A Functional Hodrick-Prescott Filter

Research output: Contribution to journalArticle


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


External organisations
  • KTH Royal Institute of Technology
  • Linnaeus University
Research areas and keywords


  • Inverse problems, adaptive estimation, Hodrick–Prescott filter, smoothing, signal extraction, Gaussian measures on a Hilbert space
Original languageEnglish
JournalJournal of Inverse and Ill-Posed Problems (JIIP)
Publication statusE-pub ahead of print - 2016 Mar
Publication categoryResearch
Externally publishedYes