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- W3121231293 abstract "This paper presents Bayesian inference procedures for the continuous time mover-stayer model applied to labour market transition data collected in discrete time. These methods allow us 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 sampling algorithm and a new Gibbs sampling algorithm. Transition intensities, proportions of stayers and functions of these parameters are then estimated with the Gibbs sampling algorithm for individual transition data coming from the French Labour Force Surveys collected over the period 1986-2000. Copyright © 2003 John Wiley & Sons, Ltd. (This abstract was borrowed from another version of this item.)" @default.
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- W3121231293 date "2002-01-01" @default.
- W3121231293 modified "2023-10-02" @default.
- W3121231293 title "Bayesian Inference for the Mover-Stayer Model in Continuous Time with an Application to Labour Market Transition Data" @default.
- W3121231293 hasPublicationYear "2002" @default.
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