A new hidden Markov model is proposed for the analysis of cylindrical time series, i.e. bivariate time series of intensities and angles. It allows to segment cylindrical time series according to a finite number of regimes that represent the conditional distributions of the data under specific environmental conditions. The model parsimoniously accommodates for circular-linear correlation, multimodality, skewness and temporal autocorrelation. A computationally efficient Expectation-Maximization algorithm is described to estimate the parameters and a parametric bootstrap routine is provided to compute confidence intervals. These methods are illustrated on cylindrical time series of wave heights and directions.

Lagona, F., Picone, M., Maruotti, A. (2015). A Hidden Markov model for the analysis of cylindrical time series. ENVIRONMETRICS, 26, 534-544 [10.1002/env.2355].

A Hidden Markov model for the analysis of cylindrical time series

LAGONA, Francesco;
2015-01-01

Abstract

A new hidden Markov model is proposed for the analysis of cylindrical time series, i.e. bivariate time series of intensities and angles. It allows to segment cylindrical time series according to a finite number of regimes that represent the conditional distributions of the data under specific environmental conditions. The model parsimoniously accommodates for circular-linear correlation, multimodality, skewness and temporal autocorrelation. A computationally efficient Expectation-Maximization algorithm is described to estimate the parameters and a parametric bootstrap routine is provided to compute confidence intervals. These methods are illustrated on cylindrical time series of wave heights and directions.
Lagona, F., Picone, M., Maruotti, A. (2015). A Hidden Markov model for the analysis of cylindrical time series. ENVIRONMETRICS, 26, 534-544 [10.1002/env.2355].
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/11590/119703
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 20
  • ???jsp.display-item.citation.isi??? 16
social impact