Abstract
In this chapter we illustrate how the minimum distance estimate described in Chapter 10 may be used to select various parameters simultaneously in an almost optimal manner. The examples are all simple multiparameter versions of the kernel estimate. Once again, the methods applied here are fully combinatorial, as the only thing we need in each case is a suitable upper bound for the shatter coefficient appearing in Theorem 10.3.
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Devroye, L., Lugosi, G. (2001). Multiparameter Kernel Estimates. In: Combinatorial Methods in Density Estimation. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4613-0125-7_12
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DOI: https://doi.org/10.1007/978-1-4613-0125-7_12
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