Faddy, M. J. and Jones, M. C.
|DOI (Digital Object Identifier) Link:||http://doi.org/10.1093/biomet/85.1.131|
|Google Scholar:||Look up in Google Scholar|
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|
|Keywords:||binomial; Markov chain; poisson; probability function estimate; smoothing parameter selection; stationary distribution|
|Academic Unit/Department:||Faculty of Science, Technology, Engineering and Mathematics (STEM) > Mathematics and Statistics
Faculty of Science, Technology, Engineering and Mathematics (STEM)
|Depositing User:||Sarah Frain|
|Date Deposited:||04 May 2011 14:10|
|Last Modified:||04 Oct 2016 10:47|
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