On theoretical and empirical aspects of marginal distribution choice models

Management Science

Volumn 60, Issue 6, 2014, Pages 1511-1531

  Mishra, Vinit Kumar ^a   Natarajan, Karthik ^b   Padmanabhan, Dhanesh ^c   Teo, Chung Piaw ^d   Li, Xiaobo ^e  

^a UNIVERSITY OF SYDNEY   (Australia)

^b SINGAPORE UNIVERSITY OF TECHNOLOGY AND DESIGN   (Singapore)

^c GENERAL MOTORS CORPORATION   (United States)

^d NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^e UNIVERSITY OF MINNESOTA   (United States)

Author keywords

Applied probability; Convex optimization; Discrete choice model; Machine learning

Indexed keywords

ARTIFICIAL INTELLIGENCE; CONVEX OPTIMIZATION; LEARNING SYSTEMS; PROBABILITY DISTRIBUTIONS;

APPLIED PROBABILITY; DISCRETE CHOICE MODELS; ERROR DISTRIBUTIONS; FISHER'S INFORMATION; GENERALIZED EXTREME VALUE; MACHINE LEARNING APPROACHES; MARGINAL DISTRIBUTION; MULTINOMIAL LOGIT MODEL;

FISHER INFORMATION MATRIX;

EID: 84902288074     PISSN: 00251909     EISSN: 15265501     Source Type: Journal    
DOI: 10.1287/mnsc.2014.1906     Document Type: Article

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