK results with start>1 (i.e. presampling>0): the calculation speed-up construct which relies on converged covariance matrix lik(t) = lik(t) + reste*log(dF); adds reste * log(dF) to the last-1 (i.e. the smpl) member of lik (the last, the lik(smpl+1) one contains smpl*pp*log(2*pi)) but reste is usually larger than T-start+1 so that LIK =.5*(sum(lik(start:end))-(start-1)*lik(smpl+1)/smpl)
has much more log(dF)s added than required since they are all concentrated in the last-1 (the T) member For example, if I change the above construct to lik(t) = lik(t) + min(reste,(smpl-start+1))*log(dF); the reported likelihood for presample=40 from Matlab KF is 1640935.5855267849 which is nearly the same as that from C++ KF below: 1640935.5854489324 Shall I make changes to kalman/likelihood/ KFs and upload the .m files? This problem affects also the older versions of DiffuseLikelihood**.m too. Best regards George artilogica@btconnect.com <mailto:artilogica@btconnect.com> <mailto:artilogica@btconnect.com <mailto:artilogica@btconnect.com>> <mailto:artilogica@btconnect.com <mailto:artilogica@btconnect.com> <mailto:artilogica@btconnect.com <mailto:artilogica@btconnect.com>>> ----- Original Message ----- From: "Michel Juillard" <michel.juillard@ens.fr <mailto:michel.juillard@ens.fr> <mailto:michel.juillard@ens.fr <mailto:michel.juillard@ens.fr>> <mailto:michel.juillard@ens.fr <mailto:michel.juillard@ens.fr> <mailto:michel.juillard@ens.fr <mailto:michel.juillard@ens.fr>>>> To: "G. Perendia" <george@perendia.orangehome.co.uk <mailto:george@perendia.orangehome.co.uk> <mailto:george@perendia.orangehome.co.uk <mailto:george@perendia.orangehome.co.uk>> <mailto:george@perendia.orangehome.co.uk <mailto:george@perendia.orangehome.co.uk> <mailto:george@perendia.orangehome.co.uk <mailto:george@perendia.orangehome.co.uk>>>> Sent: Tuesday, May 26, 2009 10:32AM
Subject: Re: Kalman Filter+PS Hi George, Re 1) below: I modified C++ KF so that it reports log-likelihood for given start/preampling in same/similar manner as the Matlab KFs do and I am getting approximately close results, e.g. ll= -1640935.5854489324 for C++ and (-) 1640482.4179242959 for Matlab KF (for start=41, i.e. presample=40). whilst they appear same for presample=0 (e.g.2.5906e+006), i.e. -2590556.989730841 vs 2590556.989778722 Are those results acceptably close or should I investigate further where the above difference may come form? This indicates a problem . The difference should be the same with and without presample. It may come from the computation of the likelihood constant. This is done in a very obscure manner in Dynare Matlab. _______________________________________________ Dev mailing list Dev@dynare.org <mailto:Dev@dynare.org> <mailto:Dev@dynare.org <mailto:Dev@dynare.org>> <mailto:Dev@dynare.org <mailto:Dev@dynare.org> <mailto:Dev@dynare.org <mailto:Dev@dynare.org>>>http://www.dynare.org/cgi-bin/mailman/listinfo/dev
-- Stéphane Adjemian CEPREMAP & Université du Maine Tel: (33)1-43-13-62-39
_______________________________________________ Dev mailing list Dev@dynare.org <mailto:Dev@dynare.org> <mailto:Dev@dynare.org <mailto:Dev@dynare.org>>http://www.dynare.org/cgi-bin/mailman/listinfo/dev
Dev mailing list Dev@dynare.org <mailto:Dev@dynare.org> <mailto:Dev@dynare.org <mailto:Dev@dynare.org>>http://www.dynare.org/cgi-bin/mailman/listinfo/dev
-- Stéphane Adjemian CEPREMAP & Université du Maine Tel: (33)1-43-13-62-39
_______________________________________________ Dev mailing list Dev@dynare.org <mailto:Dev@dynare.org>http://www.dynare.org/cgi-bin/mailman/listinfo/dev
_______________________________________________ Dev mailing list Dev@dynare.org <mailto:Dev@dynare.org> http://www.dynare.org/cgi-bin/mailman/listinfo/dev -- Stéphane Adjemian CEPREMAP & Université du Maine Tel: (33)1-43-13-62-39
_______________________________________________ Dev mailing list Dev@dynare.org <mailto:Dev@dynare.org> http://www.dynare.org/cgi-bin/mailman/listinfo/dev _______________________________________________ Dev mailing list Dev@dynare.org <mailto:Dev@dynare.org> http://www.dynare.org/cgi-bin/mailman/listinfo/dev -- Stéphane Adjemian CEPREMAP & Université du Maine Tel: (33)1-43-13-62-39
_______________________________________________ Dev mailing list Dev@dynare.org http://www.dynare.org/cgi-bin/mailman/listinfo/dev
Dev mailing list Dev@dynare.org http://www.dynare.org/cgi-bin/mailman/listinfo/dev
Dev mailing list Dev@dynare.org http://www.dynare.org/cgi-bin/mailman/listinfo/dev
Dev mailing list Dev@dynare.org http://www.dynare.org/cgi-bin/mailman/listinfo/dev
1) There is a new pair of kalman filter prototype files in the mex/sources/kalman/matlab directory: - kalman_filters.cpp for building a DLL combined of diffuse and non-diffuse, univariate and the standard multivariate, and - its Matlab .m driver kalman_filters.m
However, presampling>0 (start>1) does not yet work properly for the univariate mode!!
