Nonparametric Curve Estimation from Time Series

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Publisher : Springer
ISBN 13 : 146123686X
Total Pages : 157 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Nonparametric Curve Estimation from Time Series by : Lazlo Györfi

Download or read book Nonparametric Curve Estimation from Time Series written by Lazlo Györfi and published by Springer. This book was released on 2013-12-21 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt: Because of the sheer size and scope of the plastics industry, the title Developments in Plastics Technology now covers an incredibly wide range of subjects or topics. No single volume can survey the whole field in any depth and what follows is, therefore, a series of chapters on selected topics. The topics were selected by us, the editors, because of their immediate relevance to the plastics industry. When one considers the advancements of the plastics processing machinery (in terms of its speed of operation and conciseness of control), it was felt that several chapters should be included which related to the types of control systems used and the correct usage of hydraulics. The importance of using cellular, rubber-modified and engineering-type plastics has had a major impact on the plastics industry and therefore a chapter on each of these subjects has been included. The two remaining chapters are on the characterisation and behaviour of polymer structures, both subjects again being of current academic or industrial interest. Each of the contributions was written by a specialist in that field and to them all, we, the editors, extend our heartfelt thanks, as writing a contribution for a book such as this, while doing a full-time job, is no easy task.

Nonparametric Curve Estimation

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Author :
Publisher : Springer Science & Business Media
ISBN 13 : 0387226389
Total Pages : 423 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Nonparametric Curve Estimation by : Sam Efromovich

Download or read book Nonparametric Curve Estimation written by Sam Efromovich and published by Springer Science & Business Media. This book was released on 2008-01-19 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives a systematic, comprehensive, and unified account of modern nonparametric statistics of density estimation, nonparametric regression, filtering signals, and time series analysis. The companion software package, available over the Internet, brings all of the discussed topics into the realm of interactive research. Virtually every claim and development mentioned in the book is illustrated with graphs which are available for the reader to reproduce and modify, making the material fully transparent and allowing for complete interactivity.

Nonparametric Curve Estimation from Time Series

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Publisher :
ISBN 13 : 9781461236870
Total Pages : 168 pages
Book Rating : 4.2/5 (368 download)

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Book Synopsis Nonparametric Curve Estimation from Time Series by : Lazlo Gyorfi

Download or read book Nonparametric Curve Estimation from Time Series written by Lazlo Gyorfi and published by . This book was released on 2014-09-01 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Nonparametric Curve Estimation from Time Series

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Publisher :
ISBN 13 : 9783540971740
Total Pages : 153 pages
Book Rating : 4.9/5 (717 download)

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Book Synopsis Nonparametric Curve Estimation from Time Series by : László Györfi

Download or read book Nonparametric Curve Estimation from Time Series written by László Györfi and published by . This book was released on 1989 with total page 153 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Missing and Modified Data in Nonparametric Estimation

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Publisher : CRC Press
ISBN 13 : 135167983X
Total Pages : 867 pages
Book Rating : 4.3/5 (516 download)

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Book Synopsis Missing and Modified Data in Nonparametric Estimation by : Sam Efromovich

Download or read book Missing and Modified Data in Nonparametric Estimation written by Sam Efromovich and published by CRC Press. This book was released on 2018-03-12 with total page 867 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a systematic and unified approach for modern nonparametric treatment of missing and modified data via examples of density and hazard rate estimation, nonparametric regression, filtering signals, and time series analysis. All basic types of missing at random and not at random, biasing, truncation, censoring, and measurement errors are discussed, and their treatment is explained. Ten chapters of the book cover basic cases of direct data, biased data, nondestructive and destructive missing, survival data modified by truncation and censoring, missing survival data, stationary and nonstationary time series and processes, and ill-posed modifications. The coverage is suitable for self-study or a one-semester course for graduate students with a prerequisite of a standard course in introductory probability. Exercises of various levels of difficulty will be helpful for the instructor and self-study. The book is primarily about practically important small samples. It explains when consistent estimation is possible, and why in some cases missing data should be ignored and why others must be considered. If missing or data modification makes consistent estimation impossible, then the author explains what type of action is needed to restore the lost information. The book contains more than a hundred figures with simulated data that explain virtually every setting, claim, and development. The companion R software package allows the reader to verify, reproduce and modify every simulation and used estimators. This makes the material fully transparent and allows one to study it interactively. Sam Efromovich is the Endowed Professor of Mathematical Sciences and the Head of the Actuarial Program at the University of Texas at Dallas. He is well known for his work on the theory and application of nonparametric curve estimation and is the author of Nonparametric Curve Estimation: Methods, Theory, and Applications. Professor Sam Efromovich is a Fellow of the Institute of Mathematical Statistics and the American Statistical Association.

