May 12, 2021 · We show that node centrality measures can be heavily affected by random errors and propose a flexible model based on the matrix-variate t distribution.
May 13, 2021 · In this paper, we propose a new Bayesian model for network data with matrix-variate t errors which accounts for heavy tails. (Tomarchio et al., ...
May 13, 2021 · The model is applied to filter out the noise from network data as a preliminary step before investigating the connectedness structure.
Networks represent a useful tool to describe relationships among financial firms and network analysis has been extensively used in recent ...
A Matrix-Variate t Model for Networks ; Authors. Billio, M; Casarin, R; Costola, M; Iacopini, M ; URI. https://qmro.qmul.ac.uk/xmlui/handle/123456789/84059 ...
We show that node centrality measures can be heavily affected by random errors and propose a flexible model based on the matrix-variate t distribution and a ...
Dec 1, 2023 · This paper adopts the Bayesian viewpoint and introduces a new matrix variate t-model in a prior sense by relying on the matrix variate gamma distribution for ...
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May 20, 2021 · GARR.tv è la piattaforma di live streaming e video on-demand dedicata alla comunità dell'Istruzione e della Ricerca, ...
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Posted: May 20, 2021
Posted: May 20, 2021
predictive matrix-variate t models on three network datasets (Friends, E.coli and Yeast). We randomly hold out 20% of each network data to test all the models.