On some properties of Markov chain Monte Carlo simulation methods based on the particle filter

Journal of Econometrics

Volumn 171, Issue 2, 2012, Pages 134-151

  Pitt, Michael K ^a   Silva, Ralph Dos Santos ^b   Giordani, Paolo ^c   Kohn, Robert ^d  

^a UNIVERSITY OF WARWICK   (United Kingdom)

^b FEDERAL UNIVERSITY OF RIO DE JANEIRO   (Brazil)

^c SVERIGES RIKSBANK   (Sweden)

^d UNIVERSITY OF NEW SOUTH WALES   (Australia)

Author keywords

Adapted filtering; Auxiliary variables; Bayesian inference; Simulated likelihood

Indexed keywords

AUXILIARY PARTICLE FILTER; AUXILIARY VARIABLES; BAYESIAN INFERENCE; COMPUTING TIME; CRITICAL ISSUES; FINITE NUMBER; MARKOV CHAIN MONTE CARLO; MARKOV CHAIN MONTE CARLO SIMULATION; MODEL PARAMETERS; OPTIMAL NUMBER; PARTICLE FILTER; POSTERIOR DISTRIBUTIONS; PRACTICAL GUIDELINES; SIMULATED LIKELIHOOD;

BAYESIAN NETWORKS; INFERENCE ENGINES; SIGNAL FILTERING AND PREDICTION; TARGET TRACKING;

MONTE CARLO METHODS;

EID: 84868208864     PISSN: 03044076     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jeconom.2012.06.004     Document Type: Conference Paper

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