M Pitt
M Pitt
Bestätigte E-Mail-Adresse bei kcl.ac.uk - Startseite
Zitiert von
Zitiert von
Filtering via simulation: auxiliary particle filters
MK Pitt, N Shephard
Journal of the American Statistical Association 94 (446), 590-599, 1999
Likelihood analysis of non-Gaussian measurement time series
N Shephard, MK Pitt
Biometrika 84 (3), 653-667, 1997
On some properties of Markov chain Monte Carlo simulation methods based on the particle filter
MK Pitt, RS Silva, P Giordani, R Kohn
Journal of Econometrics 171 (2), 134–151, 2012
Particle filters for continuous likelihood evaluation and maximisation
S Malik, MK Pitt
Journal of Econometrics 165 (2), 190–209, 2011
Efficient Bayesian inference for Gaussian copula regression models
M Pitt, D Chan, R Kohn
Biometrika 93 (3), 537-554, 2006
Efficient implementation of Markov chain Monte Carlo when using an unbiased likelihood estimator
A Doucet, M Pitt, G Deligiannidis, R Kohn
Biometrika 102 (2), 295–313, 2015
Time varying covariances: a factor stochastic volatility approach
M Pitt, N Shephard
Bayesian statistics 6, 547-570, 1999
Auxiliary variable based particle filters
MK Pitt, N Shephard
Sequential Monte Carlo methods in practice, 273-293, 2001
The correlated pseudo-marginal method
G Deligiannidis, A Doucet, MK Pitt
Journal of the Royal Statistical Society, Series B, 2018
Likelihood based inference for diffusion driven models.
S Chib, MK Pitt, N Shephard
Analytic convergence rates and parameterization issues for the Gibbs sampler applied to state space models
MK Pitt, N Shephard
Journal of Time Series Analysis 20 (1), 63-85, 1999
Trade union decline and the distribution of wages in the UK: evidence from kernel density estimation
BD Bell, MK Pitt
Oxford Bulletin of Economics and Statistics 60 (4), 509-528, 1998
Constructing first order stationary autoregressive models via latent processes
MK Pitt, C Chatfield, SG Walker
Scandinavian Journal of Statistics 29 (4), 657-663, 2002
Constructing stationary time series models using auxiliary variables with applications
MK Pitt, SG Walker
Journal of the American Statistical Association 100 (470), 554-564, 2005
Importance sampling squared for Bayesian inference in latent variable models
MN Tran, M Scharth, MK Pitt, R Kohn
arXiv preprint arXiv:1309.3339, 2013
Simulated likelihood inference for stochastic volatility models using continuous particle filtering
MK Pitt, S Malik, A Doucet
Annals of the Institute of Statistical Mathematics 66 (3), 527-552, 2014
Bayesian inference for time series state space models
P Giordani, M Pitt, R Kohn
The Oxford Handbook of Bayesian Econometrics, 2011
Bayesian inference for nonlinear structural time series models
J Hall, MK Pitt, R Kohn
Journal of Econometrics 179 (2), 99-111, 2014
Adaptive Metropolis-Hastings Sampling using Reversible Dependent Mixture Proposals
MN Tran, MK Pitt, R Kohn
Statistics and Computing 26 (1-2), 361-381, 2016
Copula-type Estimators for Flexible Multivariate Density Modeling using Mixtures
MN Tran, P Giordani, X Mun, R Kohn, MK Pitt
Journal of Computational and Graphical Statistics 23 (4), 2014
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