We deal with Bayesian model selection for beta autoregressive processes. We discuss the choice of parameter and model priors with possible parameter restrictions and suggest a Reversible Jump Markov-Chain Monte Carlo (RJMCMC) procedure based on a Metropolis-Hastings within Gibbs algorithm
We propose a new class of Markov-switching models useful for business cycle analysis, with transitio...
We propose a new class of Markov-switching models useful for business cycle analysis, with transitio...
We propose a new class of Markov-switching models useful for business cycle analysis, with transitio...
We deal with Bayesian model selection for beta autoregressive processes. We discuss the choice of pa...
We deal with Bayesian model selection for beta autoregressive processes. We discuss the choice of pa...
We deal with Bayesian model selection for beta autoregressive processes. We discuss the choice of pa...
We deal with Bayesian inference for Beta autoregressive processes. We restrict our attention to the ...
An approach to Bayesian model selection in self-exciting threshold autoregressive (SETAR) models is ...
Abstract. An approach to Bayesian model selection in self-exciting threshold autoregressive (SETAR) ...
A Markov chain Monte Carlo (MCMC) approach, called a reversible jump MCMC, is employed in model sele...
Various model selection criteria such as Akaike information criterion (AIC; Akaike, 1973), Bayesian ...
The aim of this paper is to demonstrate the potential of the Reversible Jump Markov Chain Monte Carl...
We propose a new class of Markov-switching models useful for business cycle analysis, with transitio...
We propose a new class of Markov-switching models useful for business cycle analysis, with transitio...
We propose a new class of Markov-switching models useful for business cycle analysis, with transitio...
We propose a new class of Markov-switching models useful for business cycle analysis, with transitio...
We propose a new class of Markov-switching models useful for business cycle analysis, with transitio...
We propose a new class of Markov-switching models useful for business cycle analysis, with transitio...
We deal with Bayesian model selection for beta autoregressive processes. We discuss the choice of pa...
We deal with Bayesian model selection for beta autoregressive processes. We discuss the choice of pa...
We deal with Bayesian model selection for beta autoregressive processes. We discuss the choice of pa...
We deal with Bayesian inference for Beta autoregressive processes. We restrict our attention to the ...
An approach to Bayesian model selection in self-exciting threshold autoregressive (SETAR) models is ...
Abstract. An approach to Bayesian model selection in self-exciting threshold autoregressive (SETAR) ...
A Markov chain Monte Carlo (MCMC) approach, called a reversible jump MCMC, is employed in model sele...
Various model selection criteria such as Akaike information criterion (AIC; Akaike, 1973), Bayesian ...
The aim of this paper is to demonstrate the potential of the Reversible Jump Markov Chain Monte Carl...
We propose a new class of Markov-switching models useful for business cycle analysis, with transitio...
We propose a new class of Markov-switching models useful for business cycle analysis, with transitio...
We propose a new class of Markov-switching models useful for business cycle analysis, with transitio...
We propose a new class of Markov-switching models useful for business cycle analysis, with transitio...
We propose a new class of Markov-switching models useful for business cycle analysis, with transitio...
We propose a new class of Markov-switching models useful for business cycle analysis, with transitio...
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