Recent Advances In Estimating Nonlinear Models

Download Recent Advances In Estimating Nonlinear Models full books in PDF, epub, and Kindle. Read online Recent Advances In Estimating Nonlinear Models ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Recent Advances in Estimating Nonlinear Models

Author : Jun Ma
Publisher : Springer Science & Business Media
ISBN 13 : 1461480604
Total Pages : 308 pages
Book Rating : 4.4/5 (614 download)

DOWNLOAD NOW!

Book Synopsis Recent Advances in Estimating Nonlinear Models by : Jun Ma

Download or read book Recent Advances in Estimating Nonlinear Models written by Jun Ma and published by Springer Science & Business Media. This book was released on 2013-09-24 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear models have been used extensively in the areas of economics and finance. Recent literature on the topic has shown that a large number of series exhibit nonlinear dynamics as opposed to the alternative--linear dynamics. Incorporating these concepts involves deriving and estimating nonlinear time series models, and these have typically taken the form of Threshold Autoregression (TAR) models, Exponential Smooth Transition (ESTAR) models, and Markov Switching (MS) models, among several others. This edited volume provides a timely overview of nonlinear estimation techniques, offering new methods and insights into nonlinear time series analysis. It features cutting-edge research from leading academics in economics, finance, and business management, and will focus on such topics as Zero-Information-Limit-Conditions, using Markov Switching Models to analyze economics series, and how best to distinguish between competing nonlinear models. Principles and techniques in this book will appeal to econometricians, finance professors teaching quantitative finance, researchers, and graduate students interested in learning how to apply advances in nonlinear time series modeling to solve complex problems in economics and finance.

Nonlinear Models for Repeated Measurement Data

Author : Marie Davidian
Publisher : Routledge
ISBN 13 : 1351428152
Total Pages : 360 pages
Book Rating : 4.3/5 (514 download)

DOWNLOAD NOW!

Book Synopsis Nonlinear Models for Repeated Measurement Data by : Marie Davidian

Download or read book Nonlinear Models for Repeated Measurement Data written by Marie Davidian and published by Routledge. This book was released on 2017-11-01 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear measurement data arise in a wide variety of biological and biomedical applications, such as longitudinal clinical trials, studies of drug kinetics and growth, and the analysis of assay and laboratory data. Nonlinear Models for Repeated Measurement Data provides the first unified development of methods and models for data of this type, with a detailed treatment of inference for the nonlinear mixed effects and its extensions. A particular strength of the book is the inclusion of several detailed case studies from the areas of population pharmacokinetics and pharmacodynamics, immunoassay and bioassay development and the analysis of growth curves.

Perspectives and advances in parameter estimation of nonlinear models

Author : Milena Clarissa Cuéllar Sánchez
Publisher :
ISBN 13 :
Total Pages : 684 pages
Book Rating : 4.:/5 (1 download)

DOWNLOAD NOW!

Book Synopsis Perspectives and advances in parameter estimation of nonlinear models by : Milena Clarissa Cuéllar Sánchez

Download or read book Perspectives and advances in parameter estimation of nonlinear models written by Milena Clarissa Cuéllar Sánchez and published by . This book was released on 2007 with total page 684 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Adaptive Learning Methods for Nonlinear System Modeling

Author : Danilo Comminiello
Publisher : Butterworth-Heinemann
ISBN 13 : 0128129778
Total Pages : 390 pages
Book Rating : 4.1/5 (281 download)

DOWNLOAD NOW!