Nonparametric Curve Estimation

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Publisher :
ISBN 13 : 9781475773002
Total Pages : 432 pages
Book Rating : 4.7/5 (73 download)

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Book Synopsis Nonparametric Curve Estimation by : Sam Efromovich

Download or read book Nonparametric Curve Estimation written by Sam Efromovich and published by . This book was released on 2014-01-15 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Nonlinear Time Series

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Publisher : Springer Science & Business Media
ISBN 13 : 0387693955
Total Pages : 565 pages
Book Rating : 4.3/5 (876 download)

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Book Synopsis Nonlinear Time Series by : Jianqing Fan

Download or read book Nonlinear Time Series written by Jianqing Fan and published by Springer Science & Business Media. This book was released on 2008-09-11 with total page 565 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book that integrates useful parametric and nonparametric techniques with time series modeling and prediction, the two important goals of time series analysis. Such a book will benefit researchers and practitioners in various fields such as econometricians, meteorologists, biologists, among others who wish to learn useful time series methods within a short period of time. The book also intends to serve as a reference or text book for graduate students in statistics and econometrics.

Nonlinear Time Series

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Publisher : CRC Press
ISBN 13 : 1420011219
Total Pages : 249 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Nonlinear Time Series by : Jiti Gao

Download or read book Nonlinear Time Series written by Jiti Gao and published by CRC Press. This book was released on 2007-03-22 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: Useful in the theoretical and empirical analysis of nonlinear time series data, semiparametric methods have received extensive attention in the economics and statistics communities over the past twenty years. Recent studies show that semiparametric methods and models may be applied to solve dimensionality reduction problems arising from using fully

Flexible Nonparametric Curve Estimation

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Publisher : Springer
ISBN 13 : 9783031665004
Total Pages : 0 pages
Book Rating : 4.6/5 (65 download)

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Book Synopsis Flexible Nonparametric Curve Estimation by : Hassan Doosti

Download or read book Flexible Nonparametric Curve Estimation written by Hassan Doosti and published by Springer. This book was released on 2024-10-09 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book delves into the realm of nonparametric estimations, offering insights into essential notions such as probability density, regression, Tsallis Entropy, Residual Tsallis Entropy, and intensity functions. Through a series of carefully crafted chapters, the theoretical foundations of flexible nonparametric estimators are examined, complemented by comprehensive numerical studies. From theorem elucidation to practical applications, the text provides a deep dive into the intricacies of nonparametric curve estimation. Tailored for postgraduate students and researchers seeking to expand their understanding of nonparametric statistics, this book will serve as a valuable resource for anyone who wishes to explore the applications of flexible nonparametric techniques.

Statistical Analysis and Forecasting of Economic Structural Change

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Publisher : Springer Science & Business Media
ISBN 13 : 366202571X
Total Pages : 495 pages
Book Rating : 4.6/5 (62 download)

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Book Synopsis Statistical Analysis and Forecasting of Economic Structural Change by : Peter Hackl

