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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.
66 lines
2.3 KiB
Plaintext
66 lines
2.3 KiB
Plaintext
// The MIT License (MIT)
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// © mihakralj
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//@version=6
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indicator("Interquartile Range (IQR)", "IQR", overlay=false, precision=4)
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//@function Function to calculate percentile using linear interpolation
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//@param src Source series for calculation
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//@param len Lookback period for data collection
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//@param p Percentile value (0-100)
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//@returns Calculated percentile value
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// Adapted from percentile.pine
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iqr(series float src, simple int len, simple float p) =>
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if len <= 0 // Should not happen due to input minval=2
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runtime.error("Lookback Period must be greater than 0.")
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float(na)
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if p < 0 or p > 100
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runtime.error("Percentile 'p' must be between 0 and 100.")
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float(na)
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data_points = array.new_float()
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for i = 0 to len - 1
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val = src[i]
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if not na(val)
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array.push(data_points, val)
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n_valid = array.size(data_points)
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float result = na
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if n_valid == 0
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result := na
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else if n_valid == 1
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result := array.get(data_points, 0)
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else
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array.sort(data_points)
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rank = (p / 100.0) * (n_valid - 1)
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if p == 0.0
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result := array.get(data_points, 0)
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else if p == 100.0
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result := array.get(data_points, n_valid - 1)
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else
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k_floor_idx = math.floor(rank)
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k_ceil_idx = math.ceil(rank)
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int_k_floor = math.max(0, math.min(n_valid - 1, int(k_floor_idx)))
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int_k_ceil = math.max(0, math.min(n_valid - 1, int(k_ceil_idx)))
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if int_k_floor == int_k_ceil
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result := array.get(data_points, int_k_floor)
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else
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val_floor = array.get(data_points, int_k_floor)
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val_ceil = array.get(data_points, int_k_ceil)
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if val_floor == val_ceil
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result := val_floor
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else
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result := val_floor + (rank - k_floor_idx) * (val_ceil - val_floor)
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result
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// Inputs
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i_source = input.source(close, title="Source")
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i_length = input.int(20, title="Lookback Period", minval=2)
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// Calculate Q1 (25th percentile) and Q3 (75th percentile)
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q1 = iqr(i_source, i_length, 25.0)
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q3 = iqr(i_source, i_length, 75.0)
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// Calculate IQR
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iqr_value = q3 - q1
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// Plot IQR
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plot(iqr_value, title="IQR", color=color.yellow, linewidth=2)
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