The scan sampler for time series models

Piet De Jong

The scan sampler for time series models

Piet De Jong^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

7 Citations (Scopus)

Abstract

An algorithm, called the scan sampler, is developed and discussed. The scan sampler has a variety of uses for time series analysis based on the state space model with nonGaussian observations. The algorithm is based on the Kaiman filter/smoothing algorithm. It can be used for Bayesian inference using Markov chain Monte Carlo and to find posterior modes.

Original language	English
Pages (from-to)	929-937
Number of pages	9
Journal	Biometrika
Volume	84
Issue number	4
Publication status	Published - 1997
Externally published	Yes

Keywords

Exponential family
Generalised linear time series
Gibbs sampling
Kaiman filter
Markov chain monte carlo
Nonparametric regression
Smoothing filter
State space model
Stochastic volatility
Tobit models

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title = "The scan sampler for time series models",

abstract = "An algorithm, called the scan sampler, is developed and discussed. The scan sampler has a variety of uses for time series analysis based on the state space model with nonGaussian observations. The algorithm is based on the Kaiman filter/smoothing algorithm. It can be used for Bayesian inference using Markov chain Monte Carlo and to find posterior modes.",

keywords = "Exponential family, Generalised linear time series, Gibbs sampling, Kaiman filter, Markov chain monte carlo, Nonparametric regression, Smoothing filter, State space model, Stochastic volatility, Tobit models",

author = "{De Jong}, Piet",

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AB - An algorithm, called the scan sampler, is developed and discussed. The scan sampler has a variety of uses for time series analysis based on the state space model with nonGaussian observations. The algorithm is based on the Kaiman filter/smoothing algorithm. It can be used for Bayesian inference using Markov chain Monte Carlo and to find posterior modes.

KW - Exponential family

KW - Generalised linear time series

KW - Gibbs sampling

KW - Kaiman filter

KW - Markov chain monte carlo

KW - Nonparametric regression

KW - Smoothing filter

KW - State space model

KW - Stochastic volatility

KW - Tobit models

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JO - Biometrika

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