refactor(indicators): Integrated R-Squared and Slope calculation

Include/MyIncludes/LinearRegression_Calculator.mqh

@@ -1,9 +1,9 @@
 //+------------------------------------------------------------------+
 //|                                 LinearRegression_Calculator.mqh  |
-//|      VERSION 3.10: Supports both Moving and Static Channels.     |
+//|      VERSION 4.00: Integrated R-Squared and Slope calculation.   |
-//|                                        Copyright 2025, xxxxxxxx  |
+//|                                        Copyright 2026, xxxxxxxx  |
 //+------------------------------------------------------------------+
-#property copyright "Copyright 2025, xxxxxxxx"
+#property copyright "Copyright 2026, xxxxxxxx"
 
 #include <MyIncludes\HeikinAshi_Tools.mqh>
 
@@ -23,6 +23,10 @@ protected:
    ENUM_CHANNEL_MODE m_channel_mode;
    double            m_deviations;
 
+   // Precalc for optimization
+   double            m_sum_x, m_sum_x2;
+   double            m_denom_x;
+
    //--- Persistent Buffer
    double            m_price[];
 
@@ -32,7 +36,10 @@ public:
                      CLinearRegressionCalculator(void) {};
    virtual          ~CLinearRegressionCalculator(void) {};
 
+   // Init 1: Full (For Channels)
    bool              Init(int period, ENUM_CHANNEL_MODE mode, double deviations);
+   // Init 2: Simple (For R2/Slope only)
+   bool              Init(int period);
 
    //--- Method 1: Moving Regression (The "Wavy" line)
    void              CalculateMoving(int rates_total, int prev_calculated, const double &open[], const double &high[], const double &low[], const double &close[], ENUM_APPLIED_PRICE price_type,
@@ -41,19 +48,42 @@ public:
    //--- Method 2: Static Channel (The "Straight" segment for current bars)
    void              CalculateStaticChannel(int rates_total, const double &open[], const double &high[], const double &low[], const double &close[], ENUM_APPLIED_PRICE price_type,
          double &middle_buffer[], double &upper_buffer[], double &lower_buffer[]);
+
+   //--- Method 3: Rolling Statistics (R-Squared & Slope) - NEW
+   void              CalculateState(int rates_total, int prev_calculated, const double &open[], const double &high[], const double &low[], const double &close[], ENUM_APPLIED_PRICE price_type,
+                                    double &out_slope[], double &out_r2[], double &out_forecast[]);
   };
 
 //+------------------------------------------------------------------+
-//| Init                                                             |
+//| Init (Full)                                                      |
 //+------------------------------------------------------------------+
 bool CLinearRegressionCalculator::Init(int period, ENUM_CHANNEL_MODE mode, double deviations)
   {
    m_period       = (period < 2) ? 2 : period;
    m_channel_mode = mode;
    m_deviations   = (deviations <= 0) ? 2.0 : deviations;
+
+// Pre-calc X sums (0..N-1)
+   m_sum_x = 0;
+   m_sum_x2 = 0;
+   for(int k = 0; k < m_period; k++)
+     {
+      m_sum_x += k;
+      m_sum_x2 += k * k;
+     }
+   m_denom_x = m_period * m_sum_x2 - m_sum_x * m_sum_x;
+
    return true;
   }
 
+//+------------------------------------------------------------------+
+//| Init (Simple)                                                    |
+//+------------------------------------------------------------------+
+bool CLinearRegressionCalculator::Init(int period)
+  {
+   return Init(period, DEVIATION_STANDARD, 2.0); // Delegate with defaults
+  }
+
 //+------------------------------------------------------------------+
 //| Method 1: Moving Regression (Wavy)                               |
 //+------------------------------------------------------------------+
@@ -206,6 +236,66 @@ void CLinearRegressionCalculator::CalculateStaticChannel(int rates_total, const
      }
   }
 
+//+------------------------------------------------------------------+
+//| Method 3: Rolling Statistics (NEW)                               |
+//+------------------------------------------------------------------+
+void CLinearRegressionCalculator::CalculateState(int rates_total, int prev_calculated, const double &open[], const double &high[], const double &low[], const double &close[], ENUM_APPLIED_PRICE price_type,
+      double &out_slope[], double &out_r2[], double &out_forecast[])
+  {
+   if(rates_total < m_period)
+      return;
+
+   int start_index = (prev_calculated == 0) ? 0 : prev_calculated - 1;
+
+   if(ArraySize(m_price) != rates_total)
+      ArrayResize(m_price, rates_total);
+   if(!PreparePriceSeries(rates_total, start_index, price_type, open, high, low, close))
+      return;
+
+   int loop_start = MathMax(m_period - 1, start_index);
+
+   for(int i = loop_start; i < rates_total; i++)
+     {
+      double sum_y = 0, sum_xy = 0, sum_y2 = 0;
+
+      for(int k = 0; k < m_period; k++)
+        {
+         double price = m_price[i - m_period + 1 + k];
+         double x = k; // Map x to 0..N-1
+
+         sum_y += price;
+         sum_xy += x * price;
+         sum_y2 += price * price;
+        }
+
+      double b = 0;
+      if(m_denom_x != 0)
+         b = (m_period * sum_xy - m_sum_x * sum_y) / m_denom_x; // Slope
+
+      double a = (sum_y - b * m_sum_x) / m_period; // Intercept
+      double forecast = a + b * (m_period - 1);    // Current Value
+
+      // R-Squared Calc
+      // SST = Total Sum of Squares = Sum(y^2) - (Sum(y)^2)/N
+      // SSR = Regression Sum of Squares = b * (Sum(xy) - Sum(x)Sum(y)/N)
+      // R2 = SSR / SST
+
+      // Alternative standard formula: R2 = (N*SumXY - SumX*SumY)^2 / (DenomX * DenomY)
+      double denom_y = (m_period * sum_y2) - (sum_y * sum_y);
+      double r2 = 0;
+
+      if(m_denom_x > 0 && denom_y > 0)
+        {
+         double num = (m_period * sum_xy - m_sum_x * sum_y);
+         r2 = (num * num) / (m_denom_x * denom_y);
+        }
+
+      out_slope[i]    = b;
+      out_r2[i]       = r2;
+      out_forecast[i] = forecast; // Same as 'middle_buffer' in Moving mode
+     }
+  }
+
 //+------------------------------------------------------------------+
 //| Prepare Price (Standard)                                         |
 //+------------------------------------------------------------------+