Smoothness of conditional independence models for discrete data

Antonio Forcina

Journal of Multivariate Analysis, 2012, vol. 106, issue C, 49-56

Abstract: We investigate a family of conditional independence models defined by constraints on complete but non hierarchical marginal log–linear parameters. By exploiting results on the mixed parameterization, we show that these models are smooth when a certain Jacobian matrix has spectral radius strictly less than 1. In the simple context when only two marginals are involved, we prove that this condition is always satisfied. In the general case, we describe an efficient numerical test for checking whether the condition is satisfied with high probability. This approach is applied to several examples of non hierarchical conditional independence models and to a directed cyclic graph model; we establish that they are all smooth.

Keywords: Conditional independence; Marginal log–linear models; Mixed parameterizations; Smoothness (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0047259X11002144
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:jmvana:v:106:y:2012:i:c:p:49-56

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.jmva.2011.11.009

Access Statistics for this article

Journal of Multivariate Analysis is currently edited by de Leeuw, J.

More articles in Journal of Multivariate Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().