R package ldr: Methods for likelihood-based dimension reduction in regression. Functions, methods, and data sets for fitting likelihood-based dimension reduction in regression, using principal fitted components (pfc), likelihood acquired directions (lad), covariance reducing models (core).
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References in zbMATH (referenced in 2 articles )
Showing results 1 to 2 of 2.
- Adragni, Kofi P.; Al-Najjar, Elias; Martin, Sean; Popuri, Sai K.; Raim, Andrew M.: Group-wise sufficient dimension reduction with principal fitted components (2016)
- Prendergast, Luke A.; Healey, Alan F.: Improving estimated sufficient summary plots in dimension reduction using minimization criteria based on initial estimates (2016)