Titlebook: Asymmetric Kernel Smoothing; Theory and Applicati Masayuki Hirukawa Book 2018 The Author(s) 2018 Asymmetric Kernel.Kernel Smoothing.Boundar

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Regression Estimation,As mentioned in Chap. ., research in asymmetric kernels appears to begin with regression estimation. This chapter investigates nonparametric regression estimation smoothed by asymmetric kernels.

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Asymmetric Kernels in Action,The final chapter presents two applications of asymmetric kernel smoothing to real data. One is on density estimation and the other on a testing problem. Each empirical illustration is closely related to the author’s latest work.

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Asymmetric Kernels: An Introduction,ry of asymmetric kernels, we provide an informal definition and a list of the kernels. Obviously it is difficult and even uneconomical to investigate each of them fully within the limited space of this book. Instead, we concentrate on a few kernels throughout, explain why they are chosen, and illust

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Specification Testing, Each test has an application-driven flavor, and it is shown to be consistent, i.e., the power of the test approaches one as the sample size diverges. In particular, the test of discontinuity in densities in Sect. . extends an existing method and contains some new results.

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