Jan 25, 2017 · The goal of this work is to estimate and validate computational models of dynamic decision making against data on sequences of actual ...

The goal of this work is to estimate and validate computational models of dynamic decision making against data on sequences of actual decisions made in ...

The goal of this work is to estimate and validate computational models of dynamic decision making against data on sequences of actual decisions made in ...

The goal of this work is to estimate and validate computational models of dynamic decision making against data on sequences of actual decisions made.

Eliminating this computational bottleneck is the key to providing a seamless link between estimating the model and performing post-estimation counterfactuals.

In this article, we review two lines of research investigating how people handle the challenges of dynamic decision making.

This paper analyses a new estimator for the structural parameters of dynamic models of discrete choice.

We show that the three common approaches for dealing with censored data—data deletion, imputation, and computation of the complete data likelihood—can all be ...

First, even if the data is time aggregated, the counterfactual analysis can leverage the full computational benefit of the underlying continuous time process.

This paper develops a general framework for constructing models of the cognitive processes underlying both inferential and preferential choice among any ...