Bayesian Bandwidth Selection in Nonparametric Time-varying Coefficient Models

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ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (931 download)

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Book Synopsis Bayesian Bandwidth Selection in Nonparametric Time-varying Coefficient Models by : Tingting Cheng

Download or read book Bayesian Bandwidth Selection in Nonparametric Time-varying Coefficient Models written by Tingting Cheng and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Nonparametric Econometrics

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Publisher : Princeton University Press
ISBN 13 : 1400841062
Total Pages : 769 pages
Book Rating : 4.4/5 (8 download)

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Book Synopsis Nonparametric Econometrics by : Qi Li

Download or read book Nonparametric Econometrics written by Qi Li and published by Princeton University Press. This book was released on 2011-10-09 with total page 769 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive, up-to-date textbook on nonparametric methods for students and researchers Until now, students and researchers in nonparametric and semiparametric statistics and econometrics have had to turn to the latest journal articles to keep pace with these emerging methods of economic analysis. Nonparametric Econometrics fills a major gap by gathering together the most up-to-date theory and techniques and presenting them in a remarkably straightforward and accessible format. The empirical tests, data, and exercises included in this textbook help make it the ideal introduction for graduate students and an indispensable resource for researchers. Nonparametric and semiparametric methods have attracted a great deal of attention from statisticians in recent decades. While the majority of existing books on the subject operate from the presumption that the underlying data is strictly continuous in nature, more often than not social scientists deal with categorical data—nominal and ordinal—in applied settings. The conventional nonparametric approach to dealing with the presence of discrete variables is acknowledged to be unsatisfactory. This book is tailored to the needs of applied econometricians and social scientists. Qi Li and Jeffrey Racine emphasize nonparametric techniques suited to the rich array of data types—continuous, nominal, and ordinal—within one coherent framework. They also emphasize the properties of nonparametric estimators in the presence of potentially irrelevant variables. Nonparametric Econometrics covers all the material necessary to understand and apply nonparametric methods for real-world problems.

Nonparametric Kernel Density Estimation and Its Computational Aspects

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Publisher : Springer
ISBN 13 : 3319716883
Total Pages : 197 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Nonparametric Kernel Density Estimation and Its Computational Aspects by : Artur Gramacki

Download or read book Nonparametric Kernel Density Estimation and Its Computational Aspects written by Artur Gramacki and published by Springer. This book was released on 2017-12-21 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes computational problems related to kernel density estimation (KDE) – one of the most important and widely used data smoothing techniques. A very detailed description of novel FFT-based algorithms for both KDE computations and bandwidth selection are presented. The theory of KDE appears to have matured and is now well developed and understood. However, there is not much progress observed in terms of performance improvements. This book is an attempt to remedy this. The book primarily addresses researchers and advanced graduate or postgraduate students who are interested in KDE and its computational aspects. The book contains both some background and much more sophisticated material, hence also more experienced researchers in the KDE area may find it interesting. The presented material is richly illustrated with many numerical examples using both artificial and real datasets. Also, a number of practical applications related to KDE are presented.

Bayesian Nonparametric Data Analysis

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Publisher : Springer
ISBN 13 : 3319189689
Total Pages : 203 pages
Book Rating : 4.3/5 (191 download)

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Book Synopsis Bayesian Nonparametric Data Analysis by : Peter Müller

Download or read book Bayesian Nonparametric Data Analysis written by Peter Müller and published by Springer. This book was released on 2015-06-17 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. Rather than providing an encyclopedic review of probability models, the book’s structure follows a data analysis perspective. As such, the chapters are organized by traditional data analysis problems. In selecting specific nonparametric models, simpler and more traditional models are favored over specialized ones. The discussed methods are illustrated with a wealth of examples, including applications ranging from stylized examples to case studies from recent literature. The book also includes an extensive discussion of computational methods and details on their implementation. R code for many examples is included in online software pages.

Recent Advances and Future Directions in Causality, Prediction, and Specification Analysis

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Publisher : Springer Science & Business Media
ISBN 13 : 1461416531
Total Pages : 582 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Recent Advances and Future Directions in Causality, Prediction, and Specification Analysis by : Xiaohong Chen

Download or read book Recent Advances and Future Directions in Causality, Prediction, and Specification Analysis written by Xiaohong Chen and published by Springer Science & Business Media. This book was released on 2012-08-01 with total page 582 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of articles that present the most recent cutting edge results on specification and estimation of economic models written by a number of the world’s foremost leaders in the fields of theoretical and methodological econometrics. Recent advances in asymptotic approximation theory, including the use of higher order asymptotics for things like estimator bias correction, and the use of various expansion and other theoretical tools for the development of bootstrap techniques designed for implementation when carrying out inference are at the forefront of theoretical development in the field of econometrics. One important feature of these advances in the theory of econometrics is that they are being seamlessly and almost immediately incorporated into the “empirical toolbox” that applied practitioners use when actually constructing models using data, for the purposes of both prediction and policy analysis and the more theoretically targeted chapters in the book will discuss these developments. Turning now to empirical methodology, chapters on prediction methodology will focus on macroeconomic and financial applications, such as the construction of diffusion index models for forecasting with very large numbers of variables, and the construction of data samples that result in optimal predictive accuracy tests when comparing alternative prediction models. Chapters carefully outline how applied practitioners can correctly implement the latest theoretical refinements in model specification in order to “build” the best models using large-scale and traditional datasets, making the book of interest to a broad readership of economists from theoretical econometricians to applied economic practitioners.

