Statistical inference for oscillation processes. Issue 1 (2nd January 2017)

• Record Type: Journal Article
• Authors: Dahlhaus, Rainer; Dumont, Thierry; Le Corff, Sylvain; Neddermeyer, Jan C.
• Is Part Of: Statistics. Volume 51:Issue 1(2017)
• Page Start: 61
• Page End: 83
• Publication Date: 2017-01-02
• Subjects: Oscillation process -- phase estimation -- instantaneous frequencies -- oscillation pattern -- Rao-Backwellized particle smoother -- Rössler attractor -- electrocardiogram; Mathematical statistics -- Periodicals; 519.505
• DOI: 10.1080/02331888.2016.1266985
• Languages: English
• ISSNs: 0233-1888

Abstract

ABSTRACT: A new model for time series with a specific oscillation pattern is proposed. The model consists of a hidden phase process controlling the speed of polling and a nonparametric curve characterizing the pattern, leading together to a generalized state space model. Identifiability of the model is proved and a method for statistical inference based on a particle smoother and a nonparametric EM algorithm is developed. In particular, the oscillation pattern and the unobserved phase process are estimated. The proposed algorithms are computationally efficient and their performance is assessed through simulations and an application to human electrocardiogram recordings.