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. - ELETTRONICO. - (2021), pp. 268-271. (Intervento presentato al convegno CLADAG 2021 13th Scientific Meeting of the Classification and Data Analysis Group tenutosi a Firenze nel 9-11 Settembre 2021).
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
