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Is there a way to restrict level/trend variance at certain value in unobserved components model in python?


Class Design: Calculating statistics from weighted valuesR function for Dynamic Ordinary Least Squares regressionGetting the math right for a Hidden Markov Model in Java













0












$begingroup$


I am building an unobserved component model using 'lltrend' method.



from statsmodels.tsa.statespace.structural import UnobservedComponents

ucm_model = UnobservedComponents(endog,exog=exog,level='lltrend',mle_regression=True)
result = ucm_model.fit()
print(result.summary())


Now, I want to restrict the level and trend variance at a certain range to make the series smoother and avoid overfitting. The method 'strend' does a similar job by setting the trend variance at zero. Is there a way I can specify and set the level/trend variance to a different value (other than zero)?









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$endgroup$
















    0












    $begingroup$


    I am building an unobserved component model using 'lltrend' method.



    from statsmodels.tsa.statespace.structural import UnobservedComponents

    ucm_model = UnobservedComponents(endog,exog=exog,level='lltrend',mle_regression=True)
    result = ucm_model.fit()
    print(result.summary())


    Now, I want to restrict the level and trend variance at a certain range to make the series smoother and avoid overfitting. The method 'strend' does a similar job by setting the trend variance at zero. Is there a way I can specify and set the level/trend variance to a different value (other than zero)?









    share







    New contributor




    Subhajyoti Sen is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
    Check out our Code of Conduct.







    $endgroup$














      0












      0








      0





      $begingroup$


      I am building an unobserved component model using 'lltrend' method.



      from statsmodels.tsa.statespace.structural import UnobservedComponents

      ucm_model = UnobservedComponents(endog,exog=exog,level='lltrend',mle_regression=True)
      result = ucm_model.fit()
      print(result.summary())


      Now, I want to restrict the level and trend variance at a certain range to make the series smoother and avoid overfitting. The method 'strend' does a similar job by setting the trend variance at zero. Is there a way I can specify and set the level/trend variance to a different value (other than zero)?









      share







      New contributor




      Subhajyoti Sen is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.







      $endgroup$




      I am building an unobserved component model using 'lltrend' method.



      from statsmodels.tsa.statespace.structural import UnobservedComponents

      ucm_model = UnobservedComponents(endog,exog=exog,level='lltrend',mle_regression=True)
      result = ucm_model.fit()
      print(result.summary())


      Now, I want to restrict the level and trend variance at a certain range to make the series smoother and avoid overfitting. The method 'strend' does a similar job by setting the trend variance at zero. Is there a way I can specify and set the level/trend variance to a different value (other than zero)?







      statistics





      share







      New contributor




      Subhajyoti Sen is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.










      share







      New contributor




      Subhajyoti Sen is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.








      share



      share






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      Subhajyoti Sen is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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      asked 6 mins ago









      Subhajyoti SenSubhajyoti Sen

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      New contributor





      Subhajyoti Sen is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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