Advances in the Statistical Sciences: Foundations of Statistical Inference: Volume II of the Festschrift in Honor of Professor V.M. Joshis 70th Birth [Paperback]

On May 27-31, 1985, a series of symposia was held at The University of Western Ontario, London, Canada, to celebrate the 70th birthday of Pro? fessor V. M. Joshi. These symposia were chosen to reflect Professor Joshi's research interests as well as areas of expertise in statistical science among faculty in the Departments of Statistical and Actuarial Sciences, Economics, Epidemiology and Biostatistics, and Philosophy. From these symposia, the six volumes which comprise the Joshi Festschrift have arisen. The 117 articles in this work reflect the broad interests and high quality of research of those who attended our conference. We would like to thank all of the contributors for their superb cooperation in helping us to complete this project. Our deepest gratitude must go to the three people who have spent so much of their time in the past year typing these volumes: Jackie Bell, Lise Constant, and Sandy Tarnowski. This work has been printed from camera ready copy produced by our Vax 785 computer and QMS Lasergraphix printers, using the text processing software TEX. At the initiation of this project, we were neophytes in the use of this system. Thank you, Jackie, Lise, and Sandy, for having the persistence and dedication needed to complete this undertaking.Probability and the Future of Statistics.- A Neyman-Pearson-Wald View of Fiducial Probability.- Statistical Principles and Tangent Models.- Data Based Choice of an Ancillary Statistic.- Bernoulli Pairs with Invariant Reversals: An Example of Partial Likelihood.- A Decision-Likelihood Solution to the Problem of Comparing Two Simple Hypotheses.- Statistical Inference for the Overlap Hypothesis.- Bayesian Method of Detecting Change Point in Regression and Growth Curve Models.- How Much Improvement Can a Shrinkage Estimator Give?.- On Shrinkage and Preliminary Test M-Estimation in a Parallelism Problem.- An Algorithm for Concave Regression.- On the Prediction of the Difference Between Responses from Two Linear Models.lC¬