LDR: A Package for Likelihood-Based Sufficient Dimension Reduction

R. Dennis Cook, Liliana M. Forzani and Diego R. Tomassi

Journal of Statistical Software, 2011, vol. 039, issue i03

Abstract: 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. The methods 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.

Date: 2011-03-01
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Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:039:i03

DOI: 10.18637/jss.v039.i03

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