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fix(docs): correct .md documentation across errors, dynamics, filters, forecasts, momentum, numerics, oscillators, reversals, statistics, trends, volatility, volume

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Deep review of all indicator categories verified .md headers against .cs WarmupPeriod, parameters, inputs, and outputs. Fixes include warmup corrections, parameter documentation, output type accuracy, and Pine Script alignment.
This commit is contained in:
Miha Kralj
2026-03-10 18:38:23 -07:00
parent 8906c62dcf
commit 35a6702b06
178 changed files with 2579 additions and 998 deletions
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lib/trends_FIR/pwma/pwma.pine
+7 -19
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@@ -1,38 +1,26 @@
// Licensed under the Apache License, Version 2.0
// © mihakralj
//@version=6
indicator("Pascal Weighted Moving Average (PWMA)", "PWMA", overlay=true)
indicator("Parabolic Weighted Moving Average (PWMA)", "PWMA", overlay=true)
//@function Calculates PWMA using Pascal's triangle coefficients as weights with compensator
//@function Calculates PWMA using i² (parabolic) weights with compensator
//@param source Series to calculate PWMA from
//@param period Lookback period - FIR window size
//@returns PWMA value, calculates from first bar using available data
//@optimized Uses Pascal's triangle weighting with O(n) complexity per bar due to lookback loop
//@optimized Uses parabolic weighting w[i]=i² with O(n) complexity per bar due to lookback loop
pwma(series float source, simple int period) =>
if period <= 0
runtime.error("Period must be greater than 0")
int p = math.min(bar_index + 1, period)
var array<float> weights = array.new_float(1, 1.0)
var int last_p = 1
if last_p != p
weights := array.new_float(p, 0.0)
array.set(weights, 0, 1.0)
if p > 1
float prev_weight = 1.0
for i = 1 to p - 1
float curr_weight = prev_weight * (p - i) / i
array.set(weights, i, curr_weight)
prev_weight := curr_weight
last_p := p
float sum = 0.0
float psum = 0.0
float weight_sum = 0.0
for i = 0 to p - 1
float price = source[i]
if not na(price)
float w = array.get(weights, i)
sum += price * w
float w = float((p - i) * (p - i))
psum += price * w
weight_sum += w
nz(sum / weight_sum, source)
nz(psum / weight_sum, source)
// ---------- Main loop ----------