Prediction, Filtering, and Smoothing in Nonlinear and Nonnormal Cases Using Monte-Carlo Integration
A simulation-based non-linear filter is developed for prediction and smoothing in non-linear and/or nonnormal structural time-series models. Recursive algorithms of weighting functions are derived by applying Monte Carlo integration. Through Monte Carlo experiments, it is shown that (1) for a small...
محفوظ في:
المؤلفون الرئيسيون: | Tanizaki, Hisashi, Mariano, Roberto S. |
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التنسيق: | text |
اللغة: | English |
منشور في: |
Institutional Knowledge at Singapore Management University
1994
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الموضوعات: | |
الوصول للمادة أونلاين: | https://ink.library.smu.edu.sg/soe_research/373 https://ink.library.smu.edu.sg/context/soe_research/article/1372/viewcontent/Prediction_Filter_NL_JAE_pv_94.pdf |
الوسوم: |
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المؤسسة: | Singapore Management University |
اللغة: | English |
مواد مشابهة
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Prediction, Filtering, and Smoothing in Nonlinear and Nonnormal Cases Using Monte-Carlo Integration
بواسطة: Mariano, Roberto S., وآخرون
منشور في: (1994) -
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منشور في: (1998) -
Nonlinear filters based on Taylor series expansions
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منشور في: (2007) -
Simulation-Based Inference in Nonlinear State-Space Models: Application to Testing the Permanent Income Hypothesis
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منشور في: (2000) -
Prediction of Final Data with Use of Preliminary and/or Revised Data
بواسطة: Mariano, Roberto S., وآخرون
منشور في: (1995)