Asymmetric Kernel Smoothing

Theory and Applications in Economics and Finance

Business & Finance, Economics, Statistics, Nonfiction, Science & Nature, Mathematics
Cover of the book Asymmetric Kernel Smoothing by Masayuki Hirukawa, Springer Singapore
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Masayuki Hirukawa ISBN: 9789811054662
Publisher: Springer Singapore Publication: June 8, 2018
Imprint: Springer Language: English
Author: Masayuki Hirukawa
ISBN: 9789811054662
Publisher: Springer Singapore
Publication: June 8, 2018
Imprint: Springer
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

More books from Springer Singapore

Cover of the book Brachiopods around the Permian-Triassic Boundary of South China by Masayuki Hirukawa
Cover of the book Refugee Law in India by Masayuki Hirukawa
Cover of the book A Study of the Turning Point of China’s Debt by Masayuki Hirukawa
Cover of the book Physical Layer Security in Random Cellular Networks by Masayuki Hirukawa
Cover of the book Assembled Lanthanide Complexes with Advanced Photophysical Properties by Masayuki Hirukawa
Cover of the book Wittgenstein’s Education: 'A Picture Held Us Captive’ by Masayuki Hirukawa
Cover of the book Water Resources Management by Masayuki Hirukawa
Cover of the book Innovations in Open and Flexible Education by Masayuki Hirukawa
Cover of the book Risks in Agriculture by Masayuki Hirukawa
Cover of the book Lymphatic Filariasis by Masayuki Hirukawa
Cover of the book Strategic Marketing Issues in Emerging Markets by Masayuki Hirukawa
Cover of the book Metallogenic Mechanism of the Galinge Polymetallic Iron Skarn Deposit, Qiman Tagh Mountains, Qinghai Province by Masayuki Hirukawa
Cover of the book Signal Processing in Neuroscience by Masayuki Hirukawa
Cover of the book Proceedings of the 2nd International Colloquium on Sports Science, Exercise, Engineering and Technology 2015 (ICoSSEET 2015) by Masayuki Hirukawa
Cover of the book Metamaterial Inspired Electromagnetic Applications by Masayuki Hirukawa
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy