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Semiparametric smoothing for discrete data

Faddy, M. J. and Jones, M. C. (1998). Semiparametric smoothing for discrete data. Biometrika, 85(1) pp. 131–138.

DOI (Digital Object Identifier) Link: http://dx.doi.org/10.1093/biomet/85.1.131
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Abstract

A method for semiparametric smoothing of discrete data is proposed. The method consists of the repeated application of a Markov chain transition matrix constructed so as to have a given standard discrete parametric vehicle model as its stationary distribution. Theory and practical examples suggest that the approach yields improved performance over fully nonparametric methods when the vehicle model is a good one and otherwise provides a method comparable to fully nonparametric smoothers. An automatic choice of the amount of smoothing is proposed and used.

Item Type: Journal Article
Copyright Holders: 1998 Biometrika Trust
ISSN: 1464-3510
Keywords: binomial; Markov chain; poisson; probability function estimate; smoothing parameter selection; stationary distribution
Academic Unit/Department: Mathematics, Computing and Technology > Mathematics and Statistics
Item ID: 24030
Depositing User: Sarah Frain
Date Deposited: 04 May 2011 14:10
Last Modified: 04 May 2011 14:10
URI: http://oro.open.ac.uk/id/eprint/24030
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