Graphical models use graphs to represent conditional independence relationships among random variables of amultivariate probability distribution. This paper introduces a new kind of chain graph models in which nodes also represent marked point processes. This is relevant to the analysis of event history data, i.e. data consisting of random sequences of events or time durations of states. Survival analysis and duration models are particular cases. This article considers the case of two marked point processes. The idea consists of representing a whole process by a single node and a conditional independence statement by a lack of connection.We refer to the resulting models as graphical duration models.

On the inclusion of bivariate marked point processes in graphical models / A. GOTTARD. - In: METRIKA. - ISSN 0026-1335. - STAMPA. - 66:(2007), pp. 269-287. [10.1007/s00184-006-0110-7]

On the inclusion of bivariate marked point processes in graphical models

GOTTARD, ANNA
2007

Abstract

Graphical models use graphs to represent conditional independence relationships among random variables of amultivariate probability distribution. This paper introduces a new kind of chain graph models in which nodes also represent marked point processes. This is relevant to the analysis of event history data, i.e. data consisting of random sequences of events or time durations of states. Survival analysis and duration models are particular cases. This article considers the case of two marked point processes. The idea consists of representing a whole process by a single node and a conditional independence statement by a lack of connection.We refer to the resulting models as graphical duration models.
2007
66
269
287
A. GOTTARD
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/253150
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