Nonparametric And Semiparametric Models

Author : Wolfgang Karl Härdle,Marlene Müller,Stefan Sperlich,Axel Werwatz
Publisher : Springer Science & Business Media
Page : 300 pages
File Size : 43,7 Mb
Release : 2012-08-27
Category : Mathematics
ISBN : 9783642171468

Get Book

Nonparametric and Semiparametric Models by Wolfgang Karl Härdle,Marlene Müller,Stefan Sperlich,Axel Werwatz Pdf

The statistical and mathematical principles of smoothing with a focus on applicable techniques are presented in this book. It naturally splits into two parts: The first part is intended for undergraduate students majoring in mathematics, statistics, econometrics or biometrics whereas the second part is intended to be used by master and PhD students or researchers. The material is easy to accomplish since the e-book character of the text gives a maximum of flexibility in learning (and teaching) intensity.

Author : Wolfgang Härdle
Publisher : Springer Science & Business Media
Page : 340 pages
File Size : 54,9 Mb
Release : 2004-03-22
Category : Business & Economics
ISBN : 3540207228

Get Book

Nonparametric and Semiparametric Models by Wolfgang Härdle Pdf

The statistical and mathematical principles of smoothing with a focus on applicable techniques are presented in this book. It naturally splits into two parts: The first part is intended for undergraduate students majoring in mathematics, statistics, econometrics or biometrics whereas the second part is intended to be used by master and PhD students or researchers. The material is easy to accomplish since the e-book character of the text gives a maximum of flexibility in learning (and teaching) intensity.

Author : Wolfgang Karl Härdle,Marlene Müller,Stefan Sperlich,Axel Werwatz
Publisher : Springer
Page : 0 pages
File Size : 43,7 Mb
Release : 2012-08-20
Category : Mathematics
ISBN : 3642620760

Get Book

Nonparametric and Semiparametric Models by Wolfgang Karl Härdle,Marlene Müller,Stefan Sperlich,Axel Werwatz Pdf

The statistical and mathematical principles of smoothing with a focus on applicable techniques are presented in this book. It naturally splits into two parts: The first part is intended for undergraduate students majoring in mathematics, statistics, econometrics or biometrics whereas the second part is intended to be used by master and PhD students or researchers. The material is easy to accomplish since the e-book character of the text gives a maximum of flexibility in learning (and teaching) intensity.

Author : William A. Barnett,James Powell,George E. Tauchen
Publisher : Cambridge University Press
Page : 512 pages
File Size : 47,8 Mb
Release : 1991-06-28
Category : Business & Economics
ISBN : 0521424313

Get Book

Nonparametric and Semiparametric Methods in Econometrics and Statistics by William A. Barnett,James Powell,George E. Tauchen Pdf

Papers from a 1988 symposium on the estimation and testing of models that impose relatively weak restrictions on the stochastic behaviour of data.

Author : Jiti Gao
Publisher : CRC Press
Page : 237 pages
File Size : 48,6 Mb
Release : 2007-03-22
Category : Mathematics
ISBN : 1420011219

Get Book

Nonlinear Time Series by Jiti Gao Pdf

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 nonparametric models and methods. Answering the call for an up-to-date overview of the latest developments in the field, Nonlinear Time Series: Semiparametric and Nonparametric Methods focuses on various semiparametric methods in model estimation, specification testing, and selection of time series data. After a brief introduction, the book examines semiparametric estimation and specification methods and then applies these approaches to a class of nonlinear continuous-time models with real-world data. It also assesses some newly proposed semiparametric estimation procedures for time series data with long-range dependence. Even though the book only deals with climatological and financial data, the estimation and specifications methods discussed can be applied to models with real-world data in many disciplines. This resource covers key methods in time series analysis and provides the necessary theoretical details. The latest applied finance and financial econometrics results and applications presented in the book enable researchers and graduate students to keep abreast of developments in the field.

