Approximating fragmented functional data by segments of Markov chains

A. Delaigle and P. Hall

Biometrika, 2016, vol. 103, issue 4, 779-799

Abstract: We consider curve extension and linear prediction for functional data observed only on a part of their domain, in the form of fragments. We suggest an approach based on a combination of Markov chains and nonparametric smoothing techniques, which enables us to extend the observed fragments and construct approximated prediction intervals around them, construct mean and covariance function estimators, and derive a linear predictor. The procedure is illustrated on real and simulated data.

Keywords: Crossvalidation; Functional principal component; Incomplete curve; Markov chain (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (7)

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