// // GaussMarkovChecker.cpp // // Created by Marc Melikyan on 11/13/20. // #include "gauss_markov_checker.h" #include "../stat/stat.h" #include void MLPPGaussMarkovChecker::checkGMConditions(std::vector eps) { bool condition1 = arithmeticMean(eps); bool condition2 = homoscedasticity(eps); bool condition3 = exogeneity(eps); if (condition1 && condition2 && condition3) { std::cout << "Gauss-Markov conditions were not violated. You may use OLS to obtain a BLUE estimator" << std::endl; } else { std::cout << "A test of the expected value of 0 of the error terms returned " << std::boolalpha << condition1 << ", a test of homoscedasticity has returned " << std::boolalpha << condition2 << ", and a test of exogenity has returned " << std::boolalpha << "." << std::endl; } } bool MLPPGaussMarkovChecker::arithmeticMean(std::vector eps) { MLPPStat stat; if (stat.mean(eps) == 0) { return 1; } else { return 0; } } bool MLPPGaussMarkovChecker::homoscedasticity(std::vector eps) { MLPPStat stat; double currentVar = (eps[0] - stat.mean(eps)) * (eps[0] - stat.mean(eps)) / eps.size(); for (int i = 0; i < eps.size(); i++) { if (currentVar != (eps[i] - stat.mean(eps)) * (eps[i] - stat.mean(eps)) / eps.size()) { return 0; } } return 1; } bool MLPPGaussMarkovChecker::exogeneity(std::vector eps) { MLPPStat stat; for (int i = 0; i < eps.size(); i++) { for (int j = 0; j < eps.size(); j++) { if (i != j) { if ((eps[i] - stat.mean(eps)) * (eps[j] - stat.mean(eps)) / eps.size() != 0) { return 0; } } } } return 1; }