[Scilab-users] Grocer: Estimation of a Sequence of States

Eric Dubois grocer.toolbox at gmail.com
Wed Apr 1 21:54:20 CEST 2015


Hi Deb.

I am not sure to understand:
- the output from ms_var, a results tlist, contains field 'smoothed probs'
and 'filteed probs' that provides the (smoothed and filtered) probabilities
of the corresponding states on the estimation period;
- the output from ms_var_oos provides the same results, but on any period
(in or out of sample).

Isn't it what you search?

Éric.

2015-04-01 19:05 GMT+02:00 dnayak <dnayak at ncsu.edu>:

> Hi Eric,
>
> Thanks for the information. However, after going through the function
> ms_var_oos, I feel it runs the Markov-switching VAR model estimated over
> one period of time on another period and compares the results.
>
> However, I need a function that will estimate for me the sequence of
> regimes/states that the data goes through. So, what I need is to first
> estimate the parameters for the Markov-switching VAR model, i.e. train the
> model on a time-series data set X and then use the same parameters to
> estimate the regimes that every instant of X falls into. For example, it
> should give me something like - 1. Data for time instant 1 falls in Regime
> 2; 2. Data for time instant 2 falls in Regime 4; and so on.
>
> Can Grocer do that?
>
> Thanks,
> Deb
>
> On Mon, Mar 30, 2015 at 12:57 PM, Eric Dubois [via Scilab / Xcos - Mailing
> Lists Archives] <[hidden email]
> <http:///user/SendEmail.jtp?type=node&node=4032031&i=0>> wrote:
>
>> Hello.
>>
>> The function ms_var_oos that has been introduced in Grocer 1.66 is
>> probably what you need.
>>
>> See help ms_var_oos for a description of the function.
>>
>> Eric
>> Le 30 mars 2015 17:30, "dnayak" <[hidden email]
>> <http:///user/SendEmail.jtp?type=node&node=4031999&i=0>> a écrit :
>>
>>> Hi,
>>>
>>> I have been using Grocer for some time now for the estimation of HMM-VAR
>>> parameters. However, I have a different problem now.
>>>
>>> Suppose, I have estimated the parameters of an HMM-VAR. Now, I want to
>>> use
>>> those parameters to estimate the sequence of states in a given
>>> time-series
>>> data. This may or may not be the data used to obtain the parameters.
>>>
>>> Is there any function, that is able to do that?
>>>
>>> Thanks,
>>> Deb
>>>
>>>
>>>
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