pyblp.SimulationResults¶

class
pyblp.
SimulationResults
¶ Results of a solved simulation of synthetic BLP data.
The
SimulationResults.to_problem()
method can be used to convert the full set of simulated data (along with some basic default instruments) and configured information into aProblem
.
simulation
¶ Simulation
that created these results. Type
Simulation

product_data
¶ Simulated
Simulation.product_data
with product characteristics replaced so as to be consistent with the true parameters. IfSimulation.replace_endogenous()
was used to create these results, prices and market shares were replaced. IfSimulation.replace_exogenous()
was used, exogenous characteristics were replaced instead. Thedata_to_dict()
function can be used to convert this into a more usable data type. Type
recarray

delta
¶ Simulated mean utility, \(\delta\).
 Type
ndarray

costs
¶ Simulated marginal costs, \(c\).
 Type
ndarray

computation_time
¶ Number of seconds it took to compute prices and market shares.
 Type
float

fp_converged
¶ Flags for convergence of the iteration routine used to compute prices or \(\delta\) (depending on the method used to create these results) in each market. Flags are in the same order as
Simulation.unique_market_ids
. Type
ndarray

fp_iterations
¶ Number of major iterations completed by the iteration routine used to compute prices or \(\delta\) in each market. Counts are in the same order as
Simulation.unique_market_ids
. Type
ndarray

contraction_evaluations
¶ Number of times the contraction used to compute prices or \(\delta\) was evaluated in each market. Counts are in the same order as
Simulation.unique_market_ids
. Type
ndarray
Examples
Methods
compute_micro_values
(micro_moments)Compute simulated micro moment values \(v_m\).
to_dict
([attributes])Convert these results into a dictionary that maps attribute names to values.
to_problem
([product_formulations, …])Convert the solved simulation into a problem.