Book Synopsis Adaptive Learning Methods for Nonlinear System Modeling by : Danilo Comminiello

Download or read book Adaptive Learning Methods for Nonlinear System Modeling written by Danilo Comminiello and published by Butterworth-Heinemann. This book was released on 2018-06-11 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive Learning Methods for Nonlinear System Modeling presents some of the recent advances on adaptive algorithms and machine learning methods designed for nonlinear system modeling and identification. Real-life problems always entail a certain degree of nonlinearity, which makes linear models a non-optimal choice. This book mainly focuses on those methodologies for nonlinear modeling that involve any adaptive learning approaches to process data coming from an unknown nonlinear system. By learning from available data, such methods aim at estimating the nonlinearity introduced by the unknown system. In particular, the methods presented in this book are based on online learning approaches, which process the data example-by-example and allow to model even complex nonlinearities, e.g., showing time-varying and dynamic behaviors. Possible fields of applications of such algorithms includes distributed sensor networks, wireless communications, channel identification, predictive maintenance, wind prediction, network security, vehicular networks, active noise control, information forensics and security, tracking control in mobile robots, power systems, and nonlinear modeling in big data, among many others. This book serves as a crucial resource for researchers, PhD and post-graduate students working in the areas of machine learning, signal processing, adaptive filtering, nonlinear control, system identification, cooperative systems, computational intelligence. This book may be also of interest to the industry market and practitioners working with a wide variety of nonlinear systems. Presents the key trends and future perspectives in the field of nonlinear signal processing and adaptive learning. Introduces novel solutions and improvements over the state-of-the-art methods in the very exciting area of online and adaptive nonlinear identification. Helps readers understand important methods that are effective in nonlinear system modelling, suggesting the right methodology to address particular issues.

Nonlinear Regression Analysis and Its Applications

Author : Douglas M. Bates
Publisher : Wiley-Interscience
ISBN 13 :
Total Pages : 398 pages
Book Rating : 4.:/5 (318 download)

DOWNLOAD NOW!

Book Synopsis Nonlinear Regression Analysis and Its Applications by : Douglas M. Bates

Download or read book Nonlinear Regression Analysis and Its Applications written by Douglas M. Bates and published by Wiley-Interscience. This book was released on 2007-04-23 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides a presentation of the theoretical, practical, and computational aspects of nonlinear regression. There is background material on linear regression, including a geometrical development for linear and nonlinear least squares.

Nonlinear Modeling

Author : Johan A.K. Suykens
Publisher : Springer Science & Business Media
ISBN 13 : 1461557038
Total Pages : 265 pages
Book Rating : 4.4/5 (615 download)

DOWNLOAD NOW!

Book Synopsis Nonlinear Modeling by : Johan A.K. Suykens

Download or read book Nonlinear Modeling written by Johan A.K. Suykens and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 265 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear Modeling: Advanced Black-Box Techniques discusses methods on Neural nets and related model structures for nonlinear system identification; Enhanced multi-stream Kalman filter training for recurrent networks; The support vector method of function estimation; Parametric density estimation for the classification of acoustic feature vectors in speech recognition; Wavelet-based modeling of nonlinear systems; Nonlinear identification based on fuzzy models; Statistical learning in control and matrix theory; Nonlinear time-series analysis. It also contains the results of the K.U. Leuven time series prediction competition, held within the framework of an international workshop at the K.U. Leuven, Belgium in July 1998.

Nonlinear Regression

Author : George A. F. Seber
Publisher : John Wiley & Sons
ISBN 13 : 0471725307
Total Pages : 768 pages
Book Rating : 4.4/5 (717 download)

DOWNLOAD NOW!

Book Synopsis Nonlinear Regression by : George A. F. Seber

Download or read book Nonlinear Regression written by George A. F. Seber and published by John Wiley & Sons. This book was released on 2005-02-25 with total page 768 pages. Available in PDF, EPUB and Kindle. Book excerpt: WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. From the Reviews of Nonlinear Regression "A very good book and an important one in that it is likely to become a standard reference for all interested in nonlinear regression; and I would imagine that any statistician concerned with nonlinear regression would want a copy on his shelves." –The Statistician "Nonlinear Regression also includes a reference list of over 700 entries. The compilation of this material and cross-referencing of it is one of the most valuable aspects of the book. Nonlinear Regression can provide the researcher unfamiliar with a particular specialty area of nonlinear regression an introduction to that area of nonlinear regression and access to the appropriate references . . . Nonlinear Regression provides by far the broadest discussion of nonlinear regression models currently available and will be a valuable addition to the library of anyone interested in understanding and using such models including the statistical researcher." –Mathematical Reviews

Dynamic Nonlinear Econometric Models

Author : Benedikt M. Pötscher
Publisher : Springer Science & Business Media
ISBN 13 : 3662034867
Total Pages : 307 pages
Book Rating : 4.6/5 (62 download)

DOWNLOAD NOW!

