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Frontiers In Statistics


Frontiers In Statistics
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New Frontiers In Statistics And Data Science


New Frontiers In Statistics And Data Science
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Author : Lígia Henriques-Rodrigues
language : en
Publisher: Springer Nature
Release Date : 2025-01-10

New Frontiers In Statistics And Data Science written by Lígia Henriques-Rodrigues and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-10 with Mathematics categories.


This volume showcases a collection of thirty-two peer-reviewed articles presented at the XXVI Congress of the Portuguese Statistical Society (2023). It covers a wide range of cutting-edge topics in both theoretical and applied statistics. Each contribution highlights the latest advancements and research in the field, offering valuable insights and innovative methodologies for researchers and practitioners alike. Readers with a background in mathematics and statistics will find it particularly beneficial, while researchers from various scientific disciplines can explore numerous robust applications.



Frontiers In Statistics


Frontiers In Statistics
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Author : Jianqing Fan
language : en
Publisher: World Scientific
Release Date : 2006

Frontiers In Statistics written by Jianqing Fan and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Mathematics categories.


During the last two decades, many areas of statistical inference have experienced phenomenal growth. This book presents a timely analysis and overview of some of these new developments and a contemporary outlook on the various frontiers of statistics.Eminent leaders in the field have contributed 16 review articles and 6 research articles covering areas including semi-parametric models, data analytical nonparametric methods, statistical learning, network tomography, longitudinal data analysis, financial econometrics, time series, bootstrap and other re-sampling methodologies, statistical computing, generalized nonlinear regression and mixed effects models, martingale transform tests for model diagnostics, robust multivariate analysis, single index models and wavelets.This volume is dedicated to Prof. Peter J Bickel in honor of his 65th birthday. The first article of this volume summarizes some of Prof. Bickel's distinguished contributions.



Artificial Intelligence Frontiers In Statistics


Artificial Intelligence Frontiers In Statistics
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Author : David J. Hand
language : en
Publisher: CRC Press
Release Date : 2020-11-26

Artificial Intelligence Frontiers In Statistics written by David J. Hand and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-26 with Business & Economics categories.


This book presents a summary of recent work on the interface between artificial intelligence and statistics. It does this through a series of papers by different authors working in different areas of this interface. These papers are a selected and referenced subset of papers presented at the 3rd Interntional Workshop on Artificial Intelligence and Statistics, Florida, January 1991.



Artificial Intelligence Frontiers In Statistics


Artificial Intelligence Frontiers In Statistics
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Author : D. J. Hand
language : en
Publisher: Springer
Release Date : 2013-08-22

Artificial Intelligence Frontiers In Statistics written by D. J. Hand and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-22 with Mathematics categories.




Frontiers In Statistical Quality Control 11


Frontiers In Statistical Quality Control 11
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Author : Sven Knoth
language : en
Publisher: Springer
Release Date : 2015-04-24

Frontiers In Statistical Quality Control 11 written by Sven Knoth and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-24 with Computers categories.


The main focus of this edited volume is on three major areas of statistical quality control: statistical process control (SPC), acceptance sampling and design of experiments. The majority of the papers deal with statistical process control, while acceptance sampling and design of experiments are also treated to a lesser extent. The book is organized into four thematic parts, with Part I addressing statistical process control. Part II is devoted to acceptance sampling. Part III covers the design of experiments, while Part IV discusses related fields. The twenty-three papers in this volume stem from The 11th International Workshop on Intelligent Statistical Quality Control, which was held in Sydney, Australia from August 20 to August 23, 2013. The event was hosted by Professor Ross Sparks, CSIRO Mathematics, Informatics and Statistics, North Ryde, Australia and was jointly organized by Professors S. Knoth, W. Schmid and Ross Sparks. The papers presented here were carefully selected and reviewed by the scientific program committee, before being revised and adapted for this volume.



Frontiers Of Statistical Decision Making And Bayesian Analysis


Frontiers Of Statistical Decision Making And Bayesian Analysis
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Author : Ming-Hui Chen
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-07-24

Frontiers Of Statistical Decision Making And Bayesian Analysis written by Ming-Hui Chen and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-07-24 with Mathematics categories.


