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https://github.com/mihakralj/QuanTAlib.git
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Miha Kralj
24e86d762a
- Updated BBWN, BBWP, CCV, CV, CVI, EWMA, GKV, HLV, HV, Jvolty, JVOLTYN, MASSI, NATR, RSV, RV, RVI, TR, UI, VOV, VR, YZV indicators with documentation links. - Added documentation links for Aberration, Acceleration Bands, Andrews' Pitchfork, Adaptive Price Zone, ATR Bands, Bollinger Bands, Center of Gravity, Donchian Channels, Decay Min-Max Channel, Detrended Synthetic Price, EACP, EBSW, HOMOD, Jurik Volatility Bands, Keltner Channel, MA Envelope, Min-Max Channel, Price Channel, Regression Channels, Standard Deviation Channel, Stoller Average Range Channel, Super Trend Bands, Ultimate Bands, Ultimate Channel, VWAP Bands, and VWAP with Standard Deviation Bands.
75 lines
3.4 KiB
Plaintext
75 lines
3.4 KiB
Plaintext
// The MIT License (MIT)
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// © mihakralj
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//@version=6
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indicator("R² Coefficient of Determination (RSQUARED)", "RSQUARED")
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//@function Calculates the R-squared (Coefficient of Determination) between two sources
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//@param source1 First series to compare (actual)
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//@param source2 Second series to compare (predicted)
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//@param period Lookback period for averaging
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//@returns R-squared value averaging over the specified period
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rsquared(series float source1, series float source2, simple int period) =>
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if period <= 0
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runtime.error("Period must be greater than 0")
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int p = math.min(math.max(1, period), 4000)
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var float sum_source1 = 0.0
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var float[] buffer_source1 = array.new_float(p, na)
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var int head_source1 = 0
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var int valid_count_source1 = 0
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float oldest_source1 = array.get(buffer_source1, head_source1)
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if not na(oldest_source1)
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sum_source1 := sum_source1 - oldest_source1
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valid_count_source1 := valid_count_source1 - 1
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if not na(source1)
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sum_source1 := sum_source1 + source1
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valid_count_source1 := valid_count_source1 + 1
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array.set(buffer_source1, head_source1, source1)
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head_source1 := (head_source1 + 1) % p
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float mean_source1 = valid_count_source1 > 0 ? sum_source1 / valid_count_source1 : source1
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float squared_residual = math.pow(source1 - source2, 2)
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float total_ss = math.pow(source1 - mean_source1, 2)
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var float sum_squared_residual = 0.0
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var float[] buffer_squared_residual = array.new_float(p, na)
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var int head_squared_residual = 0
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var int valid_count_squared_residual = 0
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float oldest_squared_residual = array.get(buffer_squared_residual, head_squared_residual)
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if not na(oldest_squared_residual)
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sum_squared_residual := sum_squared_residual - oldest_squared_residual
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valid_count_squared_residual := valid_count_squared_residual - 1
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if not na(squared_residual)
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sum_squared_residual := sum_squared_residual + squared_residual
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valid_count_squared_residual := valid_count_squared_residual + 1
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array.set(buffer_squared_residual, head_squared_residual, squared_residual)
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head_squared_residual := (head_squared_residual + 1) % p
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var float sum_total_ss = 0.0
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var float[] buffer_total_ss = array.new_float(p, na)
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var int head_total_ss = 0
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var int valid_count_total_ss = 0
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float oldest_total_ss = array.get(buffer_total_ss, head_total_ss)
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if not na(oldest_total_ss)
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sum_total_ss := sum_total_ss - oldest_total_ss
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valid_count_total_ss := valid_count_total_ss - 1
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if not na(total_ss)
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sum_total_ss := sum_total_ss + total_ss
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valid_count_total_ss := valid_count_total_ss + 1
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array.set(buffer_total_ss, head_total_ss, total_ss)
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head_total_ss := (head_total_ss + 1) % p
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float rss = valid_count_squared_residual > 0 ? sum_squared_residual : squared_residual
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float tss = valid_count_total_ss > 0 ? sum_total_ss : total_ss
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tss != 0 ? 1 - (rss / tss) : 1.0
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// ---------- Main loop ----------
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// Inputs
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i_source1 = input.source(close, "Source")
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i_period = input.int(100, "Period", minval=1)
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i_source2 = ta.ema(i_source1, i_period)
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// Calculation
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score = rsquared(i_source1, i_source2, i_period)
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// Plot
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plot(score, "R²", color.new(color.red, 60, color=color.yellow, linewidth=2), linewidth = 2, style = plot.style_area)
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plot(i_source2, "EMA", color.new(color.yellow, 0, linewidth=2), linewidth = 1, style = plot.style_line, force_overlay = true)
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