mirror of https://github.com/Relintai/pmlpp.git
61 lines
1.7 KiB
C++
61 lines
1.7 KiB
C++
//
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// GaussMarkovChecker.cpp
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//
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// Created by Marc Melikyan on 11/13/20.
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//
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#include "gauss_markov_checker_old.h"
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#include "../stat/stat.h"
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#include <iostream>
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void MLPPGaussMarkovCheckerOld::checkGMConditions(std::vector<real_t> eps) {
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bool condition1 = arithmeticMean(eps);
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bool condition2 = homoscedasticity(eps);
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bool condition3 = exogeneity(eps);
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if (condition1 && condition2 && condition3) {
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std::cout << "Gauss-Markov conditions were not violated. You may use OLS to obtain a BLUE estimator" << std::endl;
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} else {
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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;
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}
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}
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bool MLPPGaussMarkovCheckerOld::arithmeticMean(std::vector<real_t> eps) {
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MLPPStat stat;
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if (stat.mean(eps) == 0) {
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return true;
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} else {
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return false;
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}
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}
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bool MLPPGaussMarkovCheckerOld::homoscedasticity(std::vector<real_t> eps) {
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MLPPStat stat;
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real_t currentVar = (eps[0] - stat.mean(eps)) * (eps[0] - stat.mean(eps)) / eps.size();
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for (uint32_t i = 0; i < eps.size(); i++) {
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if (currentVar != (eps[i] - stat.mean(eps)) * (eps[i] - stat.mean(eps)) / eps.size()) {
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return false;
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}
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}
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return true;
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}
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bool MLPPGaussMarkovCheckerOld::exogeneity(std::vector<real_t> eps) {
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MLPPStat stat;
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for (uint32_t i = 0; i < eps.size(); i++) {
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for (uint32_t j = 0; j < eps.size(); j++) {
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if (i != j) {
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if ((eps[i] - stat.mean(eps)) * (eps[j] - stat.mean(eps)) / eps.size() != 0) {
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return false;
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}
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}
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}
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}
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return true;
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}
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void MLPPGaussMarkovCheckerOld::_bind_methods() {
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}
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