Includes bibliographical references (p. 379-406) and index.
|Statement||Geof H. Givens, Jennifer A. Hoeting.|
|Series||Wiley series in probability and statistics|
|Contributions||Hoeting, Jennnifer A. 1966-|
|LC Classifications||QA276.4 .G58 2005|
|The Physical Object|
|Pagination||xix, 418 p. :|
|Number of Pages||418|
|LC Control Number||2005297238|
Computational Statistics is recommended for graduate-level courses in statistics, computer science, mathematics, engineering, and other quantitative sciences. Advanced undergraduate students can also use this text to learn the basics and for deeper study as they progress. Chapters are written to stand independently, allowing instructors to /5(5). Jan 03, · Think Stats by Allen Downey, Greentea Press is a good read. It is also available as a free download(tonyasgaapartments.com), and introduces basics of. Computational Statistics (CompStat) is an international journal that fosters the publication of applications and methodological research in the field of computational statistics. The journal provides a forum for computer scientists, mathematicians, and statisticians working in a variety of areas in statistics, including biometrics, econometrics, data analysis, graphics, simulation, algorithms. The book assumes an intermediate background in mathematics, computing, and applied and theoretical statistics. The first part of the book, consisting of a single long chapter, reviews this background material while introducing computationally-intensive exploratory data analysis and computational inference.
Computational inference has taken its place alongside asymptotic inference and exact techniques in the standard collection of statistical methods. Computational inference is based on an approach to statistical methods that uses modern computational power to simulate distributional properties of estimators and test statistics. This book describes computationally-intensive statistical methods in. Oct 22, · GEOF H. GIVENS, PhD, is Associate Professor in the Department of Statistics at Colorado State University. He serves as Associate Editor for Computational Statistics and Data Analysis. His research interests include statistical problems in wildlife conservation biology including ecology, population modeling and management, and automated computer face recognition. Computational Statistics by James E. Gentle - free book at E-Books Directory. You can download the book or read it online. It is made freely available by its author. A hands-on introduction to computational statistics from a Bayesian point of view Providing a solid grounding in statistics while uniquely covering the topics from a Bayesian perspective, Understanding Computational Bayesian Statistics successfully guides readers through this new, cutting-edge approach. With its hands-on treatment of the topic, the book shows how samples can be drawn from the.
Purchase Computational Statistics with R, Volume 32 - 1st Edition. Print Book & E-Book. ISBN , Computational Statistics Handbook with MATLAB ®, Third Edition covers today’s most commonly used techniques in computational statistics while maintaining the same philosophy and writing style of the bestselling previous editions. The text keeps theoretical concepts to a minimum, emphasizing the implementation of the methods. The book includes a large number of exercises with some solutions provided in an appendix. James E. Gentle is University Professor of Computational Statistics at George Mason University. He is a Fellow of the American Statistical Association (ASA) and of the American Association for . This book does not cover topics about the basic Python programming language. Python libraries for computational statistics and data science. Python has big communities. They help their members to learn and share. Several community members have been open sources related to computational statistics and data science, which can be used for our work.