Anderson Darling Test in C++ - c++

Question

I am trying to compute the Anderson-Darling test found here. I followed the steps on Wikipedia and made sure that when I calculate the average and standard deviation of the data I am testing denoted X by using MATLAB. Also, I used a function called phi for computing the standard normal CDF, I have also tested this function to make sure it is correct which it is. Now I seem to have a problem when I actually compute the A-squared (denoted in Wikipedia, I denote it as A in C++).
Here is my function I made for Anderson-Darling Test:
void Anderson_Darling(int n, double X[]){
sort(X,X + n);
// Find the mean of X
double X_avg = 0.0;
double sum = 0.0;
for(int i = 0; i < n; i++){
sum += X[i];
}
X_avg = ((double)sum)/n;
// Find the variance of X
double X_sig = 0.0;
for(int i = 0; i < n; i++){
X_sig += (X[i] - X_avg)*(X[i] - X_avg);
}
X_sig /= n;
// The values X_i are standardized to create new values Y_i
double Y[n];
for(int i = 0; i < n; i++){
Y[i] = (X[i] - X_avg)/(sqrt(X_sig));
//cout << Y[i] << endl;
}
// With a standard normal CDF, we calculate the Anderson_Darling Statistic
double A = 0.0;
for(int i = 0; i < n; i++){
A += -n - 1/n *(2*(i) - 1)*(log(phi(Y[i])) + log(1 - phi(Y[n+1 - i])));
}
cout << A << endl;
}
Note, I know that the formula for Anderson-Darling (A-squared) starts with i = 1 to i = n, although when I changed the index to make it work in C++, I still get the same result without changing the index.
The value I get in C++ is:
-4e+006
The value I should get, received in MATLAB is:
0.2330
Any suggestions are greatly appreciated.
Here is my whole code:
#include <iostream>
#include <math.h>
#include <cmath>
#include <random>
#include <algorithm>
#include <chrono>
using namespace std;
double *Box_Muller(int n, double u[]);
double *Beasley_Springer_Moro(int n, double u[]);
void Anderson_Darling(int n, double X[]);
double phi(double x);
int main(){
int n = 2000;
double Mersenne[n];
random_device rd;
mt19937 e2(1);
uniform_real_distribution<double> dist(0, 1);
for(int i = 0; i < n; i++){
Mersenne[i] = dist(e2);
}
// Print Anderson Statistic for Mersenne 6a
double *result = new double[n];
result = Box_Muller(n,Mersenne);
Anderson_Darling(n,result);
return 0;
}
double *Box_Muller(int n, double u[]){
double *X = new double[n];
double Y[n];
double R_2[n];
double theta[n];
for(int i = 0; i < n; i++){
R_2[i] = -2.0*log(u[i]);
theta[i] = 2.0*M_PI*u[i+1];
}
for(int i = 0; i < n; i++){
X[i] = sqrt(-2.0*log(u[i]))*cos(2.0*M_PI*u[i+1]);
Y[i] = sqrt(-2.0*log(u[i]))*sin(2.0*M_PI*u[i+1]);
}
return X;
}
double *Beasley_Springer_Moro(int n, double u[]){
double y[n];
double r[n+1];
double *x = new double(n);
// Constants needed for algo
double a_0 = 2.50662823884; double b_0 = -8.47351093090;
double a_1 = -18.61500062529; double b_1 = 23.08336743743;
double a_2 = 41.39119773534; double b_2 = -21.06224101826;
double a_3 = -25.44106049637; double b_3 = 3.13082909833;
double c_0 = 0.3374754822726147; double c_5 = 0.0003951896511919;
double c_1 = 0.9761690190917186; double c_6 = 0.0000321767881768;
double c_2 = 0.1607979714918209; double c_7 = 0.0000002888167364;
double c_3 = 0.0276438810333863; double c_8 = 0.0000003960315187;
double c_4 = 0.0038405729373609;
// Set r and x to empty for now
for(int i = 0; i <= n; i++){
r[i] = 0.0;
x[i] = 0.0;
}
for(int i = 1; i <= n; i++){
y[i] = u[i] - 0.5;
if(fabs(y[i]) < 0.42){
r[i] = pow(y[i],2.0);
x[i] = y[i]*(((a_3*r[i] + a_2)*r[i] + a_1)*r[i] + a_0)/((((b_3*r[i] + b_2)*r[i] + b_1)*r[i] + b_0)*r[i] + 1);
}else{
r[i] = u[i];
if(y[i] > 0.0){
r[i] = 1.0 - u[i];
r[i] = log(-log(r[i]));
x[i] = c_0 + r[i]*(c_1 + r[i]*(c_2 + r[i]*(c_3 + r[i]*(c_4 + r[i]*(c_5 + r[i]*(c_6 + r[i]*(c_7 + r[i]*c_8)))))));
}
if(y[i] < 0){
x[i] = -x[i];
}
}
}
return x;
}
double phi(double x){
return 0.5 * erfc(-x * M_SQRT1_2);
}
void Anderson_Darling(int n, double X[]){
sort(X,X + n);
// Find the mean of X
double X_avg = 0.0;
double sum = 0.0;
for(int i = 0; i < n; i++){
sum += X[i];
}
X_avg = ((double)sum)/n;
// Find the variance of X
double X_sig = 0.0;
for(int i = 0; i < n; i++){
X_sig += (X[i] - X_avg)*(X[i] - X_avg);
}
X_sig /= (n-1);
// The values X_i are standardized to create new values Y_i
double Y[n];
for(int i = 0; i < n; i++){
Y[i] = (X[i] - X_avg)/(sqrt(X_sig));
//cout << Y[i] << endl;
}
// With a standard normal CDF, we calculate the Anderson_Darling Statistic
double A = -n;
for(int i = 0; i < n; i++){
A += -1.0/(double)n *(2*(i+1) - 1)*(log(phi(Y[i])) + log(1 - phi(Y[n - i])));
}
cout << A << endl;
}

Answer 1

Let me guess, your n was 2000. Right?
The major issue here is when you do 1/n in the last expression. 1 is an int and ao is n. When you divide 1 by n it performs integer division. Now 1 divided by any number > 1 is 0 under integer division (think if it as only keeping only integer part of the quotient. What you need to do is cast n as double by writing 1/(double)n.
Rest all should work fine.
Summary from discussions -
Indexes to Y[] should be i and n-1-i respectively.
n should not be added in the loop but only once.
Minor fixes like changing divisor to n instead of n-1 while calculating Variance.

Answer 2

You have integer division here:
A += -n - 1/n *(2*(i) - 1)*(log(phi(Y[i])) + log(1 - phi(Y[n+1 - i])));
^^^
1/n is zero when n > 1 - you need to change this to, e.g.: 1.0/n:
A += -n - 1.0/n *(2*(i) - 1)*(log(phi(Y[i])) + log(1 - phi(Y[n+1 - i])));
^^^^^