Challenges in Stochastic Computation
PROGRAM OF RESEARCH PRESENTATIONS

Saturday, September 28

Session 1: MCMC Theory and Methods
10:00 am - 12:30 pm

• Sequential Importance Sampling with Pilot Exploration
  Jun Liu
  
• Bridge Estimation of the Probability Density at a Point
  Antonietta Mira
  
• Adaptive Polar Sampling: a Flexible and Robust Monte Carlo Method
  Herman van Dijk

Session 2: More MCMC Theory and Methods
2:00 pm - 3:40 pm

• A Strategy for MCMC Acceleration
  David Draper
  
• Honest MCMC via Drift and Minorization
  Jim Hobert

Session 3: And more MCMC
4:10 pm - 5:50 pm

• An Efficient Sampler for Decomposable Covariance Selection Models
  Chris Carter
  
• Analysis of van Dyk and Meng's Data Augmentation Algorithm for the Multivariate t Model
  Dobrin Marchev

POSTER SESSION: 8:00 pm - 11:00 pm (with cash bar)

Sunday, September 29

Session 4: Particle Filtering and Sequential Methods
9:00 am - 10:40 am

• Particle Methods for Control of Nonlinear Non-Gaussian State-Space Models
  Arnaud Doucet
  
• Smoothing and Filtering with Particle Approximations
  Simon Godsill

Session 5: Stochastic Computation in Contingency Tables and Discrete Distributions
11:10 am - 12:50 pm

• Posterior Distributions over Spaces of Contingency Tables
  Adrian Dobra
  
• Transform Methods for the Hypergeometric Distribution
  Ian Dinwoodie

Session 6: Stochastic Computation in Spatial Statistics
2:00 pm - 3:40 pm

• Hidden Markov Models and Disease Mapping
  Peter Green
  
• Stochastic Computation Strategies for Fitting Spatial Data Models
  Alan Gelfand

Session 7: Stochastic Computation in Nonparametric Regression and Curve Fitting
4:10 pm - 5:50 pm

• Stochastic Simulation Based Methods for Bayesian Curve and Surface fitting
  Bani Mallick
  
• Estimation and Variable Selection in Nonparametric Heteroscedastic Regression
  Robert Kohn

Monday, September 30

Session 8: Stochastic Computation in Population Genetics
9:00 am - 10:40 pm

• Approximate Bayesian Computation in Population Genetics
  Simon Tavare
  
• Sequential Importance Sampling with Resampling in Molecular Population Genetics
  Yuguo Chen

Session 9: More Stochastic Computation in Genetics
11:10 am - 12:50 pm

• Pedigree Data Analysis with Crossover Interference
  Sharon Browning
  
• MCMC in Parentage Analysis
  Beatrix Jones

Session 10: Perfect Sampling and Novel Methods of Stochastic Computation
2:00 pm - 3:40 pm

• Perfect Sampling for Some Mixtures of Distributions
  Mark Huber
  
• Perfect Sampling for Non-Markovian Queues
  Duncan Murdoch

Session 11: Perfect Sampling
4:10 pm - 5:50 pm

• Perfect Forward Simulation via Simulated Tempering
  Steve  Brooks
  
• On the Possibility, and Impossibility, of Interruptible Perfect Sampling
  Jim Fill
  
  

Session 12: Stochastic Computation and SDEs
9:00 am - 10:40 am

• Variance Reduction Methods in Monte Carlo Simulations for Stochastic Differential Equations
  Yazhen Wang
  
• On the Perfect Simulation of Stochastic Differential Equations
  Xiaoqiang Li

Session 13: Stochastic Computation in Hierarchical Models and Applications
11:10 am - 12:50 pm

• Bayesian Hierarchical Quantile Regression
  David Dunson
  
• Signature Recognition via MCMC
  Ian McKeague

Session 14: Stochastic Computation in Financial Modelling
2:00 pm - 4:20 pm

• Monte Carlo Simulations in Finance
  Jean Pierre Fouque
  
• An MCMC Approach for Multivariate Dynamic Models with Stochastic Volatility
  Jane Liu
  
• Multivariate Stochastic Volatility Models: Portfolio Allocation, Financial Contagion and Regime Switching
  Hedibert Lopes
  
  

CONFERENCE DINNER: 7:30 pm

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