In this paper we present a Bayesian model to analyze sequences of hospitalizations of patients affected by chronic heart disease, focusing not only on the sequence but also on the times between two next events; considering covariates and time, the model is able to identify the most relevant factors influencing the evolution.

(2014). Analysis of hospitalizations of patients affected by chronic heart disease . Retrieved from http://hdl.handle.net/10446/193139

Analysis of hospitalizations of patients affected by chronic heart disease

Argiento, Raffaele
2014-01-01

Abstract

In this paper we present a Bayesian model to analyze sequences of hospitalizations of patients affected by chronic heart disease, focusing not only on the sequence but also on the times between two next events; considering covariates and time, the model is able to identify the most relevant factors influencing the evolution.
2014
Inglese
The Contribution of Young Researchers to Bayesian Statistics. Proceedings of BAYSM2013
Lanzarone, Ettore; Ieva, Francesca;
978-3-319-02083-9
63
155
159
cartaceo
online
Switzerland
Cham
Springer
esperti anonimi
BAYSM 2013: 1st Bayesian Young Statisticians Meeting, CNR Milan, 5-6 June 2013
1st
Milan (Italy)
5-6 June 2013
internazionale
contributo
Settore SECS-S/01 - Statistica
Posterior Distribution; Weibull Distribution; Bayesian Model; Gibbs Sampling; Sampling Algorithm;
info:eu-repo/semantics/conferenceObject
4
Parodi, Alice; Ieva, Francesca; Guglielmi, Alessandra; Argiento, Raffaele
1.4 Contributi in atti di convegno - Contributions in conference proceedings::1.4.01 Contributi in atti di convegno - Conference presentations
reserved
Non definito
273
(2014). Analysis of hospitalizations of patients affected by chronic heart disease . Retrieved from http://hdl.handle.net/10446/193139
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