A flexible two-piece normal dynamic linear model

Emanuele Aliverti, Reinaldo B. Arellano-Valle, Fereshteh Kahrari and Bruno Scarpa ()
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Emanuele Aliverti: Università di Padova
Reinaldo B. Arellano-Valle: Pontificia Universidad Católica de Chile
Fereshteh Kahrari: Università di Padova
Bruno Scarpa: Università di Padova

Computational Statistics, 2023, vol. 38, issue 4, No 21, 2075-2096

Abstract: Abstract We construct a flexible dynamic linear model for the analysis and prediction of multivariate time series, assuming a two-piece normal initial distribution for the state vector. We derive a novel Kalman filter for this model, obtaining a two components mixture as predictive and filtering distributions. In order to estimate the covariance of the error sequences, we develop a Gibbs-sampling algorithm to perform Bayesian inference. The proposed approach is validated and compared with a Gaussian dynamic linear model in simulations and on a real data set.

Keywords: Two-piece normal distribution; Skew-normal distribution; Bayesian inference; Kalman filter; FFBS algorithm (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s00180-023-01355-3

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