PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Inference and Estimation in Probabilistic Time-Series Models
David Barber and Silvia Chiappa
(2008) Proceedings of the Isaac Newton Institute for Mathematical Sciences . Newton Institute , Cambridge, UK .


Inference and Estimation in Probabilistic Time-Series Models 1 Esmail Amiri, Bayesian study of Stochastic volatility models with STAR volatilities and Leverage effect 10 Katerina Aristodemou,And Keming Yu, CaViaR via Bayesian Nonparametric Quantile Regression 18 John A. D. Aston,Michael Jyh-Ying Peng,Donald E. K. Martin, Is that really the pattern we’re looking for? Bridging the gap between statistical uncertainty and dynamic programming algorithms in pattern detection 26 Yuzhi Cai, A Bayesian Method for Non-Gaussian Autoregressive Quantile Function Time Series Models 28 Adam M. Johansen, Nick Whiteley, A Modern Perspective on Auxiliary Particle Filters 36 Xiaodong Luo, Irene M. Moroz, State Estimation in High Dimensional Systems: The Method of The Ensemble Unscented Kalman Filter 44 Geoffrey J. McLachlan, S.K. Ng, KuiWang, Clustering of Time Course Gene- Expression Data via Mixture Regression Models 50 Valderio A. Reisen, Fabio A. Fajardo Molinares, Francisco Cribari-Neto, Stationary long-memory process in the presence of additive outliers. A robust model estimation 58 Teo Sharia, Parameter Estimation Procedures in Time Series Models 67 Yuan Shen, Cedric Archambeau, Dan Cornford, Manfred Opper, Variational Markov Chain Monte Carlo for Inference in Partially Observed Nonlinear Diffusions 79 Xiaohai Sun, A Kernel Test of Nonlinear Granger Causality 90 Adam Sykulski, Sofia Olhede, Grigorios Pavliotis, High Frequency Variability and Microstructure Bias 98 Michalis K. Titsias, Neil Lawrence, Magnus Rattray, Markov Chain Monte Carlo Algorithms for Gaussian Processes 107 Richard E. Turner, Pietro Berkes, Maneesh Sahani, Two problems with variational expectation maximisation for time-series models

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EPrint Type:Book
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Computational, Information-Theoretic Learning with Statistics
Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:5335
Deposited By:David Barber
Deposited On:24 March 2009