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// The contents of this file are in the public domain. See LICENSE_FOR_EXAMPLE_PROGRAMS.txt
/*
This is an example illustrating the use of the running_stats object from the dlib C++
Library. It is a simple tool for computing basic statistics on a stream of numbers.
In this example, we sample 100 points from the sinc function and then then compute the
unbiased sample mean, variance, skewness, and excess kurtosis.
*/
#include <iostream>
#include <vector>
#include <dlib/statistics.h>
using namespace std;
using namespace dlib;
// Here we define the sinc function so that we may generate sample data. We compute the mean,
// variance, skewness, and excess kurtosis of this sample data.
double sinc(double x)
{
if (x == 0)
return 1;
return sin(x)/x;
}
int main()
{
running_stats<double> rs;
double tp1 = 0;
double tp2 = 0;
// We first generate the data and add it sequentially to our running_stats object. We
// then print every fifth data point.
for (int x = 1; x <= 100; x++)
{
tp1 = x/100.0;
tp2 = sinc(pi*x/100.0);
rs.add(tp2);
if(x % 5 == 0)
{
cout << " x = " << tp1 << " sinc(x) = " << tp2 << endl;
}
}
// Finally, we compute and print the mean, variance, skewness, and excess kurtosis of
// our data.
cout << endl;
cout << "Mean: " << rs.mean() << endl;
cout << "Variance: " << rs.variance() << endl;
cout << "Skewness: " << rs.skewness() << endl;
cout << "Excess Kurtosis " << rs.ex_kurtosis() << endl;
return 0;
}
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