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Author: Wolfgang Härdle
Publisher: Cambridge University Press
Published: 1990
Total Pages: 356
ISBN-13: 9780521429504
DOWNLOAD EBOOKThis is the first book to bring together in one place the techniques for regression curve smoothing involving more than one variable.
Author: Wolfgang Hrdle
Publisher:
Published: 1990
Total Pages: 0
ISBN-13:
DOWNLOAD EBOOKAuthor: Wolfgang Hrdle
Publisher:
Published: 1990
Total Pages: 333
ISBN-13:
DOWNLOAD EBOOKAuthor: K. Takezawa
Publisher: John Wiley & Sons
Published: 2005-12-02
Total Pages: 566
ISBN-13: 0471771449
DOWNLOAD EBOOKAn easy-to-grasp introduction to nonparametric regression This book's straightforward, step-by-step approach provides an excellent introduction to the field for novices of nonparametric regression. Introduction to Nonparametric Regression clearly explains the basic concepts underlying nonparametric regression and features: * Thorough explanations of various techniques, which avoid complex mathematics and excessive abstract theory to help readers intuitively grasp the value of nonparametric regression methods * Statistical techniques accompanied by clear numerical examples that further assist readers in developing and implementing their own solutions * Mathematical equations that are accompanied by a clear explanation of how the equation was derived The first chapter leads with a compelling argument for studying nonparametric regression and sets the stage for more advanced discussions. In addition to covering standard topics, such as kernel and spline methods, the book provides in-depth coverage of the smoothing of histograms, a topic generally not covered in comparable texts. With a learning-by-doing approach, each topical chapter includes thorough S-Plus? examples that allow readers to duplicate the same results described in the chapter. A separate appendix is devoted to the conversion of S-Plus objects to R objects. In addition, each chapter ends with a set of problems that test readers' grasp of key concepts and techniques and also prepares them for more advanced topics. This book is recommended as a textbook for undergraduate and graduate courses in nonparametric regression. Only a basic knowledge of linear algebra and statistics is required. In addition, this is an excellent resource for researchers and engineers in such fields as pattern recognition, speech understanding, and data mining. Practitioners who rely on nonparametric regression for analyzing data in the physical, biological, and social sciences, as well as in finance and economics, will find this an unparalleled resource.
Author: Daniel J. Henderson
Publisher: Cambridge University Press
Published: 2015-01-19
Total Pages: 381
ISBN-13: 110701025X
DOWNLOAD EBOOKThe 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: Wayne W. Daniel
Publisher: Brooks/Cole
Published: 2000-06-30
Total Pages: 0
ISBN-13: 9780534381943
DOWNLOAD EBOOKThis book covers the most commonly used nonparametric statistical techniques by emphasizing applications rather than theory. Exercises and examples are drawn from various disciplines including agriculture, biology, sociology, education, psychology, medicine, business, geology, and anthropology. The applications of techniques are presented in a step-by-step format that is repeated for all illustrative examples. Concepts are reinforced with many references to statistical literature to show the relevance to real-world problems. Chapters contain references of available computer programs and software packages that apply to methods presented in the book.
Author: Jeffrey Racine
Publisher: Oxford University Press
Published: 2014-04
Total Pages: 562
ISBN-13: 0199857946
DOWNLOAD EBOOKThis 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: László Györfi
Publisher: Springer Science & Business Media
Published: 2006-04-18
Total Pages: 662
ISBN-13: 0387224424
DOWNLOAD EBOOKThis book provides a systematic in-depth analysis of nonparametric regression with random design. It covers almost all known estimates. The emphasis is on distribution-free properties of the estimates.
Author: Adonis Yatchew
Publisher: Cambridge University Press
Published: 2003-06-02
Total Pages: 238
ISBN-13: 9780521012263
DOWNLOAD EBOOKThis book provides an accessible collection of techniques for analyzing nonparametric and semiparametric regression models. Worked examples include estimation of Engel curves and equivalence scales, scale economies, semiparametric Cobb-Douglas, translog and CES cost functions, household gasoline consumption, hedonic housing prices, option prices and state price density estimation. The book should be of interest to a broad range of economists including those working in industrial organization, labor, development, urban, energy and financial economics. A variety of testing procedures are covered including simple goodness of fit tests and residual regression tests. These procedures can be used to test hypotheses such as parametric and semiparametric specifications, significance, monotonicity and additive separability. Other topics include endogeneity of parametric and nonparametric effects, as well as heteroskedasticity and autocorrelation in the residuals. Bootstrap procedures are provided.
Author: Wolfgang Karl Härdle
Publisher: Springer Science & Business Media
Published: 2012-08-27
Total Pages: 317
ISBN-13: 364217146X
DOWNLOAD EBOOKThe 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.
