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• W2064282308 startingPage "113" @default.
• W2064282308 abstract "A class of nonlinear time-series models in which the underlying process follows a finite mixture of bilinear representations is proposed. The mixture feature appears in the conditional distribution of the process which is given as a finite mixture of distributions evaluated at the normed innovations of diagonal bilinear specifications. This class is aimed at capturing special characteristics exhibited by many observed time series such as tail heaviness, multimodality, asymmetry and change in regime. Some probabilistic properties of the proposed model, namely strict and second-order stationarity, geometric ergodicity, covariance structure, existence of higher order moments, tail behaviour and invertibility, are first studied. Parameter estimation is then performed through the EM algorithm, performance of which is shown via simulation experiments. Applications to some real-time-series data are proposed and through which it is shown how neglecting the mixture framework in a bilinear representation results in a loss in adequacy." @default.
• W2064282308 created "2016-06-24" @default.
• W2064282308 creator A5014540607 @default.
• W2064282308 creator A5063855488 @default.
• W2064282308 date "2010-03-01" @default.
• W2064282308 modified "2023-09-27" @default.
• W2064282308 title "On an independent and identically distributed mixture bilinear time-series model" @default.
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• W2064282308 doi "https://doi.org/10.1111/j.1467-9892.2009.00649.x" @default.
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