Book Synopsis Dynamic Nonlinear Econometric Models by : Benedikt M. Pötscher

Download or read book Dynamic Nonlinear Econometric Models written by Benedikt M. Pötscher and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many relationships in economics, and also in other fields, are both dynamic and nonlinear. A major advance in econometrics over the last fifteen years has been the development of a theory of estimation and inference for dy namic nonlinear models. This advance was accompanied by improvements in computer technology that facilitate the practical implementation of such estimation methods. In two articles in Econometric Reviews, i.e., Pötscher and Prucha {1991a,b), we provided -an expository discussion of the basic structure of the asymptotic theory of M-estimators in dynamic nonlinear models and a review of the literature up to the beginning of this decade. Among others, the class of M-estimators contains least mean distance estimators (includ ing maximum likelihood estimators) and generalized method of moment estimators. The present book expands and revises the discussion in those articles. It is geared towards the professional econometrician or statistician. Besides reviewing the literature we also presented in the above men tioned articles a number of then new results. One example is a consis tency result for the case where the identifiable uniqueness condition fails.

Modelling Nonlinear Economic Time Series

Author : Timo Teräsvirta
Publisher : OUP Oxford
ISBN 13 : 9780199587148
Total Pages : 592 pages
Book Rating : 4.5/5 (871 download)

DOWNLOAD NOW!

Book Synopsis Modelling Nonlinear Economic Time Series by : Timo Teräsvirta

Download or read book Modelling Nonlinear Economic Time Series written by Timo Teräsvirta and published by OUP Oxford. This book was released on 2010-12-16 with total page 592 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains an extensive up-to-date overview of nonlinear time series models and their application to modelling economic relationships. It considers nonlinear models in stationary and nonstationary frameworks, and both parametric and nonparametric models are discussed. The book contains examples of nonlinear models in economic theory and presents the most common nonlinear time series models. Importantly, it shows the reader how to apply these models in practice. For thispurpose, the building of various nonlinear models with its three stages of model building: specification, estimation and evaluation, is discussed in detail and is illustrated by several examples involving both economic and non-economic data. Since estimation of nonlinear time series models is carried outusing numerical algorithms, the book contains a chapter on estimating parametric nonlinear models and another on estimating nonparametric ones.Forecasting is a major reason for building time series models, linear or nonlinear. The book contains a discussion on forecasting with nonlinear models, both parametric and nonparametric, and considers numerical techniques necessary for computing multi-period forecasts from them. The main focus of the book is on models of the conditional mean, but models of the conditional variance, mainly those of autoregressive conditional heteroskedasticity, receive attention as well. A separate chapter isdevoted to state space models. As a whole, the book is an indispensable tool for researchers interested in nonlinear time series and is also suitable for teaching courses in econometrics and time series analysis.

Nonlinear Models for Repeated Measurement Data

Author : Marie Davidian
Publisher : Routledge
ISBN 13 : 1351428144
Total Pages : 212 pages
Book Rating : 4.3/5 (514 download)

DOWNLOAD NOW!

Book Synopsis Nonlinear Models for Repeated Measurement Data by : Marie Davidian

Download or read book Nonlinear Models for Repeated Measurement Data written by Marie Davidian and published by Routledge. This book was released on 2017-11-01 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonlinear measurement data arise in a wide variety of biological and biomedical applications, such as longitudinal clinical trials, studies of drug kinetics and growth, and the analysis of assay and laboratory data. Nonlinear Models for Repeated Measurement Data provides the first unified development of methods and models for data of this type, with a detailed treatment of inference for the nonlinear mixed effects and its extensions. A particular strength of the book is the inclusion of several detailed case studies from the areas of population pharmacokinetics and pharmacodynamics, immunoassay and bioassay development and the analysis of growth curves.

