Add changelog

Author: mdcattaneo

.gitignore

@@ -23,6 +23,7 @@ AGENTS.md
 !/docs/audit/baselines/README.md
 !/README.md
 !/LICENSE.md
+!/CHANGELOG.md
 
 # Keep only the Python package subtree public under Python/.
 /Python/*

CHANGELOG.md

@@ -0,0 +1,42 @@
+# Changelog
+
+All notable changes to RDPOWER will be recorded here. This changelog starts
+with the May 2026 modernization baseline.
+
+## [R 3.0 / Python 2.0.0] - 2026-05-15
+
+Modernization release prepared across May 15-16, 2026.
+
+### Added
+
+- Added fixed-seed numerical contract coverage and baseline comparison tooling
+  for the R, Python, and Stata implementations.
+- Added repository release hardening, including GitHub Actions CI, issue and
+  pull request templates, Dependabot and security configuration, Git attributes
+  and ignore rules, and PyPI trusted publishing support.
+- Added modern Python package metadata under `Python/rdpower`, including
+  `pyproject.toml`, package-level licensing, README content, and shared utility
+  helpers.
+- Added scripts for repository validation and Stata help PDF generation.
+- Added R summary methods for `rdpower`, `rdmde`, and `rdsampsi` output objects.
+
+### Changed
+
+- Updated the R package to version 3.0, the Python package to version 2.0.0, and
+  the Stata distribution date to 2026-05-15.
+- Modernized package metadata with current author emails, GPL-3.0 licensing
+  metadata, and repository issue links.
+- Moved the Python package from `python/rdpower` to `Python/rdpower` and removed
+  stale generated Python build artifacts from version control.
+- Refreshed README content, R documentation, Python documentation, Stata help
+  files and PDFs, and the R, Python, and Stata illustration scripts.
+- Aligned R output handling with the new summary methods while preserving the
+  package's returned result objects.
+- Removed temporary audit baseline files from tracked content after release
+  preparation.
+
+### Validated
+
+- Added package-level checks intended to cover R, Python, and Stata numerical
+  baselines, repository metadata, Python package tests, and Stata help artifact
+  consistency.