A novel segmentation method is proposed for the analysis of bivariate times eries of intensities and angles that often occur in environmental applications. The model is based on a mixture of copula-based cylindrical distributions,whose parameters evolve according to a latent Markov chain.The model parsimoniously accommodates typical features of cylindrical time series such as circular-linear correlation, multimodality, skewness and temporal auto-correlation. A computationally efficient Expectation-Maximization algorithm is described to estimate the parameters and a parametric bootstrap routine is exploited to compute confidence intervals. These methods are illustrated on cylindrical time series of wave heights and directions in the Adriatic sea.
Francesco Lagona (2017). Copula-based segmentation of environmental time series with linear and circular components.. In Alessandra Petrucci and Rosanna Verde (a cura di), SIS 2017. Statistics and Data Science: new challenges, new generations. 28-30 June 2017 Florence (Italy). Proceedings of the Conference of the Italian Statistical Society (pp. 569-574). Firenze : Firenze University Press.
Titolo: | Copula-based segmentation of environmental time series with linear and circular components. |
Autori: | |
Data di pubblicazione: | 2017 |
Citazione: | Francesco Lagona (2017). Copula-based segmentation of environmental time series with linear and circular components.. In Alessandra Petrucci and Rosanna Verde (a cura di), SIS 2017. Statistics and Data Science: new challenges, new generations. 28-30 June 2017 Florence (Italy). Proceedings of the Conference of the Italian Statistical Society (pp. 569-574). Firenze : Firenze University Press. |
Handle: | http://hdl.handle.net/11590/321384 |
ISBN: | 978-88-6453-521-0 |
Appare nelle tipologie: | 2.1 Contributo in volume (Capitolo o Saggio) |