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*GMM: Generalized Method of Moments
*MSM: Markov State ModelMethod of Simulated Moments
*MLE: Maximum Likelihood Estimation
*GA: Genetic Algorithm
*SE:Standard Error
==How to run==
This is the fitness function. Takes a vector and returns a scalar. GA minimizes this function.
 
===moments.m===
 
Generates the moments needed for the GMM.
==Location/Structure of Data==
'''empirics_match_specific_2nd_stage_ga''':
'''empirics_match_specific_with_se''': Saved if task = 'data'
'''type_(error_type)_monte_mktsize_(mktsize)_K_(K)_S_(S)_rep_(montenn)''':
because it returns a scalar, but should return a 166x1 vector.
 
Better fix notes:
The problem is narrowed down to the section of mkt_resample.m before the call to moments. Somehow the parameters to moments are changed such that it returns a scalar.
 
Solution found (I think):
monte_M cannot be set to 1. For values greater than 1, the program seems to work. It doesn't crash, anyway.
==Profiling==
Monte_data and monte run much faster than data, because data is so large.
 
==Notes==
 
There is a lot of unused code. For example, monte_std and monte_x seem to only be assigned, not used.

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