mirror of https://github.com/Relintai/pmlpp.git
58 lines
1.6 KiB
C++
58 lines
1.6 KiB
C++
//
|
|
// GaussMarkovChecker.cpp
|
|
//
|
|
// Created by Marc Melikyan on 11/13/20.
|
|
//
|
|
|
|
#include "gauss_markov_checker.h"
|
|
#include "../stat/stat.h"
|
|
#include <iostream>
|
|
|
|
|
|
void MLPPGaussMarkovChecker::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 MLPPGaussMarkovChecker::arithmeticMean(std::vector<double> eps) {
|
|
MLPPStat stat;
|
|
if (stat.mean(eps) == 0) {
|
|
return 1;
|
|
} else {
|
|
return 0;
|
|
}
|
|
}
|
|
|
|
bool MLPPGaussMarkovChecker::homoscedasticity(std::vector<double> 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<double> 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;
|
|
}
|
|
|