We propose a data-constrained generalized maximum entropy (GME) estimator for discrete sequential move games of perfect information which can be easily implemented on optimization software with high-level interfaces such as GAMS. Unlike most other work on the estimation of complete information...

We propose simulation based estimation for discrete sequential move games of perfect information which relies on the simulated moments and importance sampling. We use importance sampling techniques not only to reduce computational burden and simulation error, but also to overcome non-smoothness...

We propose a data-constrained generalized maximum entropy estimator for discrete sequential move games of perfect information. Unlike most other work on the estimation of complete information games, the method we proposed is data constrained and requires o simulation or assumptions about the...