Prediction and Stochastic Choice

Pathikrit Basu *

Computing and Mathematical Sciences, California Institute of Technology, United States.

*Author to whom correspondence should be addressed.


Abstract

In this paper, we study a non-parametric approach to prediction in stochastic choice models in economics. We show that VC complexity characterises the predictability of stochastic choice models. We establish prediction methods and provide corresponding rates of convergence.

Keywords: Statistical learning, VC dimension, stochastic choice


How to Cite

Basu, Pathikrit. 2024. “Prediction and Stochastic Choice”. Asian Journal of Probability and Statistics 26 (9):123-50. https://doi.org/10.9734/ajpas/2024/v26i9650.

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