mirror of
https://github.com/aicodix/dsp.git
synced 2026-04-27 14:30:36 +00:00
added the repeated median estimator of Siegel
This commit is contained in:
parent
5c456aae28
commit
e90a3b601b
2 changed files with 69 additions and 0 deletions
|
|
@ -187,6 +187,10 @@ Implemented [Simple linear regression](https://en.wikipedia.org/wiki/Simple_line
|
|||
|
||||
The [Theil-Sen estimator](https://en.wikipedia.org/wiki/Theil%E2%80%93Sen_estimator) is a [robust](https://en.wikipedia.org/wiki/Robust_statistics) [line fitting](https://en.wikipedia.org/wiki/Line_fitting) algorithm.
|
||||
|
||||
### [repeated_median.hh](repeated_median.hh)
|
||||
|
||||
The [repeated median estimator](https://en.wikipedia.org/wiki/Repeated_median_regression) is a [robust](https://en.wikipedia.org/wiki/Robust_statistics) [line fitting](https://en.wikipedia.org/wiki/Line_fitting) algorithm.
|
||||
|
||||
### [complex.hh](complex.hh)
|
||||
|
||||
Faster alternative (no Inf/NaN handling) to the std::complex implementation.
|
||||
|
|
|
|||
65
repeated_median.hh
Normal file
65
repeated_median.hh
Normal file
|
|
@ -0,0 +1,65 @@
|
|||
/*
|
||||
Repeated median estimator of Siegel
|
||||
|
||||
Copyright 2021 Ahmet Inan <inan@aicodix.de>
|
||||
*/
|
||||
|
||||
#pragma once
|
||||
|
||||
#include <algorithm>
|
||||
|
||||
namespace DSP {
|
||||
|
||||
template <typename TYPE, int SIZE>
|
||||
class RepeatedMedianEstimator
|
||||
{
|
||||
TYPE inner_[SIZE-1], outer_[SIZE];
|
||||
TYPE xint_, yint_, slope_;
|
||||
public:
|
||||
RepeatedMedianEstimator() : xint_(0), yint_(0), slope_(0) {}
|
||||
void compute(TYPE *x, TYPE *y, int LEN)
|
||||
{
|
||||
if (LEN > SIZE)
|
||||
LEN = SIZE;
|
||||
for (int i = 0; i < LEN; ++i) {
|
||||
int count = 0;
|
||||
for (int j = 0; j < LEN; ++j)
|
||||
if (x[j] != x[i])
|
||||
inner_[count++] = (y[j] - y[i]) / (x[j] - x[i]);
|
||||
std::nth_element(inner_, inner_+count/2, inner_+count);
|
||||
outer_[i] = inner_[count/2];
|
||||
}
|
||||
std::nth_element(outer_, outer_+LEN/2, outer_+LEN);
|
||||
slope_ = outer_[LEN/2];
|
||||
for (int i = 0; i < LEN; ++i) {
|
||||
int count = 0;
|
||||
for (int j = 0; j < LEN; ++j)
|
||||
if (x[j] != x[i])
|
||||
inner_[count++] = (x[j]*y[i] - x[i]*y[j]) / (x[j] - x[i]);
|
||||
std::nth_element(inner_, inner_+count/2, inner_+count);
|
||||
outer_[i] = inner_[count/2];
|
||||
}
|
||||
std::nth_element(outer_, outer_+LEN/2, outer_+LEN);
|
||||
yint_ = outer_[LEN/2];
|
||||
xint_ = - yint_ / slope_;
|
||||
}
|
||||
TYPE xint()
|
||||
{
|
||||
return xint_;
|
||||
}
|
||||
TYPE slope()
|
||||
{
|
||||
return slope_;
|
||||
}
|
||||
TYPE yint()
|
||||
{
|
||||
return yint_;
|
||||
}
|
||||
TYPE operator () (TYPE x)
|
||||
{
|
||||
return yint_ + slope_ * x;
|
||||
}
|
||||
};
|
||||
|
||||
}
|
||||
|
||||
Loading…
Add table
Add a link
Reference in a new issue