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Choice Computation - Correlated Utilities

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Karthik Natarajan

on 16 June 2015

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Transcript of Choice Computation - Correlated Utilities

A Convex Optimization Approach for Computing Correlated Choice Probabilities with Many Alternatives

Choice Probability
Cross Moment Model
New Results
Computational Results

Closed form, numerical integration or simulation

Convex optimization formulation
Random utility maximization

Representative agent model

i.i.d. Gumbel random error term

Entropy maximization
Random utility maximization

Representative agent model
Random utility maximization

Representative agent model
Multivariate normal random error terms with
zero mean and given covariance matrix

Several simulation based methods

No simple form that is amenable for computation

Multinomial Logit & Probit Models
Distribution that maximizes the expected agent utility given first two moments:

Previous works shows that this reduces to solving a semidefinite program (SDP):
Choice probability in CMM
A representative agent model for CMM:

Efficiently computable gradient that makes a simple gradient ascent method suitable for CMM:
Selin Damla Ahipasaoglu (SUTD), Xiaobo Li (University of Minnesota), Karthik Natarajan (SUTD)
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