Research in Bayesian analysis and statistical decision theory is rapidly expanding and diversifying, making it increasingly more difficult for any single researcher to stay up to date on all current research frontiers. This book provides a review of current research challenges and opportunities. While the book can not exhaustively cover all current research areas, it does include some exemplary discussion of most research frontiers. Topics include objective Bayesian inference, shrinkage estimation and other decision based estimation, model selection and testing, nonparametric Bayes, the interface of Bayesian and frequentist inference, data mining and machine learning, methods for categorical and spatio-temporal data analysis and posterior simulation methods. Several major application areas are covered: computer models, Bayesian clinical trial design, epidemiology, phylogenetics, bioinformatics, climate modeling and applications in political science, finance and marketing. As a review of current research in Bayesian analysis the book presents a balance between theory and applications. The lack of a clear demarcation between theoretical and applied research is a reflection of the highly interdisciplinary and often applied nature of research in Bayesian statistics. The book is intended as an update for researchers in Bayesian statistics, including non-statisticians who make use of Bayesian inference to address substantive research questions in other fields. It would also be useful for graduate students and research scholars in statistics or biostatistics who wish to acquaint themselves with current research frontiers.



Exploring Research Frontiers In Contemporary Statistics And Econometrics


Exploring Research Frontiers In Contemporary Statistics And Econometrics
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Author : Ingrid Van Keilegom
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-09-15

Exploring Research Frontiers In Contemporary Statistics And Econometrics written by Ingrid Van Keilegom and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-15 with Mathematics categories.


This book collects contributions written by well-known statisticians and econometricians to acknowledge Léopold Simar’s far-reaching scientific impact on Statistics and Econometrics throughout his career. The papers contained herein were presented at a conference in Louvain-la-Neuve in May 2009 in honor of his retirement. The contributions cover a broad variety of issues surrounding frontier estimation, which Léopold Simar has contributed much to over the past two decades, as well as related issues such as semiparametric regression and models for censored data. This book collects contributions written by well-known statisticians and econometricians to acknowledge Léopold Simar’s far-reaching scientific impact on Statistics and Econometrics throughout his career. The papers contained herein were presented at a conference in Louvain-la-Neuve in May 2009 in honor of his retirement. The contributions cover a broad variety of issues surrounding frontier estimation, which Léopold Simar has contributed much to over the past two decades, as well as related issues such as semiparametric regression and models for censored data.



New Developments In Biostatistics And Bioinformatics


New Developments In Biostatistics And Bioinformatics
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Author : Jianqing Fan
language : en
Publisher: World Scientific
Release Date : 2009

New Developments In Biostatistics And Bioinformatics written by Jianqing Fan and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with Mathematics categories.


This book presents an overview of recent developments in biostatistics and bioinformatics. Written by active researchers in these emerging areas, it is intended to give graduate students and new researchers an idea of where the frontiers of biostatistics and bioinformatics are as well as a forum to learn common techniques in use, so that they can advance the fields via developing new techniques and new results. Extensive references are provided so that researchers can follow the threads to learn more comprehensively what the literature is and to conduct their own research. In particulars, the book covers three important and rapidly advancing topics in biostatistics: analysis of survival and longitudinal data, statistical methods for epidemiology, and bioinformatics.



Bootstrap Methods


Bootstrap Methods
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Author : Michael R. Chernick
language : en
Publisher: John Wiley & Sons
Release Date : 2011-09-23

Bootstrap Methods written by Michael R. Chernick and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-23 with Mathematics categories.


A practical and accessible introduction to the bootstrap method——newly revised and updated Over the past decade, the application of bootstrap methods to new areas of study has expanded, resulting in theoretical and applied advances across various fields. Bootstrap Methods, Second Edition is a highly approachable guide to the multidisciplinary, real-world uses of bootstrapping and is ideal for readers who have a professional interest in its methods, but are without an advanced background in mathematics. Updated to reflect current techniques and the most up-to-date work on the topic, the Second Edition features: The addition of a second, extended bibliography devoted solely to publications from 1999–2007, which is a valuable collection of references on the latest research in the field A discussion of the new areas of applicability for bootstrap methods, including use in the pharmaceutical industry for estimating individual and population bioequivalence in clinical trials A revised chapter on when and why bootstrap fails and remedies for overcoming these drawbacks Added coverage on regression, censored data applications, P-value adjustment, ratio estimators, and missing data New examples and illustrations as well as extensive historical notes at the end of each chapter With a strong focus on application, detailed explanations of methodology, and complete coverage of modern developments in the field, Bootstrap Methods, Second Edition is an indispensable reference for applied statisticians, engineers, scientists, clinicians, and other practitioners who regularly use statistical methods in research. It is also suitable as a supplementary text for courses in statistics and resampling methods at the upper-undergraduate and graduate levels.



Frontiers In Massive Data Analysis


Frontiers In Massive Data Analysis
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Author : National Research Council
language : en
Publisher: National Academies Press
Release Date : 2013-10-03

Frontiers In Massive Data Analysis written by National Research Council and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-03 with Mathematics categories.


Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale-terabytes and petabytes-is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge-from computer science, statistics, machine learning, and application disciplines-that must be brought to bear to make useful inferences from massive data.