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Author: Ding-Geng Chen
Publisher: Springer
ISBN: 3319694162
Category : Mathematics
Languages : en
Pages : 355
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Book Description
This book is comprised of the presentations delivered at the 25th ICSA Applied Statistics Symposium held at the Hyatt Regency Atlanta, on June 12-15, 2016. This symposium attracted more than 700 statisticians and data scientists working in academia, government, and industry from all over the world. The theme of this conference was the “Challenge of Big Data and Applications of Statistics,” in recognition of the advent of big data era, and the symposium offered opportunities for learning, receiving inspirations from old research ideas and for developing new ones, and for promoting further research collaborations in the data sciences. The invited contributions addressed rich topics closely related to big data analysis in the data sciences, reflecting recent advances and major challenges in statistics, business statistics, and biostatistics. Subsequently, the six editors selected 19 high-quality presentations and invited the speakers to prepare full chapters for this book, which showcases new methods in statistics and data sciences, emerging theories, and case applications from statistics, data science and interdisciplinary fields. The topics covered in the book are timely and have great impact on data sciences, identifying important directions for future research, promoting advanced statistical methods in big data science, and facilitating future collaborations across disciplines and between theory and practice.
Author: Ding-Geng Chen
Publisher: Springer
ISBN: 3319694162
Category : Mathematics
Languages : en
Pages : 355
Get Book Here
Book Description
This book is comprised of the presentations delivered at the 25th ICSA Applied Statistics Symposium held at the Hyatt Regency Atlanta, on June 12-15, 2016. This symposium attracted more than 700 statisticians and data scientists working in academia, government, and industry from all over the world. The theme of this conference was the “Challenge of Big Data and Applications of Statistics,” in recognition of the advent of big data era, and the symposium offered opportunities for learning, receiving inspirations from old research ideas and for developing new ones, and for promoting further research collaborations in the data sciences. The invited contributions addressed rich topics closely related to big data analysis in the data sciences, reflecting recent advances and major challenges in statistics, business statistics, and biostatistics. Subsequently, the six editors selected 19 high-quality presentations and invited the speakers to prepare full chapters for this book, which showcases new methods in statistics and data sciences, emerging theories, and case applications from statistics, data science and interdisciplinary fields. The topics covered in the book are timely and have great impact on data sciences, identifying important directions for future research, promoting advanced statistical methods in big data science, and facilitating future collaborations across disciplines and between theory and practice.
Author: M. Haseeb Rizvi
Publisher: Academic Press
ISBN: 1483266605
Category : Mathematics
Languages : en
Pages : 626
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Book Description
Recent Advances in Statistics: Papers in Honor of Herman Chernoff on His Sixtieth Birthday is a collection of papers on statistics in honor of Herman Chernoff on the occasion of his 60th birthday. Topics covered range from sequential analysis (including designs) to optimization (including control theory), nonparametrics (including large sample theory), and statistical graphics. Comprised of 27 chapters, this book begins with a discussion on optimal stopping of Brownian motion, followed by an analysis of sequential design of comparative clinical trials. A two-sample sequential test for shift with one sample size fixed in advance is then presented. Subsequent chapters focus on set-valued parameters and set-valued statistics; large deviations of the maximum likelihood estimate in the Markov chain case; the limiting behavior of multiple roots of the likelihood equation; and optimal uniform rate of convergence for nonparametric estimators of a density function and its derivatives. The book concludes by considering significance and confidence levels, closed regions and models, and discrete distributions. This monograph should be of interest to students, researchers, and specialists in the fields of mathematics and statistics.
Author: J. P. Vilaplana
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3112313968
Category : Mathematics
Languages : en
Pages : 480
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Book Description
No detailed description available for "Recent Advances in Statistics and Probability".
Author: Yogendra P Chaubey
Publisher: World Scientific
ISBN: 1783261145
Category : Mathematics
Languages : en
Pages : 378
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Book Description
This volume consists of research papers dealing with computational and methodological issues of statistical methods on the cutting edge of modern science. It touches on many applied fields such as Bayesian Methods, Biostatistics, Econometrics, Finite Population Sampling, Genomics, Linear and Nonlinear Models, Networks and Queues, Survival Analysis, Time Series, and many more.
