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Functional continuum regression

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  • Zhou, Zhiyang

Abstract

Functional principal component regression (PCR) can fail to provide good prediction if the response is highly correlated with some excluded functional principal component(s). This situation is common since the construction of functional principal components never involves the response. Aiming at this shortcoming, we develop functional continuum regression (CR). The framework of functional CR includes, as special cases, both functional PCR and functional partial least squares (PLS). Under certain circumstances, functional CR is more accurate than functional PCR and functional PLS both in estimation and prediction; evidence to this effect is provided through simulations and numerical case studies. Also, we demonstrate the consistency of estimators given by functional CR.

Suggested Citation

  • Zhou, Zhiyang, 2019. "Functional continuum regression," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 328-346.
    • Handle: RePEc:eee:jmvana:v:173:y:2019:i:c:p:328-346
    DOI: 10.1016/j.jmva.2019.03.006
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    References listed on IDEAS

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