The Savage AwardThe Savage Award, named in honor of Leonard J. "Jimmie" Savage, is bestowed each year to two outstanding doctoral dissertations in Bayesian econometrics and statistics, one each in:
The award was instituted by the NBER-NSF Seminar in Bayesian Inference in Econometrics and Statistics in 1977. ISBA and the ASA Section on Bayesian Statistical Science (SBSS) joined as co-sponsors in 1993. Leonard J. "Jimmie" SavageBorn 20 November 1917, Jimmie Savage was graduated from the University of Michigan and later worked at the Institute for Advanced Study in Princeton, New Jersey, the University of Chicago, and the Statistical Research Group at Columbia University. Though his thesis advisor was Sumner Myers, he also credited Milton Friedman and W. Allen Wallis as his statistical mentors.His most noted work was the 1954 book Foundations of Statistics, in which he put forward a theory of subjective and personal probability and statistics which forms one of the strands underlying Bayesian statistics and has applications to game theory. One of Savage's indirect contributions was his discovery of the work of Louis Bachelier on stochastic models for asset prices and the mathematical theory of option pricing. Savage brought the work of Bachelier to the attention of Paul Samuelson. It was from Samuelson's subsequent writing that random walk (and subsequently Brownian motion) became fundamental to mathematical finance. In 1951 he introduced the Minimax regret criterion used in decision theory. The Hewitt-Savage zero-one law is (in part) named after him. Eligibility and Application ProcedureThe Bylaws specify that all Ph.D. theses that have not been submitted in a previous year are eligible; thus a dissertation may be nominated only once. The Prize Committee interprets the phrase "Ph.D. Thesis" to mean a dissertation in final form: approved by the student's committee or examining board, for example (final University approval is not required). A dissertation may be nominated by the author, by the advisor, the department chair, or by any ISBA or SBSS member (joining ISBA is easy). Nomination is made by on-line electronic submission of the dissertation along with a letter that describes the main theoretical, methodological, and/or applied contributions of the thesis and specifies for which award the thesis is being nominated--- either Theory and Methods or Applied Methodology.Nominating letters should be written in English, and it is recommended that dissertations also be written in English (the Savage Award Committee may require an English translation for full consideration of theses written in other languages). Dissertations and letters must be submitted electronically in pdf format. Dissertations may be submitted on-line here. Finalists will be selected by the middle of January and will be invited to present their dissertations at the Joint Statistics Meetings (in odd years) or at an ISBA World Meeting (in even years), with the winners announced at the meeting. Questions about the process may be sent to awards@bayesian.org. 2009 Savage Award FinalistsThe finalists for the 2009 Savage Award are:
Past Winners of the Savage Award
Antonietta Mira, Ordering, splicing and splitting Monte Carlo Markov chains. Univ Minnesota; Luke Tierney, advisor. Jaelong Lee (Honorable Mention) Semiparametric Bayesian analysis: selection models and meteorolgical applications. Purdue Univ; Jim Berger, advisor. David Denison, Simulation Based Bayesian Non-parametric Regression Methods. Imperial College; Bani Mallick & Adrian Smith, advisors. Juha Heikkinen (Honorable Mention), Bayesian Smoothing and Step Functions in Nonparametric Estimation of Curves and Surfaces. Univ Helsinki; Antti Penttinen & Elija Arjas, advisors. Nariankadu D. Shyamalkumar, Contributions to Bayesian Nonparametrics and Bayesian Robustness. Purdue Univ; Jim Berger, advisor. Eric Bradlow (Honorable Mention), A Hierarchical Latent Response Model for Ordinal Data with "No Answer" Responses. Harvard Univ; Alan Zaslavsky, advisor. Max Chickering (Honorable Mention), Learning Bayesian Networks from Data. UCLA; David Heckerman, Richard Korf & Judea Pearl, advisors. Andrea Piesse (Honorable Mention), Coherent Predictive Probabilities. Univ Canterbury; John Deely & Frank Lad, advisors. Christopher K. Carter (Co-winner), On Markov Chain Monte Carlo for Linear State Space. Univ New South Wales; Robert Kohn, advisor. Alyson Wilson (Co-winner) Statistical Models for Shapes and Deformations. Duke Univ; Valen Johnson, advisor. Simon J. Godsill (Honorable Mention), The Restoration of Degraded Audio Signals. Ming-Hui Chen (Honorable Mention), Monte Carlo Markov Chain Sampling for Bayesian Computation with Applications. Purdue Univ; Jim Berger & Bruce Schmeiseer, advisors. Merlise A. Clyde, Bayesian Optimal Designs for Approximate Normality. Univ Minnesota; Kathryn Chaloner, advisor. Marìa Del Carmen Fernandez-Llana (Honorable Mention), Estudios Sobre Robustez Bayesiana Global. Univ Autonoma de Madrid; Julian de la Horra, advisor. Paul Gustafson (Honorable Mention), Local Sensitivity of Posterior Expectations. CMU; Larry Wasserman, advisor. Debajyoti Sinha (Honorable Mention), Semiparametric Bayesian Analysis of Single and Multiple Time Event Data. Univ Rochester; W Jack Hall, advisor. Charles Jeremy York, Bayesian Methods for the Analysis of Misclassified or Incomplete Multivariate Data. Giovanni Parmigiani, Optimal Scheduling of Inspections with an Application to Medical Screening Tests. Valen E. Johnson, On Statistical Image Reconstruction. Michael David Escobar, Estimating the Means of Several Normal Populations by Nonparametric Estimation of the distribution of the Means. Peter E. Rossi, Specification and Analysis of Econometric Production Models. Mohan Delampady (Co-winner), Testing a Precise Hypothesis Interpreting P-Values from a Robust Bayesian Viewpoint. S. Sivaganesan (Co-winner), Robust Bayesian Analysis with Contamminated Classes. Herman K. van Dijk (Co-winner), Posterior Analysis of Econometric Models Using Monte Carlo Integration. Peter Jamison Lenk, Bayesian Nonparametric Predictive Distributions. Luc Bauwens (Co-winner), Bayesian Full Information Analysis of Simultaneous Equation Models. Peter C. Cranston (Co-winner), The Role of Time and Information in Bargaining. Paul H. Garthwaite, Assessment of Prior Distributions for Normal Linear Models. Soo Hong Chew, Two representation Theorems and Their Applications to Decision Theory. Robert Kass (Co-winner), The Riemannian Structure of Model Spaces: A Geometrical Approach to Inference. John P. O'Connor (Co-winner), A Certainty Equivlaent Based Metrization of Utility Function Space. Paul Milgram, The Structure of Information in Competitive Bidding. Kevin James McConway, The Combination of Experts' Opinions in Probability Assessment: Some Theoretical Considerations. Lorraine DeRobertis, The Use of Partial Prior Knowledge in Bayesian Inference. José Bernardo (Honorable Mention), The Use of Information in the Design and Analysis of Scientific Experimentation. Charles A. Holt, Bidding for Contracts. Robert Shore (Honorable Mention), A Bayesian Approach to the Spectral Analysis of Stationary Time Series. |