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Journal of the American Statistical Association Volume 118, 2023 - Issue 542
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Theory and Methods

Score-Driven Modeling of Spatio-Temporal Data

Francesca Gasperonia MRC Biostatistics Unit, University of Cambridge, Cambridge, UKCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0002-1713-9477View further author information
ORCID Icon,
Alessandra Luatib Department of Statistical Sciences, University of Bologna, Bologna, ItalyORCID Iconhttps://orcid.org/0000-0001-6407-9385View further author information
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Lucia Pacic Department of Statistical Sciences, Università Cattolica del Sacro Cuore, Milano, ItalyORCID Iconhttps://orcid.org/0000-0001-7403-2054View further author information
ORCID Icon &
Enzo D’Innocenzob Department of Statistical Sciences, University of Bologna, Bologna, ItalyView further author information
Pages 1066-1077 | Received 06 Nov 2020, Accepted 14 Aug 2021, Published online: 04 Oct 2021

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Enzo D’Innocenzo, Alessandra Luati & Mario Mazzocchi. (2023) A robust score-driven filter for multivariate time series. Econometric Reviews 42:5, pages 441-470.
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Andrea Guizzardi, Luca Vincenzo Ballestra & Enzo D’Innocenzo. (2024) Reverse engineering the last-minute on-line pricing practices: an application to hotels. Statistical Methods & Applications.
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P Gorgi, C S A Lauria & A Luati. (2023) On the optimality of score-driven models. Biometrika.
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Thomas L.A. Heil, Franziska J. Peter & Philipp Prange. (2022) Measuring 25 years of global equity market co-movement using a time-varying spatial model. Journal of International Money and Finance 128, pages 102708.
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