pmlpp/mlpp/gauss_markov_checker/gauss_markov_checker.cpp

//
//  GaussMarkovChecker.cpp
//
//  Created by Marc Melikyan on 11/13/20.
//

#include "GaussMarkovChecker.hpp"
#include "Stat/Stat.hpp"
#include <iostream>


namespace MLPP{
    void GaussMarkovChecker::checkGMConditions(std::vector<double> 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 GaussMarkovChecker::arithmeticMean(std::vector<double> eps){
        Stat stat;
        if(stat.mean(eps) == 0) {
            return 1;
        }
        else { return 0; }
    }
    
    bool GaussMarkovChecker::homoscedasticity(std::vector<double> eps){
        Stat 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 GaussMarkovChecker::exogeneity(std::vector<double> eps){
        Stat 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;
    }
}