Asymptotics for penalised splines in generalised additive models

Takuma Yoshida and Kanta Naito

Journal of Nonparametric Statistics, 2014, vol. 26, issue 2, 269-289

Abstract: This paper discusses asymptotic theory for penalised spline estimators in generalised additive models. The purpose of this paper is to establish the asymptotic bias and variance as well as the asymptotic normality of the ridge-corrected penalised spline estimator. Furthermore, the asymptotics for the penalised quasi-likelihood fit in mixed models are also discussed.

Date: 2014
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DOI: 10.1080/10485252.2014.899360

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