2) on the issue of likelihood and presampling, the loglikelihood calculation for cases with presampling should be modified in the other *kalman*.m files of the matlab/kalman/likelihood directory (i.e. diffuse, univariate, etc), e.g. on the lines of the changes that Michel applied to the basic kalman_filter.m too.
Best regards
George
----- Original Message ----- From: "Michel Juillard" michel.juillard@ens.fr To: "List for Dynare developers" dev@dynare.org Sent: Thursday, May 28, 2009 7:48 AM Subject: Re: [DynareDev] Kalman Filter
Hi George,
- Shall we then, for start, have only all-in-one driving cc/dll called
kalman_filters.c/dll (i.e rather than emulating 4 or more as in matlab/kalman/likelihood)? It would contain combination of all:
univariate
and multivariate, non diffuse and diffuse and it is easier to maintain.
It will handle presampling/start like Matlab Dynare and returning full likelihood array for comparing and testing KF results (and as new Dynare matlab KFs do).
For the time being and prototype testing then the full-size Z, H and
Pinf
matrices will be created by matlab driver file such as kalmandll_test.m
yes, what ever is the simpler from your point of view. My objective is first to build the entire estimation chain for the simple case, without diffuse filter. Don't spend much time writing mex functions interfaces to call individual functions from Matlab, only what is needed to test simple cases. When the entire library is built, we may use the loadlibrary¨ interface rather than mex functions.
- Are we going to cater for missing observation/time-variable state
matrices KFs too?
Only in a second stage.
All the best,
Michel
Best regards
George
----- Original Message ----- From: "Michel Juillard" michel.juillard@ens.fr To: "List for Dynare developers" dev@dynare.org Sent: Wednesday, May 27, 2009 5:51 PM Subject: Re: [DynareDev] Kalman Filter
Dear George,
the aim of the project is to build a whole DLL for estimation,
including
optimization and Metropolis. Don't loose to much time matching the calling conventions from the exiting *.m files. For example, the mf input arguments looses its utility if we always use the Schur transformation of the transition equation. Calling *.mex functions instead of *.m functions has an overhead cost. So it isn't informative to time a Kalman filter DLL called from a
Matlab
loop. For the timing exercise to make sense, we would need to code the calling loop inside the DLL.
Best
Michel
G. Perendia wrote:
PS:
Aim is to emulate calling protocol for current matlab/kalman/likelihood .m files.
I am currently adjusting the kalman_filter.cpp dll suite (kalman_filter.cpp to start with) to create internally H and Pinf 0 matrices of suitable size if empty or single 0 passed to them and so that non-diffuse on can take mf instead Z as C++ currently expects.
(The matlab*.cpp files have already been adjusted to return likelihood array as .m files do.)
in meantime one may use .m file to prepare those on the lines of the kalmandll_test.m I just enclosed in the matlab subdirectory of sources/kalman repository.
