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mql5_indicators_mt5_part3/Nonlinear regression - indicator for MetaTrader 5/nonlinear_regression.mq5
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//------------------------------------------------------------------
#property copyright "© mladen, 2018"
#property link "mladenfx@gmail.com"
#property description "Nonlinear regression"
//+------------------------------------------------------------------
#property indicator_chart_window
#property indicator_buffers 4
#property indicator_plots 1
#property indicator_label1 "Nonlinear regression"
#property indicator_type1 DRAW_COLOR_LINE
#property indicator_color1 clrDarkGray,clrDeepPink,clrLimeGreen
#property indicator_width1 2
//--- input parameters
input int inpPeriod = 50; // Period
input ENUM_APPLIED_PRICE inpPrice = PRICE_CLOSE; // Price
//--- indicator buffers
double val[],valc[];
//+------------------------------------------------------------------+
//| Custom indicator initialization function |
//+------------------------------------------------------------------+
int OnInit()
{
//--- indicator buffers mapping
SetIndexBuffer(0,val,INDICATOR_DATA);
SetIndexBuffer(1,valc,INDICATOR_COLOR_INDEX);
//--- indicator short name assignment
IndicatorSetString(INDICATOR_SHORTNAME,"Nonlinear regression ("+(string)inpPeriod+")");
//---
return (INIT_SUCCEEDED);
}
//+------------------------------------------------------------------+
//| Custom indicator de-initialization function |
//+------------------------------------------------------------------+
void OnDeinit(const int reason)
{
}
//+------------------------------------------------------------------+
//| Custom indicator iteration function |
//+------------------------------------------------------------------+
int OnCalculate(const int rates_total,const int prev_calculated,const datetime &time[],
const double &open[],
const double &high[],
const double &low[],
const double &close[],
const long &tick_volume[],
const long &volume[],
const int &spread[])
{
if(Bars(_Symbol,_Period)<rates_total) return(prev_calculated);
for(int i=(int)MathMax(prev_calculated-1,0); i<rates_total && !IsStopped(); i++)
{
val[i]=iNlr(getPrice(inpPrice,open,close,high,low,i,rates_total),inpPeriod,i,0,rates_total);
valc[i]=(i>0) ?(val[i]>val[i-1]) ? 2 :(val[i]<val[i-1]) ? 1 : valc[i-1]: 0;
}
return(rates_total);
}
//+------------------------------------------------------------------+
//| Custom functions |
//+------------------------------------------------------------------+
double workNlr[][1];
double nlrYValue[];
double nlrXValue[];
//
//---
//
double iNlr(double price,int Length,int shift,int desiredBar,int bars,int instanceNo=0)
{
if(ArrayRange(workNlr,0)!=bars) ArrayResize(workNlr,bars);
if(ArraySize(nlrYValue)!=Length) ArrayResize(nlrYValue,Length);
if(ArraySize(nlrXValue)!=Length) ArrayResize(nlrXValue,Length);
//
//---
//
double AvgX = 0;
double AvgY = 0;
int r=shift;
workNlr[r][instanceNo]=price;
ArrayInitialize(nlrXValue,0);
ArrayInitialize(nlrYValue,0);
for(int i=0;i<Length && (r-i)>=0;i++)
{
nlrXValue[i] = i;
nlrYValue[i] = workNlr[r-i][instanceNo];
AvgX += nlrXValue[i];
AvgY += nlrYValue[i];
}
AvgX /= Length;
AvgY /= Length;
//
//---
//
double SXX = 0;
double SXY = 0;
double SYY = 0;
double SXX2 = 0;
double SX2X2 = 0;
double SYX2 = 0;
for(int i=0;i<Length;i++)
{
double XM = nlrXValue[i] - AvgX;
double YM = nlrYValue[i] - AvgY;
double XM2 = nlrXValue[i] * nlrXValue[i] - AvgX*AvgX;
SXX += XM*XM;
SXY += XM*YM;
SYY += YM*YM;
SXX2 += XM*XM2;
SX2X2 += XM2*XM2;
SYX2 += YM*XM2;
}
//
//---
//
double tmp;
double ACoeff=0;
double BCoeff=0;
double CCoeff=0;
tmp=SXX*SX2X2-SXX2*SXX2;
if(tmp!=0)
{
BCoeff = ( SXY*SX2X2 - SYX2*SXX2 ) / tmp;
CCoeff = ( SXX*SYX2 - SXX2*SXY ) / tmp;
}
ACoeff = AvgY - BCoeff*AvgX - CCoeff*AvgX*AvgX;
tmp = ACoeff + BCoeff*desiredBar + CCoeff*desiredBar*desiredBar;
return(tmp);
}
//
//---
//
double getPrice(ENUM_APPLIED_PRICE tprice,const double &open[],const double &close[],const double &high[],const double &low[],int i,int _bars)
{
if(i>=0)
switch(tprice)
{
case PRICE_CLOSE: return(close[i]);
case PRICE_OPEN: return(open[i]);
case PRICE_HIGH: return(high[i]);
case PRICE_LOW: return(low[i]);
case PRICE_MEDIAN: return((high[i]+low[i])/2.0);
case PRICE_TYPICAL: return((high[i]+low[i]+close[i])/3.0);
case PRICE_WEIGHTED: return((high[i]+low[i]+close[i]+close[i])/4.0);
}
return(0);
}
//+------------------------------------------------------------------+