Non-Linear Time Series

Author : Kamil Feridun Turkman
Publisher : Springer
ISBN 13 : 3319070282
Total Pages : 255 pages
Book Rating : 4.3/5 (19 download)

DOWNLOAD NOW!

Book Synopsis Non-Linear Time Series by : Kamil Feridun Turkman

Download or read book Non-Linear Time Series written by Kamil Feridun Turkman and published by Springer. This book was released on 2014-09-29 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a useful combination of probabilistic and statistical tools for analyzing nonlinear time series. Key features of the book include a study of the extremal behavior of nonlinear time series and a comprehensive list of nonlinear models that address different aspects of nonlinearity. Several inferential methods, including quasi likelihood methods, sequential Markov Chain Monte Carlo Methods and particle filters, are also included so as to provide an overall view of the available tools for parameter estimation for nonlinear models. A chapter on integer time series models based on several thinning operations, which brings together all recent advances made in this area, is also included. Readers should have attended a prior course on linear time series, and a good grasp of simulation-based inferential methods is recommended. This book offers a valuable resource for second-year graduate students and researchers in statistics and other scientific areas who need a basic understanding of nonlinear time series.

Recent Advances In Statistical Methods, Proceedings Of Statistics 2001 Canada: The 4th Conference In Applied Statistics

Author : Yogendra P Chaubey
Publisher : World Scientific
ISBN 13 : 1783261145
Total Pages : 376 pages
Book Rating : 4.7/5 (832 download)

DOWNLOAD NOW!

Book Synopsis Recent Advances In Statistical Methods, Proceedings Of Statistics 2001 Canada: The 4th Conference In Applied Statistics by : Yogendra P Chaubey

Download or read book Recent Advances In Statistical Methods, Proceedings Of Statistics 2001 Canada: The 4th Conference In Applied Statistics written by Yogendra P Chaubey and published by World Scientific. This book was released on 2002-11-21 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Recent Advances in Total Least Squares Techniques and Errors-in-variables Modeling

Author : Sabine van Huffel
Publisher : SIAM
ISBN 13 : 9780898713930
Total Pages : 404 pages
Book Rating : 4.7/5 (139 download)

DOWNLOAD NOW!

Book Synopsis Recent Advances in Total Least Squares Techniques and Errors-in-variables Modeling by : Sabine van Huffel

Download or read book Recent Advances in Total Least Squares Techniques and Errors-in-variables Modeling written by Sabine van Huffel and published by SIAM. This book was released on 1997-01-01 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: An overview of the computational issues; statistical, numerical, and algebraic properties, and new generalizations and applications of advances on TLS and EIV models. Experts from several disciplines prepared overview papers which were presented at the conference and are included in this book.

Advanced Methodologies and Technologies in Business Operations and Management

Author : Khosrow-Pour, D.B.A., Mehdi
Publisher : IGI Global
ISBN 13 : 1522573631
Total Pages : 1482 pages
Book Rating : 4.5/5 (225 download)

DOWNLOAD NOW!

Book Synopsis Advanced Methodologies and Technologies in Business Operations and Management by : Khosrow-Pour, D.B.A., Mehdi

Download or read book Advanced Methodologies and Technologies in Business Operations and Management written by Khosrow-Pour, D.B.A., Mehdi and published by IGI Global. This book was released on 2018-09-14 with total page 1482 pages. Available in PDF, EPUB and Kindle. Book excerpt: Businesses consistently work on new projects, products, and workflows to remain competitive and successful in the modern business environment. To remain zealous, businesses must employ the most effective methods and tools in human resources, project management, and overall business plan execution as competitors work to succeed as well. Advanced Methodologies and Technologies in Business Operations and Management provides emerging research on business tools such as employee engagement, payout policies, and financial investing to promote operational success. While highlighting the challenges facing modern organizations, readers will learn how corporate social responsibility and utilizing artificial intelligence improve a company’s culture and management. This book is an ideal resource for executives and managers, researchers, accountants, and financial investors seeking current research on business operations and management.

