| 期刊全稱 | Asymmetric Kernel Smoothing | | 期刊簡稱 | Theory and Applicati | | 影響因子2023 | Masayuki Hirukawa | | 視頻video | http://file.papertrans.cn/164/163750/163750.mp4 | | 發(fā)行地址 | Provides an accessible collection of recently developed nonparametric smoothing techniques for estimation and testing procedures.Explores the statistical properties of estimators and test statistics s | | 學科分類 | SpringerBriefs in Statistics | | 圖書封面 |  | | 影響因子 | .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 concen | | Pindex | Book 2018 |
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