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Author : Emanuel Parzen
Publisher :
ISBN 13 : 9781461216957
Total Pages : 448 pages
Book Rating : 4.2/5 (169 download)
Download or read book Selected Papers of Hirotugu Akaike written by Emanuel Parzen and published by . This book was released on 1997-12-12 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Hirotsugu Akaike
Publisher : Springer Science & Business Media
ISBN 13 : 0387983554
Total Pages : 448 pages
Book Rating : 4.3/5 (879 download)
Download or read book Selected Papers of Hirotugu Akaike written by Hirotsugu Akaike and published by Springer Science & Business Media. This book was released on 1998 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hirotugu Akaike is an internationally renowned researcher who profoundly affected how data and time-series are analyzed and modeled. His pioneering work is highly regarded and his talc method is frequently cited and applied in almost every area of the physical and social sciences. This book includes groundbreaking papers representing successive phases of Akaike's research which spanned more than 40 years.
Author : Emanuel Parzen
Publisher : Springer Science & Business Media
ISBN 13 : 146121694X
Total Pages : 432 pages
Book Rating : 4.4/5 (612 download)
Download or read book Selected Papers of Hirotugu Akaike written by Emanuel Parzen and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: The pioneering research of Hirotugu Akaike has an international reputation for profoundly affecting how data and time series are analyzed and modelled and is highly regarded by the statistical and technological communities of Japan and the world. His 1974 paper "A new look at the statistical model identification" (IEEE Trans Automatic Control, AC-19, 716-723) is one of the most frequently cited papers in the area of engineering, technology, and applied sciences (according to a 1981 Citation Classic of the Institute of Scientific Information). It introduced the broad scientific community to model identification using the methods of Akaike's criterion AIC. The AIC method is cited and applied in almost every area of physical and social science. The best way to learn about the seminal ideas of pioneering researchers is to read their original papers. This book reprints 29 papers of Akaike's more than 140 papers. This book of papers by Akaike is a tribute to his outstanding career and a service to provide students and researchers with access to Akaike's innovative and influential ideas and applications. To provide a commentary on the career of Akaike, the motivations of his ideas, and his many remarkable honors and prizes, this book reprints "A Conversation with Hirotugu Akaike" by David F. Findley and Emanuel Parzen, published in 1995 in the journal Statistical Science. This survey of Akaike's career provides each of us with a role model for how to have an impact on society by stimulating applied researchers to implement new statistical methods.
Author : Emanuel Parzen
Publisher : Springer
ISBN 13 : 9781461272489
Total Pages : 434 pages
Book Rating : 4.2/5 (724 download)
Download or read book Selected Papers of Hirotugu Akaike written by Emanuel Parzen and published by Springer. This book was released on 2012-10-23 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: The pioneering research of Hirotugu Akaike has an international reputation for profoundly affecting how data and time series are analyzed and modelled and is highly regarded by the statistical and technological communities of Japan and the world. His 1974 paper "A new look at the statistical model identification" (IEEE Trans Automatic Control, AC-19, 716-723) is one of the most frequently cited papers in the area of engineering, technology, and applied sciences (according to a 1981 Citation Classic of the Institute of Scientific Information). It introduced the broad scientific community to model identification using the methods of Akaike's criterion AIC. The AIC method is cited and applied in almost every area of physical and social science. The best way to learn about the seminal ideas of pioneering researchers is to read their original papers. This book reprints 29 papers of Akaike's more than 140 papers. This book of papers by Akaike is a tribute to his outstanding career and a service to provide students and researchers with access to Akaike's innovative and influential ideas and applications. To provide a commentary on the career of Akaike, the motivations of his ideas, and his many remarkable honors and prizes, this book reprints "A Conversation with Hirotugu Akaike" by David F. Findley and Emanuel Parzen, published in 1995 in the journal Statistical Science. This survey of Akaike's career provides each of us with a role model for how to have an impact on society by stimulating applied researchers to implement new statistical methods.
