A Bayesian network model for linear circular data

Kato, Shogo and Leguey Vitoriano, Ignacio and Bielza Lozoya, María Concepción and Larrañaga Múgica, Pedro María (2017). A Bayesian network model for linear circular data. In: "10th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2017)", 16-18 Dic 2017, Londres, Reino Unido. p. 155.

Description

Title: A Bayesian network model for linear circular data
Author/s:
  • Kato, Shogo
  • Leguey Vitoriano, Ignacio
  • Bielza Lozoya, María Concepción
  • Larrañaga Múgica, Pedro María
Item Type: Presentation at Congress or Conference (Article)
Event Title: 10th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2017)
Event Dates: 16-18 Dic 2017
Event Location: Londres, Reino Unido
Title of Book: CMStatistics 2017
Date: 2017
Subjects:
Faculty: E.T.S. de Ingenieros Informáticos (UPM)
Department: Inteligencia Artificial
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

In numerous academic fields, it is common that data include circular observations expressed as angles [−π, π). Because of the periodic nature of circular observations, a direct application of ordinary Bayesian network techniques could lead to an erroneous result in analysis. In this talk, we propose a tree-structured Bayesian network model for ‘linear–circular’ data, namely, data comprising of multiple linear and circular observations. The proposed model is an extension of the Bayesian network model of Leguey et al. (2016) for multivariate circular data

More information

Item ID: 51060
DC Identifier: http://oa.upm.es/51060/
OAI Identifier: oai:oa.upm.es:51060
Official URL: http://cmstatistics.org/CMStatistics2017/fullprogramme.php
Deposited by: Memoria Investigacion
Deposited on: 05 Jun 2019 08:53
Last Modified: 05 Jun 2019 08:53
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