IMAL   13325
INSTITUTO DE MATEMATICA APLICADA DEL LITORAL "DRA. ELEONOR HARBOURE"
Unidad Ejecutora - UE
artículos
Título:
LDR: a package for likelihood-based sufficient dimension reduction
Autor/es:
R.D. COOK; L. FORZANI; D. TOMASSI
Revista:
JOURNAL OF STATISTICAL SOFTWARE
Editorial:
JOURNAL STATISTICAL SOFTWARE
Referencias:
Año: 2011 vol. 39 p. 1 - 12
ISSN:
1548-7660
Resumen:
 We introduce a new MATLAB software package that implements several recently proposed likelihood-based methods for sufficient dimension reduction. Current capabilities include estimation of reduced subspaces with a fixed dimension d, as well as estimation of d by use of likelihood-ratio testing, permutation testing and information criteria. Themethods are suitable for preprocessing data for both regression and classification. Implementations of related estimators are also available. Although the software is more oriented to command-line operation, a graphical user interface is also provided for prototype computations.