EGC: Sparse covariance estimation in logit mixture models

EGC: Sparse covariance estimation in logit mixture models

This paper introduces a new data-driven methodology for estimating sparse covariance matrices of the random coefficients in logit mixture models. Researchers typically specify covariance matrices in logit mixture models under one of two extreme assumptions: either an unrestricted full covariance mat...

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Bibliographic Details
Main Authors: Aboutaleb, Youssef M, Danaf, Mazen, Xie, Yifei, Ben-Akiva, Moshe E
Other Authors: Massachusetts Institute of Technology. Intelligent Transportation Systems Laboratory
Format: Article
Language:English
Published: Oxford University Press (OUP) 2021
Online Access:https://hdl.handle.net/1721.1/132696

Internet

https://hdl.handle.net/1721.1/132696

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