nonparametric-estimation

Experimental T-HAL-MLE R package (AGPL-3.0-or-later)

A comprehensive Python survival analysis workflow using statsmodels. Covers Kaplan-Meier estimation, log-rank tests, Cox proportional hazards regression, and alternative approaches like Nelson-Aalen and Accelerated Failure Time models with practical code examples.

Reference implementation of a conditional-likelihood rectangular-sieve estimator for bivariate union-selected data with truncation and one-sided censoring.

Reproducible experiments for direct nonparametric estimation of Schrödinger-bridge time-series drifts.