feat(dynamics): add PlusDI, MinusDI, PlusDM, MinusDM indicators

Complete thin Dx-composition wrapper indicators with full test coverage:

- PlusDi/MinusDi: Directional Indicator wrappers (DiPlus/DiMinus from Dx)
- PlusDm/MinusDm: Directional Movement wrappers (DmPlus/DmMinus from Dx)
- Individual validation tests per indicator directory (TALib, Skender, bounds)
- Combined unit tests (DiDm.Tests.cs) and validation tests (DiDm.Validation.Tests.cs)
- Quantower wrappers + tests for all 4 indicators
- PineScript v6 implementations with compensated RMA
- Normalized .md documentation for all indicators and categories
- 182 tests passing, 0 failures

lib/filters/kalman/Kalman.md

@@ -1,5 +1,7 @@
 # Kalman Filter (KALMAN)
 
+> *Prediction is very difficult, especially if it's about the future.*
+
 | Property         | Value                            |
 | ---------------- | -------------------------------- |
 | **Category**     | Filter                        |
@@ -18,8 +20,6 @@
 - Requires `10` bars of warmup before first valid output (IsHot = true).
 - Validated against TA-Lib, Skender, and Tulip reference implementations where available.
 
-> "Prediction is very difficult, especially if it's about the future." — Niels Bohr. The Kalman Filter doesn't just predict; it optimally estimates the present by balancing what it thinks should happen with what actually happened.
-
 The **Kalman Filter** is a recursive algorithm that estimates the state of a dynamic system from a series of incomplete and noisy measurements. In technical analysis, it acts as a sophisticated smoothing filter that adapts to price changes based on specified noise covariances. Unlike simple moving averages that treat all past data equally or with fixed weights, the Kalman Filter dynamically adjusts its "trust" between its own prediction and the new price data.
 
 ## Historical Context