Extremal Families And Systems Of Sufficient Statistics
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Author | : Steffen L. Lauritzen |
Publisher | : Springer Science & Business Media |
Total Pages | : 292 |
Release | : 1988-11-28 |
Genre | : Mathematics |
ISBN | : 9780387968728 |
This book surveys results in the area sometimes denoted as "partial exchangeability" of "de Finetti type theorems". It is to be seen as an attempt to give sense to the general idea that there is a strong coupling between a statistical model and the statistical analysis. So strong that there is a canonical mathematical construction leading from the analysis to the model. Special sections are devoted to the study of sufficiency, of triviality of tails of Markov chains, studied e.g. by coupling methods, Martin boundaries and projective limits of Markov kernels and Polish spaces. In addition, many examples of extreme point models are treated in detail. This book is intended for researchers and graduate students in mathematical statistics and probability.
Author | : Steffen L. Lauritzen |
Publisher | : Springer Science & Business Media |
Total Pages | : 283 |
Release | : 2012-12-06 |
Genre | : Mathematics |
ISBN | : 1461210232 |
The pOint of view behind the present work is that the connection between a statistical model and a statistical analysis-is a dua lity (in a vague sense). In usual textbooks on mathematical statistics it is often so that the statistical model is given in advance and then various in ference principles are applied to deduce the statistical ana lysis to be performed. It is however possible to reverse the above procedure: given that one wants to perform a certain statistical analysis, how can this be expressed in terms of a statistical model? In that sense we think of the statistical analysis and the stati stical model as two ways of expressing the same phenomenon, rather than thinking of the model as representing an idealisation of "truth" and the statistical analysis as a method of revealing that truth to the scientist. It is not the aim of the present work to solve the problem of giving the correct-anq final mathematical description of the quite complicated relation between model and analysis. We have rather restricted ourselves to describe a particular aspect of this, formulate it in mathematical terms, and then tried to make a rigorous and consequent investigation of that mathematical struc ture.
Author | : American Mathematical Society |
Publisher | : American Mathematical Soc. |
Total Pages | : 514 |
Release | : 1992 |
Genre | : Mathematics |
ISBN | : 9780821801673 |
In the summer of 1988 in Providence, the AMS celebrated its centennial with a wide range of mathematical activities. Among those was a symposium, Mathematics into the Twenty-first Century, which brought together a number of the top research mathematicians who will likely have a significant impact on the mathematics of this century. This book contains the lectures presented by 16 of the 18 individuals who spoke during the symposium. Written by some of the major international figures in mathematical research, this group of articles covers a panorama of the vital areas of mathematics at the turn of the 21st century and gives the general mathematical reader a broad perspective on some of the major trends in research.
Author | : Eduardo M.R.A. Engel |
Publisher | : Springer Science & Business Media |
Total Pages | : 166 |
Release | : 2012-12-06 |
Genre | : Mathematics |
ISBN | : 1441986847 |
There are many ways of introducing the concept of probability in classical, i. e, deter ministic, physics. This work is concerned with one approach, known as "the method of arbitrary funetionJ. " It was put forward by Poincare in 1896 and developed by Hopf in the 1930's. The idea is the following. There is always some uncertainty in our knowledge of both the initial conditions and the values of the physical constants that characterize the evolution of a physical system. A probability density may be used to describe this uncertainty. For many physical systems, dependence on the initial density washes away with time. Inthese cases, the system's position eventually converges to the same random variable, no matter what density is used to describe initial uncertainty. Hopf's results for the method of arbitrary functions are derived and extended in a unified fashion in these lecture notes. They include his work on dissipative systems subject to weak frictional forces. Most prominent among the problems he considers is his carnival wheel example, which is the first case where a probability distribution cannot be guessed from symmetry or other plausibility considerations, but has to be derived combining the actual physics with the method of arbitrary functions. Examples due to other authors, such as Poincare's law of small planets, Borel's billiards problem and Keller's coin tossing analysis are also studied using this framework. Finally, many new applications are presented.
