pygambit.qre.fit_fixedpoint#
- pygambit.qre.fit_fixedpoint(data: MixedStrategyProfileDouble) LogitQREMixedStrategyFitResult#
Use maximum likelihood estimation to find the logit quantal response equilibrium on the principal branch for a strategic game which best fits empirical frequencies of play. [1]
New in version 16.1.0.
- Parameters:
data (MixedStrategyProfileDouble) – The empirical distribution of play to which to fit the QRE. To obtain the correct resulting log-likelihood, these should be expressed as total counts of observations of each strategy rather than probabilities.
- Returns:
The result of the estimation represented as a
LogitQREMixedStrategyFitResultobject.- Return type:
See also
fit_empiricalEstimate QRE by approximation of the correspondence using independent decision problems.
References