Author : David L. Weakliem
Publisher : Guilford Publications
ISBN 13 : 1462525652
Total Pages : 217 pages
Book Rating : 4.4/5 (625 download)
Download or read book Hypothesis Testing and Model Selection in the Social Sciences written by David L. Weakliem and published by Guilford Publications. This book was released on 2016-04-25 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: Examining the major approaches to hypothesis testing and model selection, this book blends statistical theory with recommendations for practice, illustrated with real-world social science examples. It systematically compares classical (frequentist) and Bayesian approaches, showing how they are applied, exploring ways to reconcile the differences between them, and evaluating key controversies and criticisms. The book also addresses the role of hypothesis testing in the evaluation of theories, the relationship between hypothesis tests and confidence intervals, and the role of prior knowledge in Bayesian estimation and Bayesian hypothesis testing. Two easily calculated alternatives to standard hypothesis tests are discussed in depth: the Akaike information criterion (AIC) and Bayesian information criterion (BIC). The companion website ([ital]www.guilford.com/weakliem-materials[/ital]) supplies data and syntax files for the book's examples.
Author : Kenneth P. Burnham
Publisher : Springer Science & Business Media
ISBN 13 : 0387224564
Total Pages : 488 pages
Book Rating : 4.3/5 (872 download)
Download or read book Model Selection and Multimodel Inference written by Kenneth P. Burnham and published by Springer Science & Business Media. This book was released on 2007-05-28 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unique and comprehensive text on the philosophy of model-based data analysis and strategy for the analysis of empirical data. The book introduces information theoretic approaches and focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. It contains several new approaches to estimating model selection uncertainty and incorporating selection uncertainty into estimates of precision. An array of examples is given to illustrate various technical issues. The text has been written for biologists and statisticians using models for making inferences from empirical data.
Author : Kenneth P. Burnham
Publisher : Springer Science & Business Media
ISBN 13 : 1475729170
Total Pages : 373 pages
Book Rating : 4.4/5 (757 download)
Download or read book Model Selection and Inference written by Kenneth P. Burnham and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statisticians and applied scientists must often select a model to fit empirical data. This book discusses the philosophy and strategy of selecting such a model using the information theory approach pioneered by Hirotugu Akaike. This approach focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. The book includes practical applications in biology and environmental science.
Author : Avadhesh Kumar
Publisher : CRC Press
ISBN 13 : 1000484211
Total Pages : 232 pages
Book Rating : 4.0/5 (4 download)
Download or read book Prediction and Analysis for Knowledge Representation and Machine Learning written by Avadhesh Kumar and published by CRC Press. This book was released on 2022-01-31 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: A number of approaches are being defined for statistics and machine learning. These approaches are used for the identification of the process of the system and the models created from the system’s perceived data, assisting scientists in the generation or refinement of current models. Machine learning is being studied extensively in science, particularly in bioinformatics, economics, social sciences, ecology, and climate science, but learning from data individually needs to be researched more for complex scenarios. Advanced knowledge representation approaches that can capture structural and process properties are necessary to provide meaningful knowledge to machine learning algorithms. It has a significant impact on comprehending difficult scientific problems. Prediction and Analysis for Knowledge Representation and Machine Learning demonstrates various knowledge representation and machine learning methodologies and architectures that will be active in the research field. The approaches are reviewed with real-life examples from a wide range of research topics. An understanding of a number of techniques and algorithms that are implemented in knowledge representation in machine learning is available through the book’s website. Features: Examines the representational adequacy of needed knowledge representation Manipulates inferential adequacy for knowledge representation in order to produce new knowledge derived from the original information Improves inferential and acquisition efficiency by applying automatic methods to acquire new knowledge Covers the major challenges, concerns, and breakthroughs in knowledge representation and machine learning using the most up-to-date technology Describes the ideas of knowledge representation and related technologies, as well as their applications, in order to help humankind become better and smarter This book serves as a reference book for researchers and practitioners who are working in the field of information technology and computer science in knowledge representation and machine learning for both basic and advanced concepts. Nowadays, it has become essential to develop adaptive, robust, scalable, and reliable applications and also design solutions for day-to-day problems. The edited book will be helpful for industry people and will also help beginners as well as high-level users for learning the latest things, which includes both basic and advanced concepts.
