| Summary: | Recent books in the Wiley Series in Probability and Statistics Editors Vic Barnett J. Stuart Hunter David W. Scott Geoffrey S. Watson Ralph A. Bradley Joseph B. Kadane Adrian F.M. Smith Nicholas I. Fisher David G. Kendall Jozef L. Teugels Stochastic Geometry and Its Applications Second Edition Dietrich Stoyan, TU Bergakademie Freiberg, Germany Wilfrid S. Kendall, University of Warwick, UK Joseph Mecke, Friedrich-Schiller-Universitat Jena, Germany This standard text makes the results and methods of stochastic geometry and spatial statistics accessible to practitioners and non-theoreticians. The book is also ideal as an introduction to the subject for mathematicians. The exposition is mathematically precise and takes into account the latest results, but in many cases proofs are omitted. Topics covered include the basic theories of point processes, random sets, fibre and surface processes, random tessellations, stereology and the statistical theory of shape. The theory is illustrated by many examples drawn from different branches of science; actual data in the form of images are presented, and their statistical analysis is discussed. As well as being of great interest to statisticians, this treatment of the subject has proved useful to applied scientists working in fields such as geology, biology, microscopy and materials science, and to pure mathematicians working in geometry. 1995 Bayesian Analysis in Statistics and Econometrics. Essays in Honor of Arnold Zellner Donald A. Berry, Duke University Kathryn M. Chaloner, University of Minnesota John K. Geweke, University of Minnesota This volume affords students and professionals in statistics, econometrics, and other fields of statistical applications a unique opportunity to acquaint themselves with important current and future trends in Bayesian analytical theory and practice. Over the course of forty-eight chapters, more than one hundred authors from around the world explore a vast array of practical and theoretical issues. Topics covered include inference, estimation, prediction, regression, linear model, multivariate analysis, model selection and computation. This is a valuable working resource for statisticians, economists, and all those with a professional interest in the Bayesian approach. 1996
|
|---|