Download or read book Statistical Analysis and Forecasting of Economic Structural Change written by Peter Hackl and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 495 pages. Available in PDF, EPUB and Kindle. Book excerpt: In 1984, the University of Bonn (FRG) and the International Institute for Applied System Analysis (IIASA) in Laxenburg (Austria), created a joint research group to analyze the relationship between economic growth and structural change. The research team was to examine the commodity composition as well as the size and direction of commodity and credit flows among countries and regions. Krelle (1988) reports on the results of this "Bonn-IIASA" research project. At the same time, an informal IIASA Working Group was initiated to deal with prob lems of the statistical analysis of economic data in the context of structural change: What tools do we have to identify nonconstancy of model parameters? What type of models are particularly applicable to nonconstant structure? How is forecasting affected by the presence of nonconstant structure? What problems should be anticipated in applying these tools and models? Some 50 experts, mainly statisticians or econometricians from about 15 countries, came together in Lodz, Poland (May 1985); Berlin, GDR (June 1986); and Sulejov, Poland (September 1986) to present and discuss their findings. This volume contains a selected set of those conference contributions as well as several specially invited chapters.

Stochastic Curve Estimation

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Publisher : IMS
ISBN 13 : 9780940600225
Total Pages : 202 pages
Book Rating : 4.6/5 (2 download)

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Book Synopsis Stochastic Curve Estimation by : Murray Rosenblatt

Download or read book Stochastic Curve Estimation written by Murray Rosenblatt and published by IMS. This book was released on 1991 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Nonparametric Functional Estimation and Related Topics

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Publisher : Springer Science & Business Media
ISBN 13 : 9780792312260
Total Pages : 732 pages
Book Rating : 4.3/5 (122 download)

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Book Synopsis Nonparametric Functional Estimation and Related Topics by : George Roussas

Download or read book Nonparametric Functional Estimation and Related Topics written by George Roussas and published by Springer Science & Business Media. This book was released on 1991-04-30 with total page 732 pages. Available in PDF, EPUB and Kindle. Book excerpt: About three years ago, an idea was discussed among some colleagues in the Division of Statistics at the University of California, Davis, as to the possibility of holding an international conference, focusing exclusively on nonparametric curve estimation. The fruition of this idea came about with the enthusiastic support of this project by Luc Devroye of McGill University, Canada, and Peter Robinson of the London School of Economics, UK. The response of colleagues, contacted to ascertain interest in participation in such a conference, was gratifying and made the effort involved worthwhile. Devroye and Robinson, together with this editor and George Metakides of the University of Patras, Greece and of the European Economic Communities, Brussels, formed the International Organizing Committee for a two week long Advanced Study Institute (ASI) sponsored by the Scientific Affairs Division of the North Atlantic Treaty Organization (NATO). The ASI was held on the Greek Island of Spetses between July 29 and August 10, 1990. Nonparametric functional estimation is a central topic in statistics, with applications in numerous substantive fields in mathematics, natural and social sciences, engineering and medicine. While there has been interest in nonparametric functional estimation for many years, this has grown of late, owing to increasing availability of large data sets and the ability to process them by means of improved computing facilities, along with the ability to display the results by means of sophisticated graphical procedures.

The Analysis of Nonstationary Time Series and Curve Estimation with Locally Stationary Models

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Publisher :
ISBN 13 :
Total Pages : 56 pages
Book Rating : 4.:/5 (491 download)

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Book Synopsis The Analysis of Nonstationary Time Series and Curve Estimation with Locally Stationary Models by : Rainer Dahlhaus

Download or read book The Analysis of Nonstationary Time Series and Curve Estimation with Locally Stationary Models written by Rainer Dahlhaus and published by . This book was released on 1997 with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Asymptotics, Nonparametrics, and Time Series

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Publisher : CRC Press
ISBN 13 : 9780824700515
Total Pages : 864 pages
Book Rating : 4.7/5 (5 download)

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Book Synopsis Asymptotics, Nonparametrics, and Time Series by : Subir Ghosh

Download or read book Asymptotics, Nonparametrics, and Time Series written by Subir Ghosh and published by CRC Press. This book was released on 1999-02-18 with total page 864 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Contains over 2500 equations and exhaustively covers not only nonparametrics but also parametric, semiparametric, frequentist, Bayesian, bootstrap, adaptive, univariate, and multivariate statistical methods, as well as practical uses of Markov chain models."