Author : Yinglin Xia
Publisher : Springer Nature
ISBN 13 : 3031213912
Total Pages : 717 pages
Book Rating : 4.0/5 (312 download)
Download or read book Bioinformatic and Statistical Analysis of Microbiome Data written by Yinglin Xia and published by Springer Nature. This book was released on 2023-06-16 with total page 717 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique book addresses the bioinformatic and statistical modelling and also the analysis of microbiome data using cutting-edge QIIME 2 and R software. It covers core analysis topics in both bioinformatics and statistics, which provides a complete workflow for microbiome data analysis: from raw sequencing reads to community analysis and statistical hypothesis testing. It includes real-world data from the authors’ research and from the public domain, and discusses the implementation of QIIME 2 and R for data analysis step-by-step. The data as well as QIIME 2 and R computer programs are publicly available, allowing readers to replicate the model development and data analysis presented in each chapter so that these new methods can be readily applied in their own research. Bioinformatic and Statistical Analysis of Microbiome Data is an ideal book for advanced graduate students and researchers in the clinical, biomedical, agricultural, and environmental fields, as well as those studying bioinformatics, statistics, and big data analysis.
Author : G. Rajakumar
Publisher : Springer Nature
ISBN 13 : 9819917670
Total Pages : 923 pages
Book Rating : 4.8/5 (199 download)
Download or read book Intelligent Communication Technologies and Virtual Mobile Networks written by G. Rajakumar and published by Springer Nature. This book was released on 2023-06-01 with total page 923 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is a collection of high-quality research papers presented at Intelligent Communication Technologies and Virtual Mobile Networks (ICICV 2023), held at Francis Xavier Engineering College, Tirunelveli, Tamil Nadu, India, during February 16–17, 2023. The book shares knowledge and results in theory, methodology, and applications of communication technology and mobile networks. The book covers innovative and cutting-edge work of researchers, developers, and practitioners from academia and industry working in the area of computer networks, network protocols and wireless networks, data communication technologies, and network security.
Author : Miguel R. D. Rodrigues
Publisher : Cambridge University Press
ISBN 13 : 1108427138
Total Pages : 561 pages
Book Rating : 4.1/5 (84 download)
Download or read book Information-Theoretic Methods in Data Science written by Miguel R. D. Rodrigues and published by Cambridge University Press. This book was released on 2021-04-08 with total page 561 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first unified treatment of the interface between information theory and emerging topics in data science, written in a clear, tutorial style. Covering topics such as data acquisition, representation, analysis, and communication, it is ideal for graduate students and researchers in information theory, signal processing, and machine learning.
Author : David R. Anderson
Publisher : Springer Science & Business Media
ISBN 13 : 0387740759
Total Pages : 184 pages
Book Rating : 4.3/5 (877 download)
Download or read book Model Based Inference in the Life Sciences written by David R. Anderson and published by Springer Science & Business Media. This book was released on 2007-12-22 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook introduces a science philosophy called "information theoretic" based on Kullback-Leibler information theory. It focuses on a science philosophy based on "multiple working hypotheses" and statistical models to represent them. The text is written for people new to the information-theoretic approaches to statistical inference, whether graduate students, post-docs, or professionals. Readers are however expected to have a background in general statistical principles, regression analysis, and some exposure to likelihood methods. This is not an elementary text as it assumes reasonable competence in modeling and parameter estimation.
