A Functional Hodrick Prescott Filter

Abstract

We propose a functional version of the Hodrick-Prescott filter for functional data which take values in an infinite dimensional separable Hilbert space. We further characterize the associated optimal smoothing parameter when the associated linear operator is compact and the underlying distribution of the data is Gaussian.

References in corpus (1)

• Posterior Contraction Rates for the Bayesian Approach to Linear Ill-Posed Inverse Problems

Cited by in corpus (1)

• A consistent estimator of the smoothing operator in the functional Hodrick-Prescott filter