Best regards
George ----- Original Message -----
*From:* G. Perendia <mailto:george@perendia.orangehome.co.uk> *To:* List for Dynare developers <mailto:dev@dynare.org> *Sent:* Wednesday, May 27, 2009 2:56 PM *Subject:* Re: [DynareDev] Kalman Filter The filter routines there have names and should follow calling rules for the par matlab/kalman/likelihood ones but they do not yet take mf and still expect Z matrix of 1s to map system to observables instead and Pinf must not be empty but at least be initialised to a zeros matrix of Pstar size. The smoother is generic as it was, not suitable for running at all Best regards George ----- Original Message ----- *From:* Stéphane Adjemian <mailto:stephane.adjemian@gmail.com> *To:* List for Dynare developers <mailto:dev@dynare.org> *Sent:* Wednesday, May 27, 2009 2:46 PM *Subject:* Re: [DynareDev] Kalman Filter *Hi George* 2009/5/27 G. Perendia <george@perendia.orangehome.co.uk <mailto:george@perendia.orangehome.co.uk>> Hi The C++ Kalman dll driver routines in /mex/kalman/matlab are still in development *Sure... * and the code there is still subject to developer testing *... But I'd like to play with it.* and the Makefile there is not yet complete but it should use blas/lapack from Matlab libraries. *Ok. I will adapt your Makefile for my platform.** Best, Stéphane.* Best regards George Perendia Tel.: 02072815392 Mob: 07951415480 ----- Original Message ----- *From:* Stéphane Adjemian <mailto:stephane.adjemian@gmail.com> *To:* List for Dynare developers
*Sent:* Wednesday, May 27, 2009 2:18 PM *Subject:* Re: [DynareDev] Kalman Filter Oui, oui... I never use the presampling option... And with all the examples I have ever considered it takes much more than 10 iterations to get to the steady state kalman filter. By the way, is there somewhere linux a Makefile for the cc kalman routines? Also, why do we need Atlas (if we also use matlab's lapack/blas libraries)? Stéphane. 2009/5/27 Michel Juillard <michel.juillard@ens.fr <mailto:michel.juillard@ens.fr>> Si le filtre converge a l'etat stationnaire a une date avant start (la date a partir de laquelle on cumule la vraisemblance), alors additionner tous les determinants des iterations dans le filtre stationnaire a la derniere periode fausse le calcul de la constante. amicalement Michel Stéphane Adjemian wrote: Thanks Michel. Your commit is ok for me. I do not yet understand the problem raised by George. I need to go through his example... Stéphane. 2009/5/27 Michel Juillard <michel.juillard@ens.fr <mailto:michel.juillard@ens.fr> <mailto:michel.juillard@ens.fr <mailto:michel.juillard@ens.fr>>> Thanks Stephane, I just uploaded a new version of kalman_filter.m Tell me what you think Best Michel Stéphane Adjemian wrote: Hi all, I agree, the matlab code is very unclear (even if I had fun writting it this way ;-) and prone to errors if one uses the vector lik (Marco is using it). I would rather prefer to add the constants outside of the loop with a (sub)vector operation, this should be more efficient. I will do it today or tomorrow. Best, Stéphane. 2009/5/27 Michel Juillard <michel.juillard@ens.fr <mailto:michel.juillard@ens.fr> <mailto:michel.juillard@ens.fr <mailto:michel.juillard@ens.fr>> <mailto:michel.juillard@ens.fr <mailto:michel.juillard@ens.fr> <mailto:michel.juillard@ens.fr <mailto:michel.juillard@ens.fr>>>> On closer inspection, I don't think that the expression pointed by George in kalman_filter.m is wrong: 1. reste = smpl-t or the number of periods during which the filter is stationary. This shouldn't be larger than T-start+1 2. it is problematic (see below) but not wrong to add all the determinants at once in the last period of the stationary filter 3. I don't think this explains the difference with the C++ version of the filter and we still have to look for it. 4. it remains that the current code is very unclear and that if LIK is correct the vector lik doesn't have the correct constants on each elements. 5. I would like to simplify the code and add the correct constant to each element of the lik vector. It would be a little bit less efficient in Matlab than the current code, but I doubt it would be noticeable. Stephane, what do you think? Best Michel G. Perendia wrote: Dear Michel I think I found an error in Dynare Matlab kalman_filter. suite of utilities which affects the likelihood LIK results with start>1 (i.e. presampling>0): the calculation speed-up construct which relies on converged covariance matrix lik(t) = lik(t) + reste*log(dF); adds reste * log(dF) to the last-1 (i.e. the smpl) member of lik (the last, the lik(smpl+1) one contains smpl*pp*log(2*pi)) but reste is usually larger than T-start+1 so that LIK =.5*(sum(lik(start:end))-(start-1)*lik(smpl+1)/smpl)
