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/* Any copyright is dedicated to the Public Domain.
http://creativecommons.org/publicdomain/zero/1.0/ */
/* Adapted from "Accurately computing running variance - John D. Cook"
http://www.johndcook.com/standard_deviation.html */
#ifndef RUNNING_STAT_H_
#define RUNNING_STAT_H_
#include <math.h>
namespace mozilla {
class RunningStat
{
public:
RunningStat() : mN(0) {}
void Clear()
{
mN = 0;
}
void Push(double x)
{
mN++;
// See Knuth TAOCP vol 2, 3rd edition, page 232
if (mN == 1)
{
mOldM = mNewM = x;
mOldS = 0.0;
} else {
mNewM = mOldM + (x - mOldM) / mN;
mNewS = mOldS + (x - mOldM) * (x - mNewM);
// set up for next iteration
mOldM = mNewM;
mOldS = mNewS;
}
}
int NumDataValues() const
{
return mN;
}
double Mean() const
{
return (mN > 0) ? mNewM : 0.0;
}
double Variance() const
{
return (mN > 1) ? mNewS / (mN - 1) : 0.0;
}
double StandardDeviation() const
{
return sqrt(Variance());
}
private:
int mN;
double mOldM, mNewM, mOldS, mNewS;
};
}
#endif //RUNNING_STAT_H_
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