pmlpp/MLPP/GaussMarkovChecker/GaussMarkovChecker.cpp

60 lines
1.9 KiB
C++

//
// 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;
}
}