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Kernel Density Estimation for Compositional Data
Author(s) -
Aitchison J.,
Lauder I. J.
Publication year - 1985
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.2307/2347365
Subject(s) - kernel density estimation , statistics , estimation , density estimation , computer science , econometrics , mathematics , estimator , economics , management
SUMMARY Although rich parametric families of distributions over the simplex now exist for describing patterns of variability of compositional data, there remain problems where such descriptions fail. For such cases this paper suggests two main kernel methods of density estimation and compares their performance on real and simulated data sets.
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