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StatisticalPine Script v6

ta.percentile_linear_interpolation()Percentile (Linear Interpolation)

Calculates the percentile using linear interpolation between the two nearest ranks.

TradingView language reference

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Syntax

Syntax
ta.percentile_linear_interpolation(source, length, percentage) → series float

Arguments

ParameterTypeDescription
sourceseries int/floatSeries of values to process.
lengthseries intNumber of bars in the rolling window.
percentagesimple int/floatTarget percentile in the 0-100 range.

Returns

P-th percentile of source for length bars back using linear interpolation.

Remarks

na values in the source window are included and produce an na result. An interpolated percentile need not equal an input observation or a valid tradeable tick.

Code Examples

Pine Script v6 Example
//@version=6
indicator("percentile_linear_interpolation")
p50 = ta.percentile_linear_interpolation(close, 100, 50)
plot(p50, title="Median-like (50th pct)")

Trading Applications

Calculate precise percentile levels for price analysis

Build adaptive bands based on percentile levels

Create dynamic support/resistance from statistical distributions

Use for non-parametric volatility measurement

Related Functions

ta.percentile_nearest_rankta.percentrank

Frequently Asked Questions

It returns the value at the requested percentile over the rolling window, estimating between sorted neighbors with linear interpolation rather than selecting only an observed rank. This does not guarantee a smooth time series.

Linear interpolation blends between the two closest order statistics; nearest rank picks an actual observed value from the window. Interpolated percentiles can lie between ticks.

Common uses include channel midlines (50th), historical sample tails (5th/95th), and adaptive bands where band width reflects the empirical distribution of recent prices. These historical price percentiles are not calibrated probabilities of future loss.

Generate ta.percentile_linear_interpolation() Code with AI

Draft Pine Script using ta.percentile_linear_interpolation() with Pineify's AI Coding Agent, then review the arguments and test the result on your chart. Usage depends on your plan and available credits.

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