has much more log(dF)s added than required since they are all concentrated in the last-1 (the T) member For example, if I change the above construct to lik(t) = lik(t) + min(reste,(smpl-start+1))*log(dF); the reported likelihood for presample=40 from Matlab KF is 1640935.5855267849 which is nearly the same as that from C++ KF below: 1640935.5854489324 Shall I make changes to kalman/likelihood/ KFs and upload the .m files? This problem affects also the older versions of DiffuseLikelihood**.m too. Best regards George artilogica@btconnect.com <mailto:artilogica@btconnect.com> <mailto:artilogica@btconnect.com <mailto:artilogica@btconnect.com>> <mailto:artilogica@btconnect.com <mailto:artilogica@btconnect.com> <mailto:artilogica@btconnect.com <mailto:artilogica@btconnect.com>>> ----- Original Message ----- From: "Michel Juillard" <michel.juillard@ens.fr <mailto:michel.juillard@ens.fr> <mailto:michel.juillard@ens.fr <mailto:michel.juillard@ens.fr>> <mailto:michel.juillard@ens.fr <mailto:michel.juillard@ens.fr> <mailto:michel.juillard@ens.fr <mailto:michel.juillard@ens.fr>>>> To: "G. Perendia" <george@perendia.orangehome.co.uk <mailto:george@perendia.orangehome.co.uk> <mailto:george@perendia.orangehome.co.uk <mailto:george@perendia.orangehome.co.uk>> <mailto:george@perendia.orangehome.co.uk <mailto:george@perendia.orangehome.co.uk> <mailto:george@perendia.orangehome.co.uk <mailto:george@perendia.orangehome.co.uk>>>> Sent: Tuesday, May 26, 2009
10:32
AM
Subject: Re: Kalman Filter+PS Hi George, Re 1) below: I modified C++ KF so that it reports log-likelihood for given start/preampling in same/similar manner as the Matlab KFs do and I am getting approximately close results, e.g. ll= -1640935.5854489324 for C++ and (-) 1640482.4179242959 for Matlab KF (for start=41, i.e. presample=40). whilst they appear same for presample=0 (e.g.2.5906e+006), i.e. -2590556.989730841 vs 2590556.989778722 Are those results acceptably close or should I investigate further
where
the above difference may come form? This indicates a problem . The difference should be the same with and without presample. It may come from the computation of the likelihood constant. This is done in a very obscure manner in Dynare Matlab.
_______________________________________________
Dev mailing list Dev@dynare.org <mailto:Dev@dynare.org> <mailto:Dev@dynare.org <mailto:Dev@dynare.org>> <mailto:Dev@dynare.org <mailto:Dev@dynare.org> <mailto:Dev@dynare.org <mailto:Dev@dynare.org>>>http://www.dynare.org/cgi-bin/mailman/listinfo/dev
-- Stéphane Adjemian CEPREMAP & Université du Maine Tel: (33)1-43-13-62-39
------------------------------------------------------------------------
_______________________________________________
Dev mailing list Dev@dynare.org <mailto:Dev@dynare.org> <mailto:Dev@dynare.org
http://www.dynare.org/cgi-bin/mailman/listinfo/dev
Dev mailing list Dev@dynare.org <mailto:Dev@dynare.org> <mailto:Dev@dynare.org
http://www.dynare.org/cgi-bin/mailman/listinfo/dev
-- Stéphane Adjemian CEPREMAP & Université du Maine Tel: (33)1-43-13-62-39
------------------------------------------------------------------------
_______________________________________________
Dev mailing list Dev@dynare.org <mailto:Dev@dynare.org>http://www.dynare.org/cgi-bin/mailman/listinfo/dev
_______________________________________________ Dev mailing list Dev@dynare.org <mailto:Dev@dynare.org> http://www.dynare.org/cgi-bin/mailman/listinfo/dev -- Stéphane Adjemian CEPREMAP & Université du Maine Tel: (33)1-43-13-62-39
------------------------------------------------------------------------
_______________________________________________ Dev mailing list Dev@dynare.org <mailto:Dev@dynare.org> http://www.dynare.org/cgi-bin/mailman/listinfo/dev _______________________________________________ Dev mailing list Dev@dynare.org <mailto:Dev@dynare.org> http://www.dynare.org/cgi-bin/mailman/listinfo/dev -- Stéphane Adjemian CEPREMAP & Université du Maine Tel: (33)1-43-13-62-39
------------------------------------------------------------------------
_______________________________________________ Dev mailing list Dev@dynare.org http://www.dynare.org/cgi-bin/mailman/listinfo/dev
Dev mailing list Dev@dynare.org http://www.dynare.org/cgi-bin/mailman/listinfo/dev
Dev mailing list Dev@dynare.org http://www.dynare.org/cgi-bin/mailman/listinfo/dev
Dev mailing list Dev@dynare.org http://www.dynare.org/cgi-bin/mailman/listinfo/dev
Dev mailing list Dev@dynare.org http://www.dynare.org/cgi-bin/mailman/listinfo/dev
-
G. Perendia -
Michel Juillard