Author | : Uwe Küchler |
Publisher | : Springer Science & Business Media |
Total Pages | : 325 |
Release | : 2006-05-09 |
Genre | : Mathematics |
ISBN | : 0387227652 |
A comprehensive account of the statistical theory of exponential families of stochastic processes. The book reviews the progress in the field made over the last ten years or so by the authors - two of the leading experts in the field - and several other researchers. The theory is applied to a broad spectrum of examples, covering a large number of frequently applied stochastic process models with discrete as well as continuous time. To make the reading even easier for statisticians with only a basic background in the theory of stochastic process, the first part of the book is based on classical theory of stochastic processes only, while stochastic calculus is used later. Most of the concepts and tools from stochastic calculus needed when working with inference for stochastic processes are introduced and explained without proof in an appendix. This appendix can also be used independently as an introduction to stochastic calculus for statisticians. Numerous exercises are also included.
Author | : Vladimir Vovk |
Publisher | : Springer Science & Business Media |
Total Pages | : 332 |
Release | : 2005-12-05 |
Genre | : Computers |
ISBN | : 0387250611 |
Algorithmic Learning in a Random World describes recent theoretical and experimental developments in building computable approximations to Kolmogorov's algorithmic notion of randomness. Based on these approximations, a new set of machine learning algorithms have been developed that can be used to make predictions and to estimate their confidence and credibility in high-dimensional spaces under the usual assumption that the data are independent and identically distributed (assumption of randomness). Another aim of this unique monograph is to outline some limits of predictions: The approach based on algorithmic theory of randomness allows for the proof of impossibility of prediction in certain situations. The book describes how several important machine learning problems, such as density estimation in high-dimensional spaces, cannot be solved if the only assumption is randomness.
Author | : David Blackwell |
Publisher | : IMS |
Total Pages | : 428 |
Release | : 1996 |
Genre | : Mathematics |
ISBN | : 9780940600423 |
Most of the 26 papers are research reports on probability, statistics, gambling, game theory, Markov decision processes, set theory, and logic. But they also include reviews on comparing experiments, games of timing, merging opinions, associated memory models, and SPLIF's; historical views of Carnap, von Mises, and the Berkeley Statistics Department; and a brief history, appreciation, and bibliography of Berkeley professor Blackwell. A sampling of titles turns up The Hamiltonian Cycle Problem and Singularly Perturbed Markov Decision Process, A Pathwise Approach to Dynkin Games, The Redistribution of Velocity: Collision and Transformations, Casino Winnings at Blackjack, and Randomness and the Foundations of Probability. No index. Annotation copyrighted by Book News, Inc., Portland, OR
Author | : Mark J. Schervish |
Publisher | : Springer Science & Business Media |
Total Pages | : 732 |
Release | : 2012-12-06 |
Genre | : Mathematics |
ISBN | : 1461242509 |
The aim of this graduate textbook is to provide a comprehensive advanced course in the theory of statistics covering those topics in estimation, testing, and large sample theory which a graduate student might typically need to learn as preparation for work on a Ph.D. An important strength of this book is that it provides a mathematically rigorous and even-handed account of both Classical and Bayesian inference in order to give readers a broad perspective. For example, the "uniformly most powerful" approach to testing is contrasted with available decision-theoretic approaches.
Author | : Constantine Gatsonis |
Publisher | : Springer Science & Business Media |
Total Pages | : 483 |
Release | : 2012-12-06 |
Genre | : Mathematics |
ISBN | : 1461222907 |
This third volume of case studies presents detailed applications of Bayesian statistical analysis, emphasising the scientific context. The papers were presented and discussed at a workshop held at Carnegie-Mellon University, and this volume - dedicated to the memory of Morrie Groot-reproduces six invited papers, each with accompanying invited discussion, and nine contributed papers with the focus on econometric applications.
Author | : Piero Barone |
Publisher | : Springer Science & Business Media |
Total Pages | : 266 |
Release | : 2012-12-06 |
Genre | : Mathematics |
ISBN | : 1461229200 |
This volume comprises a collection of papers by world- renowned experts on image analysis. The papers range from survey articles to research papers, and from theoretical topics such as simulated annealing through to applied image reconstruction. It covers applications as diverse as biomedicine, astronomy, and geophysics. As a result, any researcher working on image analysis will find this book provides an up-to-date overview of the field and in addition, the extensive bibliographies will make this a useful reference.