Bayesian Inference for the Mover-Stayer Model of Continuous Time

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Bayesian Inference for the Mover-Stayer Model of Continuous Time

Author Info

Fougere, D.
Kamionka, T.

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Denis Fougere

Abstract

This paper presents bayesian inference procedures for the continuous time mover-stayer model applied to individual transition data collected in discrete time. In particular, these methods allow to derive the probability of embeddability of the discrete-time modelling with the continuous-time one. A special emphasis is put on two alternative procedures, namely the importance of sampling and Gibbs sampling algorithms.

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Paper provided by Toulouse - GREMAQ in its series Papers with number 98.b.

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Length: 36 pages
Date of creation: 1998
Date of revision:
Handle: RePEc:fth:gremaq:98.b

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Paper
- Fougere, D. & Kamionka, T., 1992. "Bayesian Inference for the Mover-Stayer Model in Continuous-Time," Papers 92.285, Toulouse - GREMAQ.

Find related papers by JEL classification:
C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - General
C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Bayesian Analysis
C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General

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