Journal of the American Statistical Association

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Publisher :
ISBN 13 :
Total Pages : 920 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Journal of the American Statistical Association by :

Download or read book Journal of the American Statistical Association written by and published by . This book was released on 2008 with total page 920 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Applied Nonparametric Econometrics

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Publisher : Cambridge University Press
ISBN 13 : 110701025X
Total Pages : 381 pages
Book Rating : 4.1/5 (7 download)

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Book Synopsis Applied Nonparametric Econometrics by : Daniel J. Henderson

Download or read book Applied Nonparametric Econometrics written by Daniel J. Henderson and published by Cambridge University Press. This book was released on 2015-01-19 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: The majority of empirical research in economics ignores the potential benefits of nonparametric methods, while the majority of advances in nonparametric theory ignores the problems faced in applied econometrics. This book helps bridge this gap between applied economists and theoretical nonparametric econometricians. It discusses in depth, and in terms that someone with only one year of graduate econometrics can understand, basic to advanced nonparametric methods. The analysis starts with density estimation and motivates the procedures through methods that should be familiar to the reader. It then moves on to kernel regression, estimation with discrete data, and advanced methods such as estimation with panel data and instrumental variables models. The book pays close attention to the issues that arise with programming, computing speed, and application. In each chapter, the methods discussed are applied to actual data, paying attention to presentation of results and potential pitfalls.

Nonparametric Regression and Generalized Linear Models

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Publisher : CRC Press
ISBN 13 : 1482229757
Total Pages : 197 pages
Book Rating : 4.4/5 (822 download)

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Book Synopsis Nonparametric Regression and Generalized Linear Models by : P.J. Green

Download or read book Nonparametric Regression and Generalized Linear Models written by P.J. Green and published by CRC Press. This book was released on 1993-05-01 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: Nonparametric Regression and Generalized Linear Models focuses on the roughness penalty method of nonparametric smoothing and shows how this technique provides a unifying approach to a wide range of smoothing problems. The emphasis is methodological rather than theoretical, and the authors concentrate on statistical and computation issues. Real data examples are used to illustrate the various methods and to compare them with standard parametric approaches. The mathematical treatment is self-contained and depends mainly on simple linear algebra and calculus. This monograph will be useful both as a reference work for research and applied statisticians and as a text for graduate students.

Machine Learning and Data Mining in Pattern Recognition

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Publisher : Springer
ISBN 13 : 3319624164
Total Pages : 462 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Machine Learning and Data Mining in Pattern Recognition by : Petra Perner

Download or read book Machine Learning and Data Mining in Pattern Recognition written by Petra Perner and published by Springer. This book was released on 2017-07-01 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 13th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2017, held in New York, NY, USA in July/August 2017.The 31 full papers presented in this book were carefully reviewed and selected from 150 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multi-media data types such as image mining, text mining, video mining, and Web mining.

Partially Linear Models

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Publisher : Springer Science & Business Media
ISBN 13 : 3642577008
Total Pages : 210 pages
Book Rating : 4.6/5 (425 download)

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Book Synopsis Partially Linear Models by : Wolfgang Härdle

Download or read book Partially Linear Models written by Wolfgang Härdle and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last ten years, there has been increasing interest and activity in the general area of partially linear regression smoothing in statistics. Many methods and techniques have been proposed and studied. This monograph hopes to bring an up-to-date presentation of the state of the art of partially linear regression techniques. The emphasis is on methodologies rather than on the theory, with a particular focus on applications of partially linear regression techniques to various statistical problems. These problems include least squares regression, asymptotically efficient estimation, bootstrap resampling, censored data analysis, linear measurement error models, nonlinear measurement models, nonlinear and nonparametric time series models.

The Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics

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Publisher : Oxford University Press
ISBN 13 : 0199857946
Total Pages : 562 pages
Book Rating : 4.1/5 (998 download)

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Book Synopsis The Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics by : Jeffrey Racine

Download or read book The Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics written by Jeffrey Racine and published by Oxford University Press. This book was released on 2014-04 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume, edited by Jeffrey Racine, Liangjun Su, and Aman Ullah, contains the latest research on nonparametric and semiparametric econometrics and statistics. Chapters by leading international econometricians and statisticians highlight the interface between econometrics and statistical methods for nonparametric and semiparametric procedures.

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.

