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Estimating Unobserved Complementarities between Entrepreneurs and Venture Capitalists Matlab Code (view source)
Revision as of 18:38, 24 January 2018
, 18:38, 24 January 2018no edit summary
Main Project here: [[Estimating Unobserved Complementarities between Entrepreneurs and Venture Capitalists]]
==Important contractions==
*GMM: Generalized Method of Moments
*MSM: Markov State Model
*MLE: Maximum Likelihood Estimation
*GA: Genetic Algorithm
*SE:
==How to run==
First, apparently, you need a gurobi license, which can be obtained (free) [http://www.gurobi.com/registration/academic-license-reg here].
In master.m, edit the options section to reflect what you want the code to do. Then run it.
'''task:''' Can take the values {'data', 'monte', 'monte_data'}.
'''estimator:''' Can take the values {'MLE', 'MSM', 'compare'}.* MSM stands for Markov State Model* MLE stands for Maximum Likelihood Estimation* compare** compare is valid only under task='monte''''use_solver:''' Can take the values {'fminunc', 'ga', 'patternsearch', 'cmaes'}.* GA stands for genetic algorithm* fminunc* patternsearch* cmaes'''error_type''' (currently hard coded as 1): 1 for match specific errors, with the error distribution following an exchangeable structure. var(e) = sig^2, and cov(e,e') = 1/4*sig^2. 2 for agent specific errors, with the error structure of match <i, j> as sig*ei*ej.
'''use_solver:''' Can take the values {'ga'}. '''error_type''' (currently hard coded as 1 and isn't fully written to support 2): 1 for match specific errors, with the error distribution following an exchangeable structure. var(e) = sig^2, and cov(e,e') = 1/4*sig^2. 2 for agent specific errors, with the error structure of match <i, j> as sig*ei*ej. ===strip_master.m(deleted in readjusted code)===
Seems to be a version of master.m that only uses the parameters task = 'monte_data', use_solver = 'ga', and estimator = 'MSM' (which apparently are the only values that work for master.m, but unverified).
===msmf_corr_coeff.m===
This is the fitness function. Takes a vector and returns a scalar.
==Location/Structure of Data==
