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- W2511883346 abstract "Bayesian analysis of threshold autoregressive (TAR) model with various possible thresholds is considered. A method of Bayesian stochastic search selection is introduced to identify a threshold-dependent sequence with highest probability. All model parameters are computed by a hybrid Markov chain Monte Carlo method, which combines Metropolis–Hastings algorithm and Gibbs sampler. The main innovation of the method introduced here is to estimate the TAR model without assuming the fixed number of threshold values, thus is more flexible and useful. Simulation experiments and a real data example lend further support to the proposed approach." @default.
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- W2511883346 date "2016-08-09" @default.
- W2511883346 modified "2023-09-23" @default.
- W2511883346 title "Bayesian analysis of multiple thresholds autoregressive model" @default.
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- W2511883346 doi "https://doi.org/10.1007/s00180-016-0673-3" @default.
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