Some Recent Advances In Statistics
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| Author | : Ding-Geng Chen |
| Publisher | : Springer |
| Total Pages | : 355 |
| Release | : 2018-01-17 |
| Genre | : Mathematics |
| ISBN | : 3319694162 |
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 | : Yogendra P Chaubey |
| Publisher | : World Scientific |
| Total Pages | : 276 |
| Release | : 2013-03-14 |
| Genre | : Mathematics |
| ISBN | : 9814417998 |
This volume consists of a series of research papers presented at the conference Statistics 2011 Canada: 5th Canadian Conference in Applied Statistics held together with the 20th conference of the Forum for Interdisciplinary Mathematics titled, “Interdisciplinary Mathematical & Statistical Techniques”. These papers cover a wide range of topics from applications of Mathematics and Statistics such as Selection Bias in Surveys, Biomarker Discovery, Analysis of Earth Temperature, Supply Chain Management, Trimmed ANOVA, Zero-inflated Data, Non-Gaussian Time Series, and Stochastic Ordering; Classification, Nonparametric Test, and Jackknifed Ridge Estimator; Bayes Factor; Random Graphs and Error Correcting Codes; Meta Analysis; and National Health Plans and Risk Reduction through Supply Chain.The topics have been reviewed by experts in the field and the selected papers are expected to provide a topical resource on the subjects concerned.
| Author | : Henry Han |
| Publisher | : Springer Nature |
| Total Pages | : 295 |
| Release | : 2020-09-28 |
| Genre | : Computers |
| ISBN | : 9811587604 |
This book constitutes selected papers of the Third International Conference on Data Science, Medicine and Bioinformatics, IDMB 2019, held in Nanning, China, in June 2019. The 19 full papers and 1 short paper were carefully reviewed and selected from 93 submissions. The papers are organized according to the following topical sections: business data science: fintech, management, and analytics.- health and biological data science.- novel data science theory and applications.
| Author | : M.G. Akritas |
| Publisher | : Elsevier |
| Total Pages | : 524 |
| Release | : 2003-10-31 |
| Genre | : Computers |
| ISBN | : 0444513787 |
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 | : Peter F. Thall |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 263 |
| Release | : 2012-12-06 |
| Genre | : Medical |
| ISBN | : 1461520096 |
Clinical trials have two purposes -- to treat the patients in the trial, and to obtain information which increases our understanding of the disease and especially how patients respond to treatment. Statistical design provides a means to achieve both these aims, while statistical data analysis provides methods for extracting useful information from the trial data. Recent advances in statistical computing have enabled statisticians to implement very rapidly a broad array of methods which previously were either impractical or impossible. Biostatisticians are now able to provide much greater support to medical researchers working in both clinical and laboratory settings. As our collective toolkit of techniques for analyzing data has grown, it has become increasingly difficult for biostatisticians to keep up with all the developments in our own field. Recent Advances in Clinical Trial Design and Analysis brings together biostatisticians doing cutting-edge research and explains some of the more recent developments in biostatistics to clinicians and scientists who work in clinical trials.
| Author | : Yogendra P. Chaubey |
| Publisher | : World Scientific |
| Total Pages | : 276 |
| Release | : 2013 |
| Genre | : Business & Economics |
| ISBN | : 981441798X |
This volume consists of a series of research papers presented at the conference Statistics 2011 Canada: 5th Canadian Conference in Applied Statistics held together with the 20th conference of the Forum for Interdisciplinary Mathematics titled, OC Interdisciplinary Mathematical & Statistical TechniquesOCO. These papers cover a wide range of topics from applications of Mathematics and Statistics such as Selection Bias in Surveys, Biomarker Discovery, Analysis of Earth Temperature, Supply Chain Management, Trimmed ANOVA, Zero-inflated Data, Non-Gaussian Time Series, and Stochastic Ordering; Classification, Nonparametric Test, and Jackknifed Ridge Estimator; Bayes Factor; Random Graphs and Error Correcting Codes; Meta Analysis; and National Health Plans and Risk Reduction through Supply Chain.The topics have been reviewed by experts in the field and the selected papers are expected to provide a topical resource on the subjects concerned.
| Author | : Manish Bhattacharjee |
| Publisher | : World Scientific |
| Total Pages | : 311 |
| Release | : 2011 |
| Genre | : Science |
| ISBN | : 9814329800 |
This unique volume provides self-contained accounts of some recent trends in Biostatistics methodology and their applications. It includes state-of-the-art reviews and original contributions. The articles included in this volume are based on a careful sel
| Author | : Rand R. Wilcox |
| Publisher | : Gulf Professional Publishing |
| Total Pages | : 688 |
| Release | : 2003-01-06 |
| Genre | : Mathematics |
| ISBN | : 9780127515410 |
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 | : M. Haseeb Rizvi |
| Publisher | : Academic Press |
| Total Pages | : 626 |
| Release | : 2014-05-10 |
| Genre | : Mathematics |
| ISBN | : 1483266605 |
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 | : Thunshun Warren Liao |
| Publisher | : World Scientific |
| Total Pages | : 816 |
| Release | : 2008 |
| Genre | : Computers |
| ISBN | : 981277985X |
The main goal of the new field of data mining is the analysis of large and complex datasets. Some very important datasets may be derived from business and industrial activities. This kind of data is known as ?enterprise data?. The common characteristic of such datasets is that the analyst wishes to analyze them for the purpose of designing a more cost-effective strategy for optimizing some type of performance measure, such as reducing production time, improving quality, eliminating wastes, or maximizing profit. Data in this category may describe different scheduling scenarios in a manufacturing environment, quality control of some process, fault diagnosis in the operation of a machine or process, risk analysis when issuing credit to applicants, management of supply chains in a manufacturing system, or data for business related decision-making.
