1 citations · 1 across the 1 of their papers we have counts for
5 papers
Censored Regression with Serially Correlated Errors: a Bayesian approach
Rodney Sousa, Isabel Pereira, Maria Eduarda Silva +1
The problem of estimating censored linear regression models with autocorrelated errors arises in many environmental and social studies. The present work proposes a Bayesian approac…
Forecasting observables with particle filters: Any filter will do!
Patrick Leung, Catherine S. Forbes, Gael M. Martin +1
We investigate the impact of filter choice on forecast accuracy in state space models. The filters are used both to estimate the posterior distribution of the parameters, via a par…
Approximate Bayesian Forecasting
David T. Frazier, Worapree Maneesoonthorn, Gael M. Martin +1
Approximate Bayesian Computation (ABC) has become increasingly prominent as a method for conducting parameter inference in a range of challenging statistical problems, most notably…
Auxiliary Likelihood-Based Approximate Bayesian Computation in State Space Models
Gael M. Martin, Brendan P. M. McCabe, David T. Frazier +2
A computationally simple approach to inference in state space models is proposed, using approximate Bayesian computation (ABC). ABC avoids evaluation of an intractable likelihood b…
Approximate Bayesian Computation in State Space Models
Gael M. Martin, Brendan P. M. McCabe, Worapree Maneesoonthorn +1
A new approach to inference in state space models is proposed, based on approximate Bayesian computation (ABC). ABC avoids evaluation of the likelihood function by matching observe…