blob: 7a83154cba738a15d8c17fd3f4bda0625f122e77 (
plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
|
#pragma once
#include <cmath>
#include <cinttypes>
// no copyright information other than the attribution below.
// code shared as an example/tutorial of running variance
// written by John D. Cook on the website <http://www.johndcook.com/blog/standard_deviation>
// following references in the site's article:
// Chan, Tony F.; Golub, Gene H.; LeVeque, Randall J. (1983).
// Algorithms for Computing the Sample Variance: Analysis and Recommendations.
// The American Statistician 37, 242-247.
// Ling, Robert F. (1974).
// Comparison of Several Algorithms for Computing Sample Means and Variances.
// Journal of the American Statistical Association, Vol. 69, No. 348, 859-866.
class variance
{
double m_old, m_new, s_old, s_new;
std::uintptr_t cnt;
public:
using size_type = std::uintptr_t;
variance() : cnt(0) {}
void clear() { *this = variance(); }
size_type count() { return cnt; }
void input(double x)
{
cnt++;
if (cnt == 1)
{
m_old = m_new = x;
s_old = 0;
}
else
{
m_new = m_old + (x - m_old)/cnt;
s_new = s_old + (x - m_old)*(x - m_new);
m_old = m_new;
s_old = s_new;
}
}
double avg() const { return cnt > 0 ? m_new : 0; }
double Var() const { return cnt > 1 ? s_new/(cnt - 1) : 0; }
double stddev() const { return std::sqrt(Var()); }
};
|