Author : Joel L. Horowitz
Publisher : Springer
Page : 0 pages
File Size : 41,6 Mb
Release : 2012-02-25
Category : Business & Economics
ISBN : 1461429277

Get Book

Semiparametric and Nonparametric Methods in Econometrics by Joel L. Horowitz Pdf

Standard methods for estimating empirical models in economics and many other fields rely on strong assumptions about functional forms and the distributions of unobserved random variables. Often, it is assumed that functions of interest are linear or that unobserved random variables are normally distributed. Such assumptions simplify estimation and statistical inference but are rarely justified by economic theory or other a priori considerations. Inference based on convenient but incorrect assumptions about functional forms and distributions can be highly misleading. Nonparametric and semiparametric statistical methods provide a way to reduce the strength of the assumptions required for estimation and inference, thereby reducing the opportunities for obtaining misleading results. These methods are applicable to a wide variety of estimation problems in empirical economics and other fields, and they are being used in applied research with increasing frequency. The literature on nonparametric and semiparametric estimation is large and highly technical. This book presents the main ideas underlying a variety of nonparametric and semiparametric methods. It is accessible to graduate students and applied researchers who are familiar with econometric and statistical theory at the level taught in graduate-level courses in leading universities. The book emphasizes ideas instead of technical details and provides as intuitive an exposition as possible. Empirical examples illustrate the methods that are presented. This book updates and greatly expands the author’s previous book on semiparametric methods in econometrics. Nearly half of the material is new.

Author : Anonim
Publisher : Springer
Page : 332 pages
File Size : 43,9 Mb
Release : 2012-08-29
Category : Electronic
ISBN : 3642171478

Get Book

Nonparametric and Semiparametric Models by Anonim Pdf

Author : Joel L. Horowitz
Publisher : Springer Science & Business Media
Page : 211 pages
File Size : 48,8 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9781461206217

Get Book

Semiparametric Methods in Econometrics by Joel L. Horowitz Pdf

Many econometric models contain unknown functions as well as finite- dimensional parameters. Examples of such unknown functions are the distribution function of an unobserved random variable or a transformation of an observed variable. Econometric methods for estimating population parameters in the presence of unknown functions are called "semiparametric." During the past 15 years, much research has been carried out on semiparametric econometric models that are relevant to empirical economics. This book synthesizes the results that have been achieved for five important classes of models. The book is aimed at graduate students in econometrics and statistics as well as professionals who are not experts in semiparametic methods. The usefulness of the methods will be illustrated with applications that use real data.

Author : Daniel J. Henderson,Christopher F. Parmeter
Publisher : Cambridge University Press
Page : 381 pages
File Size : 43,7 Mb
Release : 2015-01-19
Category : Business & Economics
ISBN : 9781107010253

Get Book

Applied Nonparametric Econometrics by Daniel J. Henderson,Christopher F. Parmeter Pdf

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.

Author : Qi Li,Jeffrey Scott Racine
Publisher : Princeton University Press
Page : 768 pages
File Size : 48,7 Mb
Release : 2023-07-18
Category : Business & Economics
ISBN : 9780691248080

Get Book

Nonparametric Econometrics by Qi Li,Jeffrey Scott Racine Pdf

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.

Author : Albert W. Marshall,Ingram Olkin
Publisher : Springer Science & Business Media
Page : 785 pages
File Size : 45,6 Mb
Release : 2007-10-13
Category : Technology & Engineering
ISBN : 9780387684772

Get Book

Life Distributions by Albert W. Marshall,Ingram Olkin Pdf

This book is devoted to the study of univariate distributions appropriate for the analyses of data known to be nonnegative. The book includes much material from reliability theory in engineering and survival analysis in medicine.

