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.File in questo prodotto:
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