Author : Attilio Meucci
Publisher : Springer Science & Business Media
ISBN 13 : 3642009646
Total Pages : 547 pages
Book Rating : 4.6/5 (42 download)
Download or read book Risk and Asset Allocation written by Attilio Meucci and published by Springer Science & Business Media. This book was released on 2009-05-22 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discusses in the practical and theoretical aspects of one-period asset allocation, i.e. market Modeling, invariants estimation, portfolia evaluation, and portfolio optimization in the prexence of estimation risk The book is software based, many of the exercises simulate in Matlab the solution to practical problems and can be downloaded from the book's web-site
Author : Simon M. Lin
Publisher : Springer Science & Business Media
ISBN 13 : 1461508738
Total Pages : 192 pages
Book Rating : 4.4/5 (615 download)
Download or read book Methods of Microarray Data Analysis written by Simon M. Lin and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: Microarray technology is a major experimental tool for functional genomic explorations, and will continue to be a major tool throughout this decade and beyond. The recent explosion of this technology threatens to overwhelm the scientific community with massive quantities of data. Because microarray data analysis is an emerging field, very few analytical models currently exist. Methods of Microarray Data Analysis is one of the first books dedicated to this exciting new field. In a single reference, readers can learn about the most up-to-date methods ranging from data normalization, feature selection and discriminative analysis to machine learning techniques. Currently, there are no standard procedures for the design and analysis of microarray experiments. Methods of Microarray Data Analysis focuses on two well-known data sets, using a different method of analysis in each chapter. Real examples expose the strengths and weaknesses of each method for a given situation, aimed at helping readers choose appropriate protocols and utilize them for their own data set. In addition, web links are provided to the programs and tools discussed in several chapters. This book is an excellent reference not only for academic and industrial researchers, but also for core bioinformatics/genomics courses in undergraduate and graduate programs.
Author : H. Akaike
Publisher : Springer
ISBN 13 : 9027727864
Total Pages : 228 pages
Book Rating : 4.0/5 (277 download)
Download or read book Statistical Analysis and Control of Dynamic Systems written by H. Akaike and published by Springer. This book was released on 1989-02-28 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : David Brillinger
Publisher : Springer Science & Business Media
ISBN 13 : 1461229626
Total Pages : 262 pages
Book Rating : 4.4/5 (612 download)
Download or read book Time Series Analysis and Applications to Geophysical Systems written by David Brillinger and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: Part of a two volume set based on a recent IMA program of the same name. The goal of the program and these books is to develop a community of statistical and other scientists kept up-to-date on developments in this quickly evolving and interdisciplinary field. Consequently, these books present recent material by distinguished researchers. Topics discussed in Part I include nonlinear and non- Gaussian models and processes (higher order moments and spectra, nonlinear systems, applications in astronomy, geophysics, engineering, and simulation) and the interaction of time series analysis and statistics (information model identification, categorical valued time series, nonparametric and semiparametric methods). Self-similar processes and long-range dependence (time series with long memory, fractals, 1/f noise, stable noise) and time series research common to engineers and economists (modeling of multivariate and possibly non-stationary time series, state space and adaptive methods) are discussed in Part II.
Author : Enders Anthony Robinson
Publisher : Springer Science & Business Media
ISBN 13 : 9780387223117
Total Pages : 282 pages
Book Rating : 4.2/5 (231 download)
Download or read book Time Series Analysis and Applications to Geophysical Systems written by Enders Anthony Robinson and published by Springer Science & Business Media. This book was released on 2004-09-17 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Time series methods are essential tools in the analysis of many geophysical systems. This volume, which consists of papers presented by a select, international group of statistical and geophysical experts at a Workshop on Time Series Analysis and Applications to Geophysical Systems at the Institute for Mathematics and its Applications (IMA) at the University of Minnesota from November 12-15, 2001 as part of the IMA's Thematic Year on Mathematics in the Geosciences, explores the application of recent advances in time series methodology to a host of important problems ranging from climate change to seismology. The works in the volume deal with theoretical and methodological issues as well as real geophysical applications, and are written with both statistical and geophysical audiences in mind. Important contributions to time series modeling, estimation, prediction, and deconvolution are presented. The results are applied to a wide range of geophysical applications including the investigation and prediction of climatic variations, the interpretation of seismic signals, the estimation of flooding risk, the description of permeability in Chinese oil fields, and the modeling of NOx decomposition from thermal power plants.
