Logistic regression and Ising networks: prediction and estimation when violating lasso assumptions
Abstract
The Ising model was originally developed to model magnetisation of solids in statistical physics. As a network of binary variables with the probability of becoming ’active’ depending only on direct neighbours, the Ising model appears appropriate for many other processes. For instance, it was recently applied in psychology to model co-occurrences of mental disorders. It has been shown that the connections between the variables (nodes) in the...
Paper Details
Title
Logistic regression and Ising networks: prediction and estimation when violating lasso assumptions
Published Date
Aug 11, 2018
Journal
Volume
46
Issue
1
Pages
49 - 72
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