info:eu-repo/semantics/article
Sucient dimension reduction and prediction in regression: Asymptotic results
Fecha
2019-03Registro en:
Forzani, Liliana Maria; Rodriguez, Daniela Andrea; Smucler, Ezequiel; Sued, Raquel Mariela; Sucient dimension reduction and prediction in regression: Asymptotic results; Elsevier Inc; Journal Of Multivariate Analysis; 171; 3-2019; 339-349
0047-259X
CONICET Digital
CONICET
Autor
Forzani, Liliana Maria
Rodriguez, Daniela Andrea
Smucler, Ezequiel
Sued, Raquel Mariela
Resumen
We consider model-based sufficient dimension reduction for generalized linear models and prove the consistency and asymptotic normality of the prediction estimator studied empirically for the normal case by Adragni and Cook (2009) when a sample version of the sufficient dimension reduction is used. Moreover, we provide a formula for the prediction that does need require explicitly computing the reduction.