feat(family-12): add 13 Statistik/Regression indicators (#51)

* feat(family-12): add 13 Statistik/Regression indicators

Brings the Price Statistics family to 20 indicators (7 → 20) and the
total catalogue to 84 (71 → 84). Every indicator ships in the Rust
core plus Python, Node, and WASM bindings with full streaming ↔ batch
parity, fuzz coverage, and benches.

Scalar (f64 → f64):
- Variance, CoefficientOfVariation: rolling population variance and
  its dimensionless ratio with the mean. O(1) updates.
- Skewness, Kurtosis: rolling Pearson skewness and excess kurtosis,
  derived from running sums of x, x², x³, x⁴ via the binomial
  identities — also O(1) per bar.
- StandardError, DetrendedStdDev: standard error of estimate (n − 2)
  and population StdDev (n) of OLS residuals, sharing the LinReg
  O(1) sliding sums.
- RSquared: coefficient of determination of the rolling OLS fit; the
  trend-quality filter, clamped to [0, 1].
- MedianAbsoluteDeviation: robust dispersion estimator; O(period log
  period) per emission via two in-place sorts of a reusable scratch
  buffer.
- Autocorrelation(period, lag): rolling lag-k Pearson autocorrelation.
- HurstExponent(period, chunks): R/S-analysis trend-persistence
  estimator clamped to [0, 1].

Pair indicators (Input = (f64, f64)):
- PearsonCorrelation: rolling cross-series Pearson, O(1).
- Beta: rolling OLS slope of asset vs. benchmark (CAPM).
- SpearmanCorrelation: rolling rank correlation with mid-rank tie
  handling; O(period log period).

Touchpoints:
- crates/wickra-core: 13 new indicator modules + mod.rs / lib.rs
  re-exports.
- bindings/python: pyclasses + add_class registration + __init__.py
  import & __all__ updates. The pair indicators expose
  update(x, y) and batch(x, y) over two equally-sized numpy arrays.
- bindings/node: scalar indicators via node_scalar_indicator! macro;
  pair indicators via new node_pair_indicator! macro; explicit
  structs for Autocorrelation and HurstExponent (two-arg ctors).
  index.js extended with the new exports.
- bindings/wasm: scalar wrappers via wasm_scalar_indicator!; pair
  wrappers via new wasm_pair_indicator! macro.
- fuzz: every scalar drove through the generic helper; pair
  indicators stress-tested by pairing adjacent samples of the fuzz
  input.
- Python tests (test_new_indicators.py): added to SCALAR
  parametrisation, plus algebraic reference values
  (variance of [2,4,6] = 8/3, MAD ignoring outlier = 0, monotone
  non-linear Spearman = 1, two-to-one Beta = 2, etc.) and a
  streaming-vs-batch test for the pair indicators.
- Node tests (indicators.test.js): extended the scalar factories
  map and added a pair-indicator section with the same algebraic
  reference values.
- crates/wickra/benches: bench_scalar entries for all 10 single-
  input new indicators.
- README: counter 71 → 84; Price Statistics family-table row
  expanded with the 13 new indicators.
- CHANGELOG: Unreleased section documents the family addition.

Wiki drafts (ghost-ignored, manual sync to wickra.wiki at release
time): indicator-ideas/families/wiki/family-12-statistik-regression/
contains 13 deep-dive pages plus _Sidebar / Indicators-Overview /
Warmup-Periods / Home fragments for the curator merge.

cargo check --workspace --all-features: clean.

* fix(family-12): remove unreachable defensive guards in hurst_exponent

The three guards (m < 2 continue, end > buf.len() break, denom == 0.0
return) are by-construction unreachable given the constructor invariant
period >= 2 * chunks: m = period / k for k in 1..=chunks always
satisfies m >= 2 and end = (c+1) * m <= k * m <= period = buf.len(),
and m_1 = period and m_2 = period / 2 are always distinct so the slope
denominator is strictly positive. Removing them brings codecov/patch
back to 100%.

CHANGELOG.md

@@ -8,6 +8,37 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 ## [Unreleased]
 
 ### Added
+- **Family 12 — Statistik / Regression (13 indicators).** A complete
+  statistical toolkit for analysing rolling price distributions and
+  cross-series relationships. Every indicator ships in the Rust core
+  plus all three bindings (Python, Node, WASM), with full streaming +
+  batch parity, fuzz coverage, and benches against the BTCUSDT
+  dataset:
+  - **Variance** — rolling population variance (`StdDev` squared).
+  - **CoefficientOfVariation** — `StdDev / Mean`, dimensionless dispersion.
+  - **Skewness** — rolling third standardised moment (Pearson skewness).
+  - **Kurtosis** — rolling excess kurtosis (fourth moment minus `3`).
+  - **StandardError** — standard error of estimate for the rolling OLS
+    fit, with `n − 2` residual degrees of freedom.
+  - **DetrendedStdDev** — population standard deviation of OLS
+    residuals (the StdDev that remains after subtracting the linear
+    trend).
+  - **RSquared** — coefficient of determination of the rolling OLS
+    fit; the trend-quality filter.
+  - **MedianAbsoluteDeviation** — robust dispersion measure that
+    survives outliers (median of absolute deviations from the median).
+  - **Autocorrelation** — rolling lag-`k` Pearson autocorrelation;
+    detects periodicity and tests for white-noise behaviour.
+  - **HurstExponent** — R/S-analysis estimator of trend-persistence
+    vs. mean-reversion regime (`0.5` is random walk).
+  - **PearsonCorrelation** — rolling correlation between two
+    synchronised series; takes `(x, y)` pairs.
+  - **Beta** — rolling OLS slope of an asset on a benchmark; the CAPM
+    sensitivity coefficient.
+  - **SpearmanCorrelation** — rolling rank correlation (monotone,
+    outlier-robust analogue of Pearson).
+
+  Indicator count: 71 → 84.
 - **Family 13 — Ichimoku & alternative charts.** Two new indicators:
   - `Ichimoku` (Ichimoku Kinko Hyo) — the full five-line cloud system
     (Tenkan-sen, Kijun-sen, Senkou Span A/B, Chikou Span) with the