Estimation in Non-Linear Non-Gaussian State Space Models with Precision-Based Methods
نویسندگان
چکیده
منابع مشابه
Efficient Simulation and Integrated Likelihood Estimation in Non-Linear Non-Gaussian State Space Models
We propose a generic approach to inference in the non-linear, non-Gaussian state space model. This approach builds on recent developments in precision-based algorithms to estimating general state space models with multivariate observations and states. The baseline algorithm approximates the conditional distribution of the states by a multivariate t density, which is then used for integrated lik...
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15 صفحه اولA General Linear Non-Gaussian State-Space Model
State-space modeling provides a powerful tool for system identification and prediction. In linear state-space models the data are usually assumed to be Gaussian and the models have certain structural constraints such that they are identifiable. In this paper we propose a non-Gaussian state-space model which does not have such constraints. We prove that this model is fully identifiable. We then ...
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ژورنال
عنوان ژورنال: SSRN Electronic Journal
سال: 2012
ISSN: 1556-5068
DOI: 10.2139/ssrn.2025754