Overview
- Provides an accessible collection of recently developed nonparametric smoothing techniques for estimation and testing procedures
- Explores the statistical properties of estimators and test statistics smoothed by asymmetric kernels, in comparison with those smoothed by conventional symmetric kernels
- Includes real data analyses in economics and finance, overcoming the methodological issues that cannot be readilyhandled by conventional kernel methods
Part of the book series: SpringerBriefs in Statistics (BRIEFSSTATIST)
Part of the book sub series: JSS Research Series in Statistics (JSSRES)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (6 chapters)
Keywords
About this book
This is the first book to provide an accessible and comprehensive introduction to a newly developed smoothing technique using asymmetric kernel functions. Further, it discusses the statistical properties of estimators and test statistics using asymmetric kernels. The topics addressed include the bias-variance tradeoff, smoothing parameter choices, achieving rate improvements with bias reduction techniques, and estimation with weakly dependent data. Further, the large- and finite-sample properties of estimators and test statistics smoothed by asymmetric kernels are compared with those smoothed by symmetric kernels. Lastly, the book addresses the applications of asymmetric kernel estimation and testing to various forms of nonnegative economic and financial data.
Until recently, the most popularly chosen nonparametric methods used symmetric kernel functions to estimate probability density functions of symmetric distributions with unbounded support. Yet many types of economic and financial data are nonnegative and violate the presumed conditions of conventional methods. Examples include incomes, wages, short-term interest rates, and insurance claims. Such observations are often concentrated near the boundary and have long tails with sparse data. Smoothing with asymmetric kernel functions has increasingly gained attention, because the approach successfully addresses the issues arising from distributions that have natural boundaries at the origin and heavy positive skewness. Offering an overview of recently developed kernel methods, complemented by intuitive explanations and mathematical proofs, this book is highly recommended to all readers seeking an in-depth and up-to-date guide to nonparametric estimation methods employing asymmetric kernel smoothing.Authors and Affiliations
About the author
Masayuki Hirukawa, Faculty of Economics, Ryukoku University
Bibliographic Information
Book Title: Asymmetric Kernel Smoothing
Book Subtitle: Theory and Applications in Economics and Finance
Authors: Masayuki Hirukawa
Series Title: SpringerBriefs in Statistics
DOI: https://doi.org/10.1007/978-981-10-5466-2
Publisher: Springer Singapore
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Author(s) 2018
Softcover ISBN: 978-981-10-5465-5Published: 02 July 2018
eBook ISBN: 978-981-10-5466-2Published: 08 June 2018
Series ISSN: 2191-544X
Series E-ISSN: 2191-5458
Edition Number: 1
Number of Pages: XII, 110
Number of Illustrations: 5 b/w illustrations
Topics: Statistics for Business, Management, Economics, Finance, Insurance, Statistical Theory and Methods, Statistics for Social Sciences, Humanities, Law, Statistics and Computing/Statistics Programs