IMAL   13325
INSTITUTO DE MATEMATICA APLICADA DEL LITORAL "DRA. ELEONOR HARBOURE"
Unidad Ejecutora - UE
artículos
Título:
Estimating Sufficient Reductions of the Predictors in Abundant High-Dimensional Regressions.
Autor/es:
COOK, R. D. AND FORZANI, L. AND ROTHMAN, A.
Revista:
ANNALS OF STATISTICS, THE
Editorial:
INST MATHEMATICAL STATISTICS
Referencias:
Año: 2012 vol. 40 p. 353 - 384
ISSN:
0090-5364
Resumen:
We study the asymptotic behavior of a class of methods for sufficient dimension reduction in high-dimension regressions, as the sample size and number of predictors grow in various alignments. It is demonstrated that these methods are consistent in a variety of settings, particularly in abundant regressions where most predictors contribute some information on the response, and oracle rates are possible. Simulation results are presented to support the theoretical conclusion.