A hidden Markov model is proposed for segmenting cylindrical time series according to a finite number of latent classes, associated with copula-based cylindrical densities. It provides a parsimonious and computationally tractable approach that integrates circular–linear correlation, multimodality and temporal auto-correlation.

Lagona, F. (2019). Copula-based segmentation of cylindrical time series. STATISTICS & PROBABILITY LETTERS, 144, 16-22 [10.1016/j.spl.2018.04.011].

Copula-based segmentation of cylindrical time series

Francesco Lagona
2019-01-01

Abstract

A hidden Markov model is proposed for segmenting cylindrical time series according to a finite number of latent classes, associated with copula-based cylindrical densities. It provides a parsimonious and computationally tractable approach that integrates circular–linear correlation, multimodality and temporal auto-correlation.
2019
Lagona, F. (2019). Copula-based segmentation of cylindrical time series. STATISTICS & PROBABILITY LETTERS, 144, 16-22 [10.1016/j.spl.2018.04.011].
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11590/335443
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 8
  • ???jsp.display-item.citation.isi??? 7
social impact