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