Python code accompanying our paper, Combining Evidence Across Filtrations Using Adjusters.
ecombine/ is the source package that implements adjusters/calibrators, e-processes, data generators, and plotting functions.
The following notebooks contain code and plots related to various numerical results in the paper.
nb_exchangeability_elifting.ipynb: stopped e-values for testing exchangeability, null case (Figures 1 and 4).nb_exchangeability_elifting_alternative.ipynb: stopped e-values for testing exchangeability, alternative cases (Figure 5).nb_exchangeability_elifting_randomization.ipynb: includes the estimate for the type I error of the randomize-then-lift procedure (Section 6.3).nb_exchangeability_elifting_spine_adjusters.ipynb: includes the estimate for the stopped e-value when using the spine adjuster (Appendix G).nb_adjusters.ipynb: plots of various adjusters (Figures 2 and 6)
git clone https://github.com/yjchoe/CombiningEvidenceAcrossFiltrations
cd CombiningEvidenceAcrossFiltrations
pip install --upgrade pip
pip install -r requirements.txt
pip install -e .The following code combines the UI and conformal e-processes for testing exchangeability given a binary data sequence:
import numpy as np
import matplotlib.pyplot as plt
import ecombine as ec
# generate data with a "shock" changepoint
rng = np.random.default_rng(2024)
T = 2000
p, q = 0.5, 0.2
change_loc, change_len = 0.2, 0.04
x = ec.data.exch.generate_binary_changepoint(
p=p, q=q, size=T,
change_loc=change_loc, change_len=change_len, rng=rng,
)
# compute e-processes; the conformal variant requires adjustment for anytime-validity wrt data
e_ui = ec.eprocess_exch_universal(x)
e_conf = ec.eprocess_exch_conformal(
x, jump=0.01, jumper_weights=(1/3, 1/3, 1/3), rng=rng,
)
# combined e-process is valid at any data-dependent stopping times!
e_combined = 0.5 * e_ui + 0.5 * ec.adjuster(e_conf)
# plotting
ec.set_theme()
fg = ec.plot_eprocess(
[e_ui, e_conf, e_combined],
["UI", "Conformal", "eLift+Avg"],
title="E-processes for Testing Exchangeability",
)
plt.show()See further usage in nb_exchangeability_elifting_alternative.ipynb.
MIT
If you use parts of our work, please cite our paper as follows:
APA:
Choe, Y. J., & Ramdas, A. (2024). Combining evidence across filtrations using adjusters. arXiv preprint arXiv:2402.09698.
BibTeX:
@article{choe2024combining,
title={Combining Evidence Across Filtrations Using Adjusters},
author={Choe, Yo Joong and Ramdas, Aaditya},
journal={arXiv preprint arXiv:2402.09698},
year={2024}
}