IMAL 13325
INSTITUTO DE MATEMATICA APLICADA DEL LITORAL "DRA. ELEONOR HARBOURE"
Unidad Ejecutora - UE
artículos
Título:
Likelihood-based sufficient dimension reduction
Autor/es:
LILIANA FORZANI; COOK, R. D.
Revista:
Journal of the American Statistical Association
Referencias:
Año: 2008 p. 1 - 1
ISSN:
0162-1459
Resumen:
We obtain the maximum likelihood estimator of the central subspace underconditional normality of the predictors given the response. Analytically and insimulations we found that our new estimator can preform much better than slicedinverse regression, sliced average variance estimation and directional regression,and that it seems quite robust to deviations from normality.
