Slope, Linear Regression (SLOPE)

// The MIT License (MIT)
// © mihakralj
//@version=6
indicator("Slope, Linear Regression (SLOPE)", "SLOPE", overlay=false, precision=8)

//@function Calculates slope (linear regression)
//@param src Source series to calculate slope from
//@param len Lookback period for calculation
//@returns Slope value properly calculated
slope(series float src, simple int len) =>
    if len <= 1
        runtime.error("Length must be greater than 1")
    var float sumX = 0.0
    var float sumY = 0.0
    var float sumXY = 0.0
    var float sumX2 = 0.0
    var int   validCount = 0
    var array<float> x_values = array.new_float(len)
    var array<float> y_values = array.new_float(len)
    var int   head = 0
    var int internal_time_counter = 0
    if internal_time_counter >= len
        float oldX = array.get(x_values, head)
        float oldY = array.get(y_values, head)
        if not na(oldY)
            sumX := sumX - oldX
            sumY := sumY - oldY
            sumXY := sumXY - oldX * oldY
            sumX2 := sumX2 - oldX * oldX
            validCount := validCount - 1
    float currentX = internal_time_counter
    float currentY = src
    array.set(x_values, head, currentX)
    array.set(y_values, head, currentY)
    if not na(currentY)
        sumX := sumX + currentX
        sumY := sumY + currentY
        sumXY := sumXY + currentX * currentY
        sumX2 := sumX2 + currentX * currentX
        validCount := validCount + 1
    head := (head + 1) % len
    internal_time_counter := internal_time_counter + 1
    float calculatedSlope = na
    if validCount >= 2
        float n = validCount
        float divisor = n * sumX2 - sumX * sumX
        if divisor != 0.0
            calculatedSlope := (n * sumXY - sumX * sumY) / divisor
    calculatedSlope

// ---------- Main loop ----------

// Inputs
i_period = input.int(14, "Period", minval=2)
i_source = input.source(close, "Source")

// Calculation
s = slope(i_source, i_period)

// Plot
plot(s, "Slope", color=color.yellow, linewidth=2)