Using DAGs to identify the sufficient dimension reduction in the Principal Fitted Components model
María Eugenia Szretter Noste
Statistics & Probability Letters, 2019, vol. 145, issue C, 317-320
Abstract:
We identify the sufficient reduction for the Principal Fitted Components model under mild conditions which generalize those considered in previous works. We give a short proof of the main result based on the d-separation for directed acyclic graphs (DAGs), linking two areas that, to our knowledge, have not been linked before in statistics.
Keywords: Sufficient dimension reduction; Directed acyclic graphs; Principal Fitted Components model; Conditional independence (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167715218302839
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:145:y:2019:i:c:p:317-320
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01
DOI: 10.1016/j.spl.2018.08.008
Access Statistics for this article
Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul
More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().