Dear Brian
1) For me it works fine; I suspect that you have run ms_var with your data
after having run with the manual example. I expect that if you reopen
Scialb and run your problem, starting from load('arhmm_example.dat'), it
will work. A good advice anyway is to set the bounds before each estimation
or to run:
--> bounds()
if you want to use the greatest available time span with your data
2) I agree; indeed the example in the manual as well as yours are
univariate, but ms_var also works with multivariate series (I have run some
tests which worked well)
3) If you want to contribute, do not hesitate to send me code (at
[email protected] or [email protected]); add your copyright; if
you can create a help file it would still be better (I have some tools do
help doing that if you want them); and if you can add to the manual, it
would be marvellous!
If you want to imporve the docs you are also welcome; I can sned you the
OpenOffice files you need if you find it suitable
Éric.
2014-05-23 14:13 GMT+02:00 Brian Bouterse <[email protected]>:
> Thanks for the reply Eric. It is great to get hints and suggestions from
> the author directly!
>
> I used the commands that you outlined, and they were able to reproduce the
> expected output verbatim, which is great. Thanks for clearing that up for
> me. I've gotten further towards my goal.
>
> I've now got three questions:
>
> 1) I get an unexpected result when I run ms_var() on my own data. I run
> these commands:
>
> load('arhmm_example.dat')
> nb_states=2
> switch_var=2 // variances are switching
> var_opt=3 // unrestricted var-cov matrix
>
> r=ms_var('cte',3,'ardata',nb_states,switch_var,var_opt,'prt=initial;final','opt_convg=0')
>
> I receive this output:
>
> WARNING: in overlay, series number 2 has been ignored because of a bad
> frequency
> !--error 10000
> series ends before the end date of the bounds
> at line 39 of function ts2vec0 called by :
> at line 101 of function explone called by :
> at line 253 of function ms_var called by :
>
> r=ms_var('cte',3,'ardata',nb_states,switch_var,var_opt,'prt=initial;final','opt_convg=0')
>
> The arhmm_example.dat file is available here[0], and it was made by
> running.the following command on the original csv[1] file arhmm_example.csv.
>
> impexc2bd('arhmm_example.csv', ';', 'arhmm_example.dat')
>
> I believe I either don't have the dates configured correctly, or it
> requires a specific number of data points to match the frequency value,
> which also may be wrong. Do you have some insight into this error message?
> I've been reading the docs on the ts structure, and I will continue to try
> to solve this roadblock.
>
>
> 2) My goal in doing all this is to analyze Autoregressive Hidden Markov
> Models. As I understand it, the VAR-HMM that ms_var provides is a
> multivariate case of an Autoregressive Hidden Markov Model. The terms
> Markov Switching Model, and Hidden Markov Model refer to the same thing.
> Using a single variable with ms_var() as I show above in the example, will
> simulate an AR-HMM(3). I would like to check if these statements agree with
> your understanding.
>
>
> 3) How could I contribute to the grocer code. At the very least I could
> improve the docs some.
>
>
> [0]:
> https://s3.amazonaws.com/dfsklfdsklfds/fdsjkfsdjkfds/arhmm_example.dat
> [1]:
> https://s3.amazonaws.com/dfsklfdsklfds/fdsjkfsdjkfds/arhmm_example.csv
>
> Thanks,
> Brian
>
>
> On Tue, May 20, 2014 at 3:55 PM, Eric Dubois <[email protected]>wrote:
>
>> Hello Brian
>>
>> Sorry for this late answer, but I have been quite busy these days.
>>
>> I did not notice the problem with this version of the MS programs. Indeed
>> I have changed the optimization device of all GROCER programs and I have
>> not adapted the defaults for the MS programs.
>>
>> If you run:
>> --> global GROCERDIR;
>> --> load(GROCERDIR+'\data\us_revu.dat')
>> --> bounds('1967m4','2004m2')
>>
>> --> nb_states=2
>> --> switch_var=2 // variances are switching
>> --> var_opt=3 // unrestricted var-cov matrix
>>
>> -->
>> r=ms_var('cte',3,'100*(log(us_revu)-lagts(2,log(us_revu)))',nb_states,switch_var,var_opt,'prt=initial;final','opt_convg=0')
>> (see chapter 6 of the manual for explanations)
>>
>> Then the results of the ms_var demo is restaured.
>>
>> I will change the default in Grocer next version .
>>
>> Regards.
>>
>> Éric.
>>
>>
>> 2014-05-19 12:56 GMT+02:00 Brian Bouterse <[email protected]>:
>>
>>> Hi Scilab community!
>>>
>>> I'm new to Scilab, and the AR-HMM and VAR-HMM solving capabilities of
>>> GROCER are what interest me.
>>>
>>> I have a question relating to Chapter 23 from the GROCER manual[0].
>>> This is the univariate MS-AR(3) solved using the function ms_reg_d() on
>>> the us_revu.dat data included with GROCER. I have made no adjustment from
>>> the example statements in Chapter 23.
>>>
>>> The example output is shown on pages 4 and 5 of the Chapter 23 module.
>>> Compare that against the output I receive.
>>>
>>> http://fpaste.org/102978/14004958/
>>>
>>> Here are my questions:
>>>
>>> 1. The numerical output is completely different. I expected it to be
>>> the same since the data is provided by GROCER, and I've done the example
>>> exactly as shown in Chapter 23. Is there some explanation to why the
>>> solved solution I receive is different than the example output in the
>>> chapter?
>>>
>>> 2. I see output like %i*8.4469016 which seems like an error because %i
>>> looks like a variable that yet needs to be replaced, and then multiplied to
>>> get to its final value. Is this some kind of bug or error?
>>>
>>> Thanks for any help the community can provide. We'll be using this for
>>> a seminar on HMM, AR-HMM, and VAR-HMM at North Carolina State University.
>>> I'm also a developer, so I really appreciate all the effort that has been
>>> put into scilab and GROCER.
>>>
>>> Thanks,
>>> Brian
>>>
>>>
>>> [0]: http://dubois.ensae.net/Grocer_manual_v1.6.zip
>>>
>>>
>>> --
>>> Brian Bouterse
>>>
>>> _______________________________________________
>>> users mailing list
>>> [email protected]
>>> http://lists.scilab.org/mailman/listinfo/users
>>>
>>>
>>
>> _______________________________________________
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>>
>
>
> --
> Brian Bouterse
>
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