Oddvar Berg Scholarship Essays

Introduction, Peter Green, Nils Hjort, Sylvia Richardson
1: Some modern applications of graphical models, Steffen Lauritzen
Analysing social science data with graphical Markov models, Nanny Wermuth
Analysis of DNA mixtures using Bayesian networks, Julia Mortera
2: Causal inference using influence diagrams: the problem of partial compliance, Philip Dawid
Commentary: causality and statistics, Elja Arjas
Semantics of causal DAG models and the identification of direct and indirect effects, James Robins
3: Causal inference via ancestral graph models, Thomas S. Richardson and Peter Sprites
Other approaches to description of conditional independence structures, Milan Studeny
On ancestral graph Markov models, Jan Koster
4: Causality and graphical models in times series analysis, Rainer Dahlhaus and Michael Eichler
Graphical models for stochastic processes, Vanessa Didelez
Discussion of "Causality and graphical models in times series analysis", Hans Kunsch
5: Linking theory and practice of MCMC, Gareth Roberts
Advances in MCMC: a discussion, Christian Robert
On some current research in MCMC, Arnoldo Frigessi
6: Trans-dimensional Markov chain Monte Carlo, Peter Green
Proposal densities and product space methods, Simon Godsill
Trans-dimensional Bayesian nonparametrics with spatial point processes, Juha Heikkinen
7: Particle filtering methods for dynamic and static Bayesian problems, Carlo Berzuini and Walter Gilks
Some further topics on Monte Carlo methods for dynamic Bayesian problems, Geir Storvik
General principles in sequential Monte Carlo methods, Peter Clifford
8: Spatial models in epidemiological applications, Sylvia Richardson
Some remarks on Gaussian Markov random field models, Leonhard Knorr-Held
A compariosn of spatial point process models in epidemiological applications, Jesper Moller
9: Spatial hierarchical Bayesian modeld in ecological applications, Antti Penttinen, Fabio Divino and Anne Riiali
Likelihood analysis of binary data in space and time, Julian Besag
Some further aspects of spatio-temporal modelling, Alexandro Mello Schmidt
10: Advances in Bayesian image analysis, Merrilee Hurn; Oddvar Husby and Havard Rue
Probabilistic image modelling, M van Lieshout
Prospects in Bayesian image analysis, Alain Trubuil
11: Preventing epidemics in heterogeneous environments, Niels Becker and Sergey Utev
MCMC methods for stochastic epidemic models, Philip O'Neill
Towards Bayesian inference in epidemic models, Kari Auranen
12: Genetic linkage analysis using Markov chain Monte Carlo techniques, Simon Heath
Graphical models for mapping continuous traits, Nuala Sheehan and Daniel Sorensen
Statistical approaches to Genetic Mapping, David Stephens
13: The genealogy of neutral mutation, R C Griffiths and Simon Tavare
Linked versus unlinked DNA data - a comparison based on ancestral inference, Gunter Weiss
The age of a rare mutation, Carsten Wiuf
14: HSSS model criticism, Anthony O'Hagan
What 'base' distribution for model criticism?, M J Bayarri
Some comments on model criticism, Alan Gelfand
15: Topics in nonparametric Bayesian statistics, Nils Hjort
Asymptotics of Nonparametirc Posteriors, Aad van der Vaart
A predictive point of view on Bayesian nonparametrics, Sonia Petrone

Задача дешифровщиков состояла в том, чтобы, изучив его, получить оригинальный, или так называемый открытый, текст. АНБ пригласило Беккера, потому что имелось подозрение, что оригинал был написан на мандаринском диалекте китайского языка, и ему предстояло переводить иероглифы по мере их дешифровки. В течение двух часов Беккер переводил бесконечный поток китайских иероглифов.

Но каждый раз, когда он предлагал перевод, дешифровщики в отчаянии качали головами. Очевидно, получалась бессмыслица.

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