Long Memory · Network-Adaptive Efficiency (NAMH)

namh_hurst

NAMH Hurst Panel (published namh). Rolling-window DFA-ℓ Hurst panel (Peng et al. 1994) via the PUBLISHED namh package (Bhandari & Sahu 2026) — the paper's own estimate_hurst_panel, not a reimplementation. Supplies the NAMH node-weight φ(H)=1−2|H−0.5| (local efficiency). Defaults reproduce the canonical paper-v3 panel on g20_24 (window=252, step=252 non-overlapping, DFA-1): bit-exact to 01_hurst_panel.csv (max|Δ|≈5e-9). Per-series summary by default; runs all 24 series if none given.

Identity

version 1.0.0 · capability long-memory · min_obs 252 · runner r (namh_hurst.R)

Primitives

P1

Composes with

not yet a catalog field — operator-composition metadata lands with Pathway F; nothing is invented here.

Parameters

nametypereqvalues / range
seriesseries (n=1–24)optional
windowintoptional
stepintoptional
orderintoptional
s_minintoptional
n_scalesintoptional

Returns

method,dataset,config,n_series,n_windows,per_series,source

Paper

none — honest: a substrate method; no single companion paper claims it.

Changelog

[object Object]

Run it

curl -s -X POST https://shssm-compute-b7ui3oxaqq-el.a.run.app/api/compute/run \
  -H "Content-Type: application/json" \
  -d '{"method":"namh_hurst","params":{"series":["India","USA"]}}'
▶ open in the Workbench with namh_hurst preselected
Generated from GET /api/compute/catalog by scripts/gen-man.mjs — the catalog is the truth; no hand-written method docs. · Econstellar · SHSSM, IIT Bhubaneswar.