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Kernel smoothing for finite populations

✍ Scribed by M. C. Jones; I. S. Bradbury

Book ID
104641391
Publisher
Springer US
Year
1993
Tongue
English
Weight
501 KB
Volume
3
Category
Article
ISSN
0960-3174

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✦ Synopsis

We identify a role for smooth curve provision in the finite population context. The performance of kernel density estimates in this scenario is explored, and they are tailored to the finite population situation especially by developing a method of data-based selection of the smoothing parameter appropriate to this problem. Simulated examples are given, including some from the particular context of permutation distributions which first motivated this investigation.

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In multivariate discrimination by the discrete kernel method the allocation rule is Bayrisk consistent if the smoothing parameter is choeen by maximizstion of the leaving-one-out nonerror rate. It is shown that oonaistency still holda if the leeving-one-out nonerror rate is replaced by a smoothed ve