A dynamic programming approach for quickly estimating large network-based MEV models

A dynamic programming approach for quickly estimating large network-based MEV models

We propose a way to estimate a family of static Multivariate Extreme Value (MEV) models with large choice sets in short computational time. The resulting model is also straightforward and fast to use for prediction. Following Daly and Bierlaire (2006), the correlation structure is defined by a roote...

Full description

Saved in:
Bibliographic Details
Main Authors: MAI, Tien, FREJINGER, Emma, FOSGEREAU, Mogens, BASTIN, Fabian
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2017
Subjects:
Multivariate extreme value models
Dynamic programming
Discrete choice
Maximum likelihood estimation
Nested fixed point algorithm
Value iteration
OS and Networks
Programming Languages and Compilers
Online Access:https://ink.library.smu.edu.sg/sis_research/5284
https://ink.library.smu.edu.sg/context/sis_research/article/6287/viewcontent/1_s2.0_S0191261515302216_main.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Singapore Management University
Language: English

Internet

https://ink.library.smu.edu.sg/sis_research/5284
https://ink.library.smu.edu.sg/context/sis_research/article/6287/viewcontent/1_s2.0_S0191261515302216_main.pdf

Similar Items