Abstract
With a basic understanding of wavelet theory and a knowledge of the practical issues involved in applying wavelets to observed data, we are now ready to extend the basic methods of Chapter 3 to more sophisticated techniques on a wide variety of applications. Perhaps the most common wavelet application in statistics is nonparametric regression, which is covered in some depth in Section 7.1. This will serve as a groundwork for other applications treated later in this chapter: density estimation, estimation of the spectral density in time series, and the general change-point problem. Extensions of these methods will be given in the context of nonparametric regression in Chapter 8.
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© 1997 Springer Science+Business Media New York
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Ogden, R.T. (1997). Other Applications. In: Essential Wavelets for Statistical Applications and Data Analysis. Birkhäuser, Boston, MA. https://doi.org/10.1007/978-1-4612-0709-2_7
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DOI: https://doi.org/10.1007/978-1-4612-0709-2_7
Publisher Name: Birkhäuser, Boston, MA
Print ISBN: 978-1-4612-6876-5
Online ISBN: 978-1-4612-0709-2
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