Statistical Inference Under Order Restrictions The Theory And Application Of Isotonic Regression R E Barlow And Others
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Statistical Methods for Disease Clustering
Author: Toshiro Tango
language: en
Publisher: Springer Science & Business Media
Release Date: 2010-01-09
This book is intended to provide a text on statistical methods for detecting clus ters and/or clustering of health events that is of interest to ?nal year undergraduate and graduate level statistics, biostatistics, epidemiology, and geography students but will also be of relevance to public health practitioners, statisticians, biostatisticians, epidemiologists, medical geographers, human geographers, environmental scien tists, and ecologists. Prerequisites are introductory biostatistics and epidemiology courses. With increasing public health concerns about environmental risks, the need for sophisticated methods for analyzing spatial health events is immediate. Further more, the research area of statistical tests for disease clustering now attracts a wide audience due to the perceived need to implement wide ranging monitoring systems to detect possible health related bioterrorism activity. With this background and the development of the geographical information system (GIS), the analysis of disease clustering of health events has seen considerable development over the last decade. Therefore, several excellent books on spatial epidemiology and statistics have re cently been published. However, it seems to me that there is no other book solely focusing on statistical methods for disease clustering. I hope that readers will ?nd this book useful and interesting as an introduction to the subject.
Integer Programming and Combinatorial Optimization
This book constitutes the refereed proceedings of the 7th International Conference on Integer Programming and Combinatorial Optimization, IPCO'99, held in Graz, Austria, in June 1999. The 33 revised full papers presented were carefully reviewed and selected from a total of 99 submissions. Among the topics addressed are theoretical, computational, and application-oriented aspects of approximation algorithms, branch and bound algorithms, computational biology, computational complexity, computational geometry, cutting plane algorithms, diaphantine equations, geometry of numbers, graph and network algorithms, online algorithms, polyhedral combinatorics, scheduling, and semidefinite programs.
Bayesian Evaluation of Informative Hypotheses
Author: Herbert Hoijtink
language: en
Publisher: Springer Science & Business Media
Release Date: 2008-09-08
This book provides an overview of the developments in the area of Bayesian evaluation of informative hypotheses that took place since the publication of the ?rst paper on this topic in 2001 [Hoijtink, H. Con?rmatory latent class analysis, model selection using Bayes factors and (pseudo) likelihood ratio statistics. Multivariate Behavioral Research, 36, 563–588]. The current state of a?airs was presented and discussed by the authors of this book during a workshop in Utrecht in June 2007. Here we would like to thank all authors for their participation, ideas, and contributions. We would also like to thank Sophie van der Zee for her editorial e?orts during the construction of this book. Another word of thanks is due to John Kimmel of Springer for his con?dence in the editors and authors. Finally, we would like to thank the Netherlands Organization for Scienti?c Research (NWO) whose VICI grant (453-05-002) awarded to the ?rst author enabled the organization of the workshop, the writing of this book, and continuation of the research with respect to Bayesian evaluation of informative hypotheses.