Tran , Minh-Ngoc, Pitt, Michael K. and Kohn, Robert V. (2016) Adaptive metropolis-Hastings sampling using reversible dependent mixture proposals. Statistics and Computing, 26 . pp. 361-381. doi:10.1007/s11222-014-9509-6 ISSN 0960-3174.

Doucet, A., Pitt, Michael K., Deligiannidis, G. and Kohn, R. (2015) Efficient implementation of Markov chain Monte Carlo when using an unbiased likelihood estimator. Biometrika, 102 (2). pp. 295-313. doi:10.1093/biomet/asu075 ISSN 0006-3444.

Tran, Minh-Ngoc, Giordani, Paolo, Mun, Xiuyan, Kohn, Robert and Pitt, Michael K. (2014) Copula-type estimators for flexible multivariate density modeling using mixtures. Journal of Computational and Graphical Statistics, Volume 23 (Number 4). pp. 1163-1178. doi:10.1080/10618600.2013.842918 ISSN 1061-8600.

Azam, Kazim and Pitt, Michael K. (2014) Bayesian inference for a semi-parametric copula-based Markov chain. Working Paper. Coventry: University of Warwick. Department of Economics. Warwick economics research papers series (TWERPS), Volume 2014 (Number 1051). (Unpublished)

Pitt, Michael K., Malik, Sheheryar and Doucet, Arnaud (2014) Simulated likelihood inference for stochastic volatility models using continuous particle filtering. Annals of the Institute of Statistical Mathematics, Volume 66 (Number 3). pp. 527-552. doi:10.1007/s10463-014-0456-y ISSN 0020-3157.

Hall, Jamie, Pitt, Michael K. and Kohn, Robert (2014) Bayesian inference for nonlinear structural time series models. Journal of Econometrics, 179 (2). pp. 99-111. doi:10.1016/j.jeconom.2013.10.016 ISSN 0304-4076.

Pitt, Michael K., Silva, Ralph dos Santos, Giordani, Paolo and Kohn, Robert (2012) On some properties of Markov chain Monte Carlo simulation methods based on the particle filter. Journal of Econometrics, Vol.171 (No.2). pp. 134-151. doi:10.1016/j.jeconom.2012.06.004 ISSN 0304-4076.

Malik, Sheheryar and Pitt, Michael K. (2011) Particle filters for continuous likelihood evaluation and maximisation. Journal of Econometrics, Vol.165 (No.2). pp. 190-209. doi:10.1016/j.jeconom.2011.07.006 ISSN 0304-4076.

Malik, Sheheryar and Pitt, Michael K. (2009) Modelling stochastic volatility with leverage and jumps: a simulated maximum likelihood approach via particle filtering. Working Paper. Coventry: University of Warwick, Department of Economics. Warwick economic research papers (No.897).

Pitt, Michael K., Chan, David and Kohn, Robert (2006) Efficient Bayesian inference for Gaussian copula regression models. Biometrika, Volume 93 (Number 3). pp. 537-554. doi:10.1093/biomet/93.3.537 ISSN 0006-3444.

Pitt, Michael K. and Walker, Stephen G. (2006) Extended constructions of stationary autoregressive processes. Statistics & Probability Letters, Volume 76 (Number 12). pp. 1219-1224. doi:10.1016/j.spl.2005.12.020 ISSN 0167-7152.

Pitt, Michael K. (2002) Smooth particle filters for likelihood evaluation and maximisation. Working Paper. Coventry: University of Warwick, Department of Economics. Warwick economic research papers (No.651).

Pitt, Michael K. and Walker, S. G. (Stephen G.) (2001) Construction of stationary time series via the Gibbs sampler with application to volatility models. Working Paper. Coventry: University of Warwick, Department of Economics. Warwick economic research papers (No.595).