Author : Aman Ullah
Publisher : Physica
Page : 0 pages
File Size : 42,5 Mb
Release : 2012-05-26
Category : Business & Economics
ISBN : 3642518508

Get Book

Semiparametric and Nonparametric Econometrics by Aman Ullah Pdf

Over the last three decades much research in empirical and theoretical economics has been carried on under various assumptions. For example a parametric functional form of the regression model, the heteroskedasticity, and the autocorrelation is always as sumed, usually linear. Also, the errors are assumed to follow certain parametric distri butions, often normal. A disadvantage of parametric econometrics based on these assumptions is that it may not be robust to the slight data inconsistency with the particular parametric specification. Indeed any misspecification in the functional form may lead to erroneous conclusions. In view of these problems, recently there has been significant interest in 'the semiparametric/nonparametric approaches to econometrics. The semiparametric approach considers econometric models where one component has a parametric and the other, which is unknown, a nonparametric specification (Manski 1984 and Horowitz and Neumann 1987, among others). The purely non parametric approach, on the other hand, does not specify any component of the model a priori. The main ingredient of this approach is the data based estimation of the unknown joint density due to Rosenblatt (1956). Since then, especially in the last decade, a vast amount of literature has appeared on nonparametric estimation in statistics journals. However, this literature is mostly highly technical and this may partly be the reason why very little is known about it in econometrics, although see Bierens (1987) and Ullah (1988).

Author : Jeffrey Racine,Liangjun Su,Aman Ullah
Publisher : Oxford University Press
Page : 562 pages
File Size : 45,5 Mb
Release : 2014-04
Category : Business & Economics
ISBN : 9780199857944

Get Book

The Oxford Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics by Jeffrey Racine,Liangjun Su,Aman Ullah Pdf

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.

Author : David Ruppert,M. P. Wand,R. J. Carroll
Publisher : Cambridge University Press
Page : 408 pages
File Size : 50,6 Mb
Release : 2003-07-14
Category : Mathematics
ISBN : 0521785162

Get Book

Semiparametric Regression by David Ruppert,M. P. Wand,R. J. Carroll Pdf

Even experts on semiparametric regression should find something new here.

Author : Hulin Wu,Jin-Ting Zhang
Publisher : John Wiley & Sons
Page : 401 pages
File Size : 51,8 Mb
Release : 2006-05-12
Category : Mathematics
ISBN : 9780470009666

Get Book

Nonparametric Regression Methods for Longitudinal Data Analysis by Hulin Wu,Jin-Ting Zhang Pdf

Incorporates mixed-effects modeling techniques for more powerful and efficient methods This book presents current and effective nonparametric regression techniques for longitudinal data analysis and systematically investigates the incorporation of mixed-effects modeling techniques into various nonparametric regression models. The authors emphasize modeling ideas and inference methodologies, although some theoretical results for the justification of the proposed methods are presented. With its logical structure and organization, beginning with basic principles, the text develops the foundation needed to master advanced principles and applications. Following a brief overview, data examples from biomedical research studies are presented and point to the need for nonparametric regression analysis approaches. Next, the authors review mixed-effects models and nonparametric regression models, which are the two key building blocks of the proposed modeling techniques. The core section of the book consists of four chapters dedicated to the major nonparametric regression methods: local polynomial, regression spline, smoothing spline, and penalized spline. The next two chapters extend these modeling techniques to semiparametric and time varying coefficient models for longitudinal data analysis. The final chapter examines discrete longitudinal data modeling and analysis. Each chapter concludes with a summary that highlights key points and also provides bibliographic notes that point to additional sources for further study. Examples of data analysis from biomedical research are used to illustrate the methodologies contained throughout the book. Technical proofs are presented in separate appendices. With its focus on solving problems, this is an excellent textbook for upper-level undergraduate and graduate courses in longitudinal data analysis. It is also recommended as a reference for biostatisticians and other theoretical and applied research statisticians with an interest in longitudinal data analysis. Not only do readers gain an understanding of the principles of various nonparametric regression methods, but they also gain a practical understanding of how to use the methods to tackle real-world problems.