Statistics in the 21st Century

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Publisher : CRC Press
ISBN 13 : 1420035398
Total Pages : 571 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Statistics in the 21st Century by : Adrian E. Raftery

Download or read book Statistics in the 21st Century written by Adrian E. Raftery and published by CRC Press. This book was released on 2001-07-09 with total page 571 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume discusses an important area of statistics and highlights the most important statistical advances. It is divided into four sections: statistics in the life and medical sciences, business and social science, the physical sciences and engineering, and theory and methods of statistics.

Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives

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Publisher : John Wiley & Sons
ISBN 13 : 9780470090435
Total Pages : 448 pages
Book Rating : 4.0/5 (94 download)

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Book Synopsis Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives by : Andrew Gelman

Download or read book Applied Bayesian Modeling and Causal Inference from Incomplete-Data Perspectives written by Andrew Gelman and published by John Wiley & Sons. This book was released on 2004-09-03 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together a collection of articles on statistical methods relating to missing data analysis, including multiple imputation, propensity scores, instrumental variables, and Bayesian inference. Covering new research topics and real-world examples which do not feature in many standard texts. The book is dedicated to Professor Don Rubin (Harvard). Don Rubin has made fundamental contributions to the study of missing data. Key features of the book include: Comprehensive coverage of an imporant area for both research and applications. Adopts a pragmatic approach to describing a wide range of intermediate and advanced statistical techniques. Covers key topics such as multiple imputation, propensity scores, instrumental variables and Bayesian inference. Includes a number of applications from the social and health sciences. Edited and authored by highly respected researchers in the area.

Modeling Discrete Time-to-Event Data

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Publisher : Springer
ISBN 13 : 3319281585
Total Pages : 252 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Modeling Discrete Time-to-Event Data by : Gerhard Tutz

Download or read book Modeling Discrete Time-to-Event Data written by Gerhard Tutz and published by Springer. This book was released on 2016-06-14 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on statistical methods for the analysis of discrete failure times. Failure time analysis is one of the most important fields in statistical research, with applications affecting a wide range of disciplines, in particular, demography, econometrics, epidemiology and clinical research. Although there are a large variety of statistical methods for failure time analysis, many techniques are designed for failure times that are measured on a continuous scale. In empirical studies, however, failure times are often discrete, either because they have been measured in intervals (e.g., quarterly or yearly) or because they have been rounded or grouped. The book covers well-established methods like life-table analysis and discrete hazard regression models, but also introduces state-of-the art techniques for model evaluation, nonparametric estimation and variable selection. Throughout, the methods are illustrated by real life applications, and relationships to survival analysis in continuous time are explained. Each section includes a set of exercises on the respective topics. Various functions and tools for the analysis of discrete survival data are collected in the R package discSurv that accompanies the book.

Mixed Effects Models for Complex Data

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Publisher : CRC Press
ISBN 13 : 9781420074086
Total Pages : 431 pages
Book Rating : 4.0/5 (74 download)

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Book Synopsis Mixed Effects Models for Complex Data by : Lang Wu

Download or read book Mixed Effects Models for Complex Data written by Lang Wu and published by CRC Press. This book was released on 2009-11-11 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although standard mixed effects models are useful in a range of studies, other approaches must often be used in correlation with them when studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate approaches to address dropouts, missing data, measurement errors, censoring, and outliers. For each class of mixed effects model, the author reviews the corresponding class of regression model for cross-sectional data. An overview of general models and methods, along with motivating examples After presenting real data examples and outlining general approaches to the analysis of longitudinal/clustered data and incomplete data, the book introduces linear mixed effects (LME) models, generalized linear mixed models (GLMMs), nonlinear mixed effects (NLME) models, and semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values, measurement errors, censoring, and outliers. Self-contained coverage of specific topics Subsequent chapters delve more deeply into missing data problems, covariate measurement errors, and censored responses in mixed effects models. Focusing on incomplete data, the book also covers survival and frailty models, joint models of survival and longitudinal data, robust methods for mixed effects models, marginal generalized estimating equation (GEE) models for longitudinal or clustered data, and Bayesian methods for mixed effects models. Background material In the appendix, the author provides background information, such as likelihood theory, the Gibbs sampler, rejection and importance sampling methods, numerical integration methods, optimization methods, bootstrap, and matrix algebra. Failure to properly address missing data, measurement errors, and other issues in statistical analyses can lead to severely biased or misleading results. This book explores the biases that arise when naïve methods are used and shows which approaches should be used to achieve accurate results in longitudinal data analysis.

Bayesian Nonparametrics

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Publisher : Springer Science & Business Media
ISBN 13 : 0387226540
Total Pages : 311 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Bayesian Nonparametrics by : J.K. Ghosh

Download or read book Bayesian Nonparametrics written by J.K. Ghosh and published by Springer Science & Business Media. This book was released on 2006-05-11 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the first systematic treatment of Bayesian nonparametric methods and the theory behind them. It will also appeal to statisticians in general. The book is primarily aimed at graduate students and can be used as the text for a graduate course in Bayesian non-parametrics.