IC   26529
INSTITUTO DE CALCULO REBECA CHEREP DE GUBER
Unidad Ejecutora - UE
artículos
Título:
Sufficient dimension reduction and prediction in regression: Asymptotic results.
Autor/es:
EZEQUIEL SMUCLER; LILIANAFORZANIA; MARIELA SUED; DANIELA RODRIGUEZ
Revista:
JOURNAL OF MULTIVARIATE ANALYSIS
Editorial:
ELSEVIER INC
Referencias:
Lugar: Amsterdam ; Año: 2019 vol. 171 p. 339 - 349
ISSN:
0047-259X
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 predictionthat does need require explicitly computing the reduction.