cmrdesign 0.1.0a1

Conditional Minimax Regret design rules for pilot-informed experiments

cmrdesign Python Package

Python implementation of cmrdesign, the applied Conditional Minimax Regret design-rule package.

The methods accompany When and How to Pilot: Design Rules for Two-Wave Experiments by Juan C. Yamin. This package is implementation-focused and uses simulated examples only; paper replications and empirical simulations are intentionally kept out of the package repository.

Installation

Until the first PyPI upload, install from GitHub for normal use:

python -m pip install "cmrdesign @ git+https://github.com/juancyamin/cmrdesign.git#subdirectory=python"

The first alpha candidate is also available on TestPyPI for release testing:

python -m pip install \
  --index-url https://test.pypi.org/simple/ \
  --extra-index-url https://pypi.org/simple \
  cmrdesign==0.1.0a1

For local development from the repository root:

python -m pip install -e python

Quick Example

import numpy as np
import cmrdesign as cmr

rng = np.random.default_rng(123)
d = np.r_[np.ones(40), np.zeros(40)]
y = np.r_[rng.beta(2, 5, 40), rng.beta(4, 4, 40)]

fit = cmr.cmr_two_arm(y, d, alpha=0.05, method="bounded")
print(fit.pi)
print(fit.U_CMR)

Implemented Surface

• cmr_two_arm() and cmr_binary().
• method="auto" for the applied bounded/binary default.
• Maurer-Pontil bounded-outcome variance rectangles.
• Exact Bernoulli folded-binomial variance rectangles.
• Martinez-Taboada-Ramdas (MTR) bounded-outcome rectangles.
• Two-arm unbounded-outcome median-of-means rectangles via cmr_unbounded().
• Shared-control multi-arm CMR via cmr_multiarm().
• Stratified CMR via cmr_stratified().
• Multiple-outcome CMR for weighted-index and co-primary workflows via cmr_multiple_outcomes().
• Proxy/delayed-outcome CMR bridge widening via cmr_proxy().
• Appendix E pilot-planning helpers via cmr_plan().
• Expert rectangle helpers via rectangle_*() and cmr_*_from_rectangle().

See the repository-level docs for applied guidance:

• docs/quickstart.md
• docs/choosing_methods.md
• docs/methods.md
• docs/pilot_planning.md

From the repository root, run local checks with:

python -m pip install -e python
python -m unittest discover -s python/tests -v