Inference for adaptive time series models: stochastic volatility and conditionally Gaussian state space form

In this paper we model the Gaussian errors in the standard Gaussian linear state space model as stochastic volatility processes. We show that conventional MCMC algorithms for this class of models are ineffective, but that the problem can be alleviated by reparameterizing the model. Instead of sampli...

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Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς:	Bos, C, Shephard, N
Μορφή:	Journal article
Γλώσσα:	English
Έκδοση:	Taylor and Francis 2006
Θέματα:	Econometrics Economics

Inference for Adaptive Time Series Models: Stochastic Volatility and Conditionally Gaussian State Space Form. ανά Bos, C, Shephard, N

Έκδοση 2006

Journal article

Inference for Adaptive Time Series Models: Stochastic Volatility and Conditionally Gaussian State Space Form. ανά Bos, C, Shephard, N

Έκδοση 2004

Working paper

Inference for adaptive time series models: stochastic volatility and conditionally Gaussian state space form

Inference for Adaptive Time Series Models: Stochastic Volatility and Conditionally Gaussian State Space Form. ανά Bos, C, Shephard, N

Inference for Adaptive Time Series Models: Stochastic Volatility and Conditionally Gaussian State Space Form. ανά Bos, C, Shephard, N

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