A semiparametric finite mixture of regression models is defined, with concomitant information assumed to influence both the component weights and the conditional means. The contribution of a concomitant variable is flexibly specified as a smooth function represented by cubic splines. A Bayesian estimation procedure is proposed and an empirical analysis of the baseball salaries dataset is illustrated.

Semiparametric finite mixture of regression models with Bayesian P-splines

Marco Berrettini;Giuliano Galimberti;Saverio Ranciati
2021

Abstract

A semiparametric finite mixture of regression models is defined, with concomitant information assumed to influence both the component weights and the conditional means. The contribution of a concomitant variable is flexibly specified as a smooth function represented by cubic splines. A Bayesian estimation procedure is proposed and an empirical analysis of the baseball salaries dataset is illustrated.
CLADAG 2021 Book of Abstracts and Short Papers
268
271
Marco Berrettini; Giuliano Galimberti; Saverio Ranciati
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/854944
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