mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-08-03 03:47:42 +00:00
Miha Kralj
73e3420379
semver fix VAR test fix new: COVAR, ZSCORE, CORR, LINREG versioning refactoring
53 lines
2.1 KiB
C#
53 lines
2.1 KiB
C#
namespace QuanTAlib;
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using System;
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using System.Collections.Generic;
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using System.Linq;
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/* <summary>
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CORR: Pearson's Correlation Coefficient
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PCC is a measure of linear correlation between two sets of data.
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It is the ratio between the covariance of two variables and the product of
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their standard deviations; it is essentially a normalized measurement of
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the covariance, such that the result always has a value between −1 and 1.
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Sources:
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https://en.wikipedia.org/wiki/Pearson_correlation_coefficient
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</summary> */
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public class CORR_Series : Pair_TSeries_Indicator
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{
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public CORR_Series(TSeries d1, TSeries d2, int period, bool useNaN = false) : base(d1, d2, period, useNaN)
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{
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if (base._d1.Count > 0 && base._d2.Count > 0) { for (int i = 0; i < base._d1.Count; i++) { this.Add(base._d1[i], base._d2[i], false); } }
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}
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private readonly System.Collections.Generic.List<double> _x = new();
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private readonly System.Collections.Generic.List<double> _xx = new();
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private readonly System.Collections.Generic.List<double> _y = new();
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private readonly System.Collections.Generic.List<double> _yy = new();
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private readonly System.Collections.Generic.List<double> _xy = new();
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public override void Add((System.DateTime t, double v) TValue1, (System.DateTime t, double v) TValue2, bool update)
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{
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Add_Replace_Trim(_x, TValue1.v, _p, update);
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Add_Replace_Trim(_xx, TValue1.v * TValue1.v, _p, update);
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Add_Replace_Trim(_y, TValue2.v, _p, update);
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Add_Replace_Trim(_yy, TValue2.v * TValue2.v, _p, update);
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Add_Replace_Trim(_xy, TValue1.v * TValue2.v, _p, update);
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double _sumx = _x.Sum();
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double _sumxx = _xx.Sum();
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double _sumy = _y.Sum();
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double _sumyy = _yy.Sum();
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double _sumxy = _xy.Sum();
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double _covar = (_sumxx - _sumx * _sumx / _p) * (_sumyy - _sumy * _sumy / _p);
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double _cor = (_covar != 0) ? (_sumxy - _sumx * _sumy / _p) / Math.Sqrt(_covar) : 0.0;
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var result = (TValue1.t, (this.Count < this._p - 1 && this._NaN) ? double.NaN : _cor);
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if (update) { base[base.Count - 1] = result; } else { base.Add(result); }
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}
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}
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