Nonparametric Statistics

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Publisher : Springer Nature
ISBN 13 : 3030573060
Total Pages : 547 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Nonparametric Statistics by : Michele La Rocca

Download or read book Nonparametric Statistics written by Michele La Rocca and published by Springer Nature. This book was released on 2020-11-11 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: Highlighting the latest advances in nonparametric and semiparametric statistics, this book gathers selected peer-reviewed contributions presented at the 4th Conference of the International Society for Nonparametric Statistics (ISNPS), held in Salerno, Italy, on June 11-15, 2018. It covers theory, methodology, applications and computational aspects, addressing topics such as nonparametric curve estimation, regression smoothing, models for time series and more generally dependent data, varying coefficient models, symmetry testing, robust estimation, and rank-based methods for factorial design. It also discusses nonparametric and permutation solutions for several different types of data, including ordinal data, spatial data, survival data and the joint modeling of both longitudinal and time-to-event data, permutation and resampling techniques, and practical applications of nonparametric statistics. The International Society for Nonparametric Statistics is a unique global organization, and its international conferences are intended to foster the exchange of ideas and the latest advances and trends among researchers from around the world and to develop and disseminate nonparametric statistics knowledge. The ISNPS 2018 conference in Salerno was organized with the support of the American Statistical Association, the Institute of Mathematical Statistics, the Bernoulli Society for Mathematical Statistics and Probability, the Journal of Nonparametric Statistics and the University of Salerno.

A Course in Time Series Analysis

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Publisher : John Wiley & Sons
ISBN 13 : 1118031229
Total Pages : 494 pages
Book Rating : 4.1/5 (18 download)

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Book Synopsis A Course in Time Series Analysis by : Daniel Peña

Download or read book A Course in Time Series Analysis written by Daniel Peña and published by John Wiley & Sons. This book was released on 2011-01-25 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: New statistical methods and future directions of research in time series A Course in Time Series Analysis demonstrates how to build time series models for univariate and multivariate time series data. It brings together material previously available only in the professional literature and presents a unified view of the most advanced procedures available for time series model building. The authors begin with basic concepts in univariate time series, providing an up-to-date presentation of ARIMA models, including the Kalman filter, outlier analysis, automatic methods for building ARIMA models, and signal extraction. They then move on to advanced topics, focusing on heteroscedastic models, nonlinear time series models, Bayesian time series analysis, nonparametric time series analysis, and neural networks. Multivariate time series coverage includes presentations on vector ARMA models, cointegration, and multivariate linear systems. Special features include: Contributions from eleven of the worldâ??s leading figures in time series Shared balance between theory and application Exercise series sets Many real data examples Consistent style and clear, common notation in all contributions 60 helpful graphs and tables Requiring no previous knowledge of the subject, A Course in Time Series Analysis is an important reference and a highly useful resource for researchers and practitioners in statistics, economics, business, engineering, and environmental analysis. An Instructor's Manual presenting detailed solutions to all the problems in he book is available upon request from the Wiley editorial department.

Selecting Models from Data

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Publisher : Springer Science & Business Media
ISBN 13 : 1461226600
Total Pages : 475 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Selecting Models from Data by : P. Cheeseman

Download or read book Selecting Models from Data written by P. Cheeseman and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is a selection of papers presented at the Fourth International Workshop on Artificial Intelligence and Statistics held in January 1993. These biennial workshops have succeeded in bringing together researchers from Artificial Intelligence and from Statistics to discuss problems of mutual interest. The exchange has broadened research in both fields and has strongly encour aged interdisciplinary work. The theme ofthe 1993 AI and Statistics workshop was: "Selecting Models from Data". The papers in this volume attest to the diversity of approaches to model selection and to the ubiquity of the problem. Both statistics and artificial intelligence have independently developed approaches to model selection and the corresponding algorithms to implement them. But as these papers make clear, there is a high degree of overlap between the different approaches. In particular, there is agreement that the fundamental problem is the avoidence of "overfitting"-Le., where a model fits the given data very closely, but is a poor predictor for new data; in other words, the model has partly fitted the "noise" in the original data.