Author: M.G. Akritas
Publisher: Elsevier
ISBN: 0444513787
Category : Computers
Languages : en
Pages : 524
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Book Description
The advent of high-speed, affordable computers in the last two decades has given a new boost to the nonparametric way of thinking. Classical nonparametric procedures, such as function smoothing, suddenly lost their abstract flavour as they became practically implementable. In addition, many previously unthinkable possibilities became mainstream; prime examples include the bootstrap and resampling methods, wavelets and nonlinear smoothers, graphical methods, data mining, bioinformatics, as well as the more recent algorithmic approaches such as bagging and boosting. This volume is a collection of short articles - most of which having a review component - describing the state-of-the art of Nonparametric Statistics at the beginning of a new millennium. Key features: . algorithic approaches . wavelets and nonlinear smoothers . graphical methods and data mining . biostatistics and bioinformatics . bagging and boosting . support vector machines . resampling methods
Author: Y. Baba
Publisher: Springer Science & Business Media
ISBN: 4431685448
Category : Mathematics
Languages : en
Pages : 133
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Book Description
Recent Advances in Statistical Research and Data Analysis is a collection of papers presented at the symposium of the same name, held in Tokyo by the Center for Information on Statistical Science of the Institute of Statistical Mathematics (ISM). Under the auspices of the Ministry of Education, Culture, Sports, Science and Technology of Japan, the ISM has created visiting professorships and organized symposia to promote collaboration between researchers from Japan and those from other countries. At the symposium on recent advances in statistical research and data analysis, the keynote speaker was Visiting Professor Anthony J. Hayter. This book includes Prof. Hayter's address as well as papers from special lectures that were presented at the symposium. All the contributions are concerned with theory and methodology for real data and thus will benefit researchers, students, and others engaged in data analysis.
Author: Andy Hector
Publisher: Oxford University Press
ISBN: 0198729057
Category : Mathematics
Languages : en
Pages : 217
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Book Description
An introductory level text covering linear, generalized linear, linear mixed-effects, and generalized mixed models implemented in R and set within a contemporary framework.
Author: Ding-Geng (Din) Chen
Publisher: Springer
ISBN: 9811051941
Category : Mathematics
Languages : en
Pages : 382
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Book Description
This book focuses on the statistical aspects of the analysis of degradation data. In recent years, degradation data analysis has come to play an increasingly important role in different disciplines such as reliability, public health sciences, and finance. For example, information on products’ reliability can be obtained by analyzing degradation data. In addition, statistical modeling and inference techniques have been developed on the basis of different degradation measures. The book brings together experts engaged in statistical modeling and inference, presenting and discussing important recent advances in degradation data analysis and related applications. The topics covered are timely and have considerable potential to impact both statistics and reliability engineering.
Author: Rand R. Wilcox
Publisher: Gulf Professional Publishing
ISBN: 9780127515410
Category : Mathematics
Languages : en
Pages : 688
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Book Description
Applying Contemporary Statistical Techniques explains why traditional statistical methods are often inadequate or outdated when applied to modern problems. Wilcox demonstrates how new and more powerful techniques address these problems far more effectively, making these modern robust methods understandable, practical, and easily accessible. Highlights: * Assumes no previous training in statistics * Explains when and why modern methods provide more accurate results * Provides simple descriptions of when and why conventional methods can be highly unsatisfactory * Covers the latest developments on multiple comparisons * Includes recent advances in risk-based methods * Features many illustrations and examples using data from real studies * Describes and illustrates easy-to-use s-plus functions for applying cutting-edge techniques "The book is quite unique in that it offers a lot of up-to-date statistical tools. No other book at this level comes close in this aspect." Xuming He -University of Illinois, Urbana
Author: Abdelaati Daouia
Publisher: Springer Nature
ISBN: 3030732495
Category : Mathematics
Languages : en
Pages : 713
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Book Description
This book presents a unique collection of contributions on modern topics in statistics and econometrics, written by leading experts in the respective disciplines and their intersections. It addresses nonparametric statistics and econometrics, quantiles and expectiles, and advanced methods for complex data, including spatial and compositional data, as well as tools for empirical studies in economics and the social sciences. The book was written in honor of Christine Thomas-Agnan on the occasion of her 65th birthday. Given its scope, it will appeal to researchers and PhD students in statistics and econometrics alike who are interested in the latest developments in their field.
