The Art Of Semiparametrics
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Author | : David Ruppert |
Publisher | : Cambridge University Press |
Total Pages | : 410 |
Release | : 2003-07-14 |
Genre | : Mathematics |
ISBN | : 9780521785167 |
Semiparametric regression is concerned with the flexible incorporation of non-linear functional relationships in regression analyses. Any application area that benefits from regression analysis can also benefit from semiparametric regression. Assuming only a basic familiarity with ordinary parametric regression, this user-friendly book explains the techniques and benefits of semiparametric regression in a concise and modular fashion. The authors make liberal use of graphics and examples plus case studies taken from environmental, financial, and other applications. They include practical advice on implementation and pointers to relevant software. The 2003 book is suitable as a textbook for students with little background in regression as well as a reference book for statistically oriented scientists such as biostatisticians, econometricians, quantitative social scientists, epidemiologists, with a good working knowledge of regression and the desire to begin using more flexible semiparametric models. Even experts on semiparametric regression should find something new here.
Author | : Anastasios Tsiatis |
Publisher | : Springer Science & Business Media |
Total Pages | : 392 |
Release | : 2007-01-15 |
Genre | : Mathematics |
ISBN | : 0387373454 |
This book summarizes current knowledge regarding the theory of estimation for semiparametric models with missing data, in an organized and comprehensive manner. It starts with the study of semiparametric methods when there are no missing data. The description of the theory of estimation for semiparametric models is both rigorous and intuitive, relying on geometric ideas to reinforce the intuition and understanding of the theory. These methods are then applied to problems with missing, censored, and coarsened data with the goal of deriving estimators that are as robust and efficient as possible.
Author | : Stefan Sperlich |
Publisher | : Springer Science & Business Media |
Total Pages | : 185 |
Release | : 2006-07-25 |
Genre | : Mathematics |
ISBN | : 3790817015 |
This selection of articles emerged from different works presented "The Art of Semiparametrics" conference in 2003 in Berlin. It offers a collection of individual works that together show the large spectrum of semiparametric statistics. The book combines theoretical contributions with more applied and empirical studies. Although each article represents an original contribution to its own field, all are written in a self-contained way that may be read by non-experts.
Author | : Matthias R. Fengler |
Publisher | : Springer Science & Business Media |
Total Pages | : 232 |
Release | : 2005-12-19 |
Genre | : Business & Economics |
ISBN | : 3540305912 |
This book offers recent advances in the theory of implied volatility and refined semiparametric estimation strategies and dimension reduction methods for functional surfaces. The first part is devoted to smile-consistent pricing approaches. The second part covers estimation techniques that are natural candidates to meet the challenges in implied volatility surfaces. Empirical investigations, simulations, and pictures illustrate the concepts.
Author | : Jeffrey Racine |
Publisher | : Oxford University Press |
Total Pages | : 562 |
Release | : 2014-04 |
Genre | : Business & Economics |
ISBN | : 0199857946 |
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 | : Peter Rossi |
Publisher | : Princeton University Press |
Total Pages | : 218 |
Release | : 2014-04-27 |
Genre | : Business & Economics |
ISBN | : 0691145326 |
This book reviews and develops Bayesian non-parametric and semi-parametric methods for applications in microeconometrics and quantitative marketing. Most econometric models used in microeconomics and marketing applications involve arbitrary distributional assumptions. As more data becomes available, a natural desire to provide methods that relax these assumptions arises. Peter Rossi advocates a Bayesian approach in which specific distributional assumptions are replaced with more flexible distributions based on mixtures of normals. The Bayesian approach can use either a large but fixed number of normal components in the mixture or an infinite number bounded only by the sample size. By using flexible distributional approximations instead of fixed parametric models, the Bayesian approach can reap the advantages of an efficient method that models all of the structure in the data while retaining desirable smoothing properties. Non-Bayesian non-parametric methods often require additional ad hoc rules to avoid "overfitting," in which resulting density approximates are nonsmooth. With proper priors, the Bayesian approach largely avoids overfitting, while retaining flexibility. This book provides methods for assessing informative priors that require only simple data normalizations. The book also applies the mixture of the normals approximation method to a number of important models in microeconometrics and marketing, including the non-parametric and semi-parametric regression models, instrumental variables problems, and models of heterogeneity. In addition, the author has written a free online software package in R, "bayesm," which implements all of the non-parametric models discussed in the book.
Author | : Albert W. Marshall |
Publisher | : Springer Science & Business Media |
Total Pages | : 785 |
Release | : 2007-10-13 |
Genre | : Technology & Engineering |
ISBN | : 0387684778 |
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 | : Qi Li |
Publisher | : Princeton University Press |
Total Pages | : 769 |
Release | : 2011-10-09 |
Genre | : Business & Economics |
ISBN | : 1400841062 |
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 | : Garrett Fitzmaurice |
Publisher | : CRC Press |
Total Pages | : 633 |
Release | : 2008-08-11 |
Genre | : Mathematics |
ISBN | : 142001157X |
Although many books currently available describe statistical models and methods for analyzing longitudinal data, they do not highlight connections between various research threads in the statistical literature. Responding to this void, Longitudinal Data Analysis provides a clear, comprehensive, and unified overview of state-of-the-art theory
Author | : Yury A. Kutoyants |
Publisher | : Springer Science & Business Media |
Total Pages | : 493 |
Release | : 2013-03-09 |
Genre | : Mathematics |
ISBN | : 144713866X |
The first book in inference for stochastic processes from a statistical, rather than a probabilistic, perspective. It provides a systematic exposition of theoretical results from over ten years of mathematical literature and presents, for the first time in book form, many new techniques and approaches.