Goodness Of Fit Tests Based On Series Estimators In Nonparametric Instrumental Regression
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| Author | : Christoph Breunig |
| Publisher | : |
| Total Pages | : |
| Release | : 2012 |
| Genre | : |
| ISBN | : |
This paper proposes several tests of restricted specification in nonparametric instrumental regression. Based on series estimators, test statistics are established that allow for tests of the general model against a parametric or nonparametric specification as well as a test of exogeneity of the vector of regressors. The tests are asymptotically normally distributed under correct specification and consistent against any alternative model. Under a sequence of local alternative hypotheses, the asymptotic distribution of the tests is derived. Moreover, uniform consistency is established over a class of alternatives whose distance to the null hypothesis shrinks appropriately as the sample size increases.
| Author | : Maragatha N. Ramachandran |
| Publisher | : |
| Total Pages | : 188 |
| Release | : 1992 |
| Genre | : Goodness-of-fit tests |
| ISBN | : |
| Author | : Jeffrey Hart |
| Publisher | : Springer |
| Total Pages | : 288 |
| Release | : 2012-11-28 |
| Genre | : Mathematics |
| ISBN | : 9781475727241 |
An exploration of the use of smoothing methods in testing the fit of parametric regression models. The book reviews many of the existing methods for testing lack-of-fit and also proposes a number of new methods, addressing both applied and theoretical aspects of the model checking problems. As such, the book is of interest to practitioners of statistics and researchers investigating either lack-of-fit tests or nonparametric smoothing ideas. The first four chapters introduce the problem of estimating regression functions by nonparametric smoothers, primarily those of kernel and Fourier series type, and could be used as the foundation for a graduate level course on nonparametric function estimation. The prerequisites for a full appreciation of the book are a modest knowledge of calculus and some familiarity with the basics of mathematical statistics.
| Author | : Johannes Hubertus Jacob Einmahl |
| Publisher | : |
| Total Pages | : |
| Release | : 2004 |
| Genre | : |
| ISBN | : |
| Author | : C. Huber-Carol |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 512 |
| Release | : 2012-12-06 |
| Genre | : Mathematics |
| ISBN | : 1461201039 |
The 37 expository articles in this volume provide broad coverage of important topics relating to the theory, methods, and applications of goodness-of-fit tests and model validity. The book is divided into eight parts, each of which presents topics written by expert researchers in their areas. Key features include: * state-of-the-art exposition of modern model validity methods, graphical techniques, and computer-intensive methods * systematic presentation with sufficient history and coverage of the fundamentals of the subject * exposure to recent research and a variety of open problems * many interesting real life examples for practitioners * extensive bibliography, with special emphasis on recent literature * subject index This comprehensive reference work will serve the statistical and applied mathematics communities as well as practitioners in the field.
| Author | : Jeffrey Hart |
| Publisher | : |
| Total Pages | : 304 |
| Release | : 2014-01-15 |
| Genre | : |
| ISBN | : 9781475727234 |
| Author | : Daniel J. Henderson |
| Publisher | : Cambridge University Press |
| Total Pages | : 381 |
| Release | : 2015-01-12 |
| Genre | : Business & Economics |
| ISBN | : 1316060675 |
The majority of empirical research in economics ignores the potential benefits of nonparametric methods, while the majority of advances in nonparametric theory ignore 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 | : Yuri Ingster |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 471 |
| Release | : 2012-11-12 |
| Genre | : Mathematics |
| ISBN | : 0387215808 |
This book presents the modern theory of nonparametric goodness-of-fit testing. It fills the gap in modern nonparametric statistical theory by discussing hypothesis testing and addresses mathematical statisticians who are interesting in the theory of non-parametric statistical inference. It will be of interest to specialists who are dealing with applied non-parametric statistical problems relevant in signal detection and transmission and in technical and medical diagnostics among others.
| Author | : Jeffrey Hart |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 298 |
| Release | : 2013-03-14 |
| Genre | : Mathematics |
| ISBN | : 1475727224 |
An exploration of the use of smoothing methods in testing the fit of parametric regression models. The book reviews many of the existing methods for testing lack-of-fit and also proposes a number of new methods, addressing both applied and theoretical aspects of the model checking problems. As such, the book is of interest to practitioners of statistics and researchers investigating either lack-of-fit tests or nonparametric smoothing ideas. The first four chapters introduce the problem of estimating regression functions by nonparametric smoothers, primarily those of kernel and Fourier series type, and could be used as the foundation for a graduate level course on nonparametric function estimation. The prerequisites for a full appreciation of the book are a modest knowledge of calculus and some familiarity with the basics of mathematical statistics.
| Author | : Jeffrey S. Racine |
| Publisher | : Cambridge University Press |
| Total Pages | : 436 |
| Release | : 2019-06-27 |
| Genre | : Business & Economics |
| ISBN | : 1108757286 |
Interest in nonparametric methodology has grown considerably over the past few decades, stemming in part from vast improvements in computer hardware and the availability of new software that allows practitioners to take full advantage of these numerically intensive methods. This book is written for advanced undergraduate students, intermediate graduate students, and faculty, and provides a complete teaching and learning course at a more accessible level of theoretical rigor than Racine's earlier book co-authored with Qi Li, Nonparametric Econometrics: Theory and Practice (2007). The open source R platform for statistical computing and graphics is used throughout in conjunction with the R package np. Recent developments in reproducible research is emphasized throughout with appendices devoted to helping the reader get up to speed with R, R Markdown, TeX and Git.
