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Practical performance of local likelihood for circular density estimation. (English) Zbl 1510.62164

Summary: Local likelihood has been mainly developed from an asymptotic point of view, with little attention to finite sample size issues. The present paper provides simulation evidence of how likelihood density estimation practically performs from two points of view. First, we explore the impact of the normalization step of the final estimate, second we show the effectiveness of higher order fits in identifying modes present in the population when small sample sizes are available. We refer to circular data, nevertheless it is easily seen that our findings straightforwardly extend to the Euclidean setting, where they appear to be somehow new.

MSC:

62G07 Density estimation
62-08 Computational methods for problems pertaining to statistics

Software:

KernSmooth
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Full Text: DOI

References:

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