Elements of Nonlinear Time Series Analysis and Forecasting

Author : Jan G. De Gooijer
Publisher : Springer
ISBN 13 : 3319432524
Total Pages : 618 pages
Book Rating : 4.3/5 (194 download)

DOWNLOAD NOW!

Book Synopsis Elements of Nonlinear Time Series Analysis and Forecasting by : Jan G. De Gooijer

Download or read book Elements of Nonlinear Time Series Analysis and Forecasting written by Jan G. De Gooijer and published by Springer. This book was released on 2017-03-30 with total page 618 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an overview of the current state-of-the-art of nonlinear time series analysis, richly illustrated with examples, pseudocode algorithms and real-world applications. Avoiding a “theorem-proof” format, it shows concrete applications on a variety of empirical time series. The book can be used in graduate courses in nonlinear time series and at the same time also includes interesting material for more advanced readers. Though it is largely self-contained, readers require an understanding of basic linear time series concepts, Markov chains and Monte Carlo simulation methods. The book covers time-domain and frequency-domain methods for the analysis of both univariate and multivariate (vector) time series. It makes a clear distinction between parametric models on the one hand, and semi- and nonparametric models/methods on the other. This offers the reader the option of concentrating exclusively on one of these nonlinear time series analysis methods. To make the book as user friendly as possible, major supporting concepts and specialized tables are appended at the end of every chapter. In addition, each chapter concludes with a set of key terms and concepts, as well as a summary of the main findings. Lastly, the book offers numerous theoretical and empirical exercises, with answers provided by the author in an extensive solutions manual.

Panel Data Econometrics

Author : Mike Tsionas
Publisher : Academic Press
ISBN 13 : 0128144319
Total Pages : 432 pages
Book Rating : 4.1/5 (281 download)

DOWNLOAD NOW!

Book Synopsis Panel Data Econometrics by : Mike Tsionas

Download or read book Panel Data Econometrics written by Mike Tsionas and published by Academic Press. This book was released on 2019-06-19 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Panel Data Econometrics: Theory introduces econometric modelling. Written by experts from diverse disciplines, the volume uses longitudinal datasets to illuminate applications for a variety of fields, such as banking, financial markets, tourism and transportation, auctions, and experimental economics. Contributors emphasize techniques and applications, and they accompany their explanations with case studies, empirical exercises and supplementary code in R. They also address panel data analysis in the context of productivity and efficiency analysis, where some of the most interesting applications and advancements have recently been made. Provides a vast array of empirical applications useful to practitioners from different application environments Accompanied by extensive case studies and empirical exercises Includes empirical chapters accompanied by supplementary code in R, helping researchers replicate findings Represents an accessible resource for diverse industries, including health, transportation, tourism, economic growth, and banking, where researchers are not always econometrics experts

Nonlinear Estimation

Author : Gavin J.S. Ross
Publisher : Springer Science & Business Media
ISBN 13 : 1461234123
Total Pages : 198 pages
Book Rating : 4.4/5 (612 download)

DOWNLOAD NOW!

Book Synopsis Nonlinear Estimation by : Gavin J.S. Ross

Download or read book Nonlinear Estimation written by Gavin J.S. Ross and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: Non-Linear Estimation is a handbook for the practical statistician or modeller interested in fitting and interpreting non-linear models with the aid of a computer. A major theme of the book is the use of 'stable parameter systems'; these provide rapid convergence of optimization algorithms, more reliable dispersion matrices and confidence regions for parameters, and easier comparison of rival models. The book provides insights into why some models are difficult to fit, how to combine fits over different data sets, how to improve data collection to reduce prediction variance, and how to program particular models to handle a full range of data sets. The book combines an algebraic, a geometric and a computational approach, and is illustrated with practical examples. A final chapter shows how this approach is implemented in the author's Maximum Likelihood Program, MLP.