Bayesian inference based only on simulated likelihood: particle filter analysis of dynamic economic models.
Suppose we wish to carry out likelihood based inference but we solely have an unbiased simulation based estimator of the likelihood. We note that unbiasedness is enough when the estimated likelihood is used inside a Metropolis-Hastings algorithm. This result has recently been introduced in statistic...
Hoofdauteurs: | Flury, T, Shephard, N |
---|---|
Formaat: | Journal article |
Taal: | English |
Gepubliceerd in: |
Cambridge University Press
2011
|
Gelijkaardige items
-
Bayesian inference based only on simulated likelihood: particle filter analysis of dynamic economic models.
door: Flury, T, et al.
Gepubliceerd in: (2008) -
Learning and filtering via simulation: smoothly jittered particle filters.
door: Flury, T, et al.
Gepubliceerd in: (2009) -
Learning and filtering via simulation: smoothly jittered particle filters
door: Shephard, N, et al.
Gepubliceerd in: (2009) -
Simulated likelihood inference for stochastic volatility models using continuous particle filtering
door: Pitt, M, et al.
Gepubliceerd in: (2014) -
Simulated likelihood inference for stochastic volatility models using continuous particle filtering
door: Pitt, M, et al.
Gepubliceerd in: (2014)