Name
Title | ||
|---|---|---|
A Convex Optimization Approach for Computing Correlated Choice Probabilities with Many Alternatives |
Abstract | ||
|---|---|---|
A popular discrete choice model that incorporates correlation information is the multinomial probit (MNP) model where the random utilities of the alternatives are chosen from a multivariate normal distribution. Computing the choice probabilities is challenging in the MNP model when the number of alternatives is large. Mishra et al. (IEEE Transactions on Automatic Control, 2012) have proposed a sem... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/TAC.2018.2875673 | IEEE Transactions on Automatic Control |
Keywords | Field | DocType |
Computational modeling,Correlation,Optimization,Covariance matrices,Perturbation methods,Convex functions | Multinomial probit,Gradient method,Mathematical optimization,Convex function,Multivariate normal distribution,Discrete choice,Covariance matrix,Mathematics,Semidefinite programming,Covariance | Journal |
Volume | Issue | ISSN |
64 | 1 | 0018-9286 |
Citations | PageRank | References |
2 | 0.37 | 9 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| selin damla | 1 | 2 | 0.37 |
| ahipasaogluxiaobo li | 2 | 2 | 0.37 |
| Karthik Natarajan | 3 | 407 | 31.52 |