M

monte-carlo

Python research code for sensitivity analysis in double machine learning. A twin design, in which the hidden confounder copies an observed benchmark covariate, tests a benchmark-calibrated omitted-variable-bias bound when the benchmark is itself estimated, with an application to 401(k) eligibility and a mathematical supplement.

Python research code that measures false-positive rates and minimum detectable lift of geo-experiment estimators by running placebo experiments on real county sales data with no intervention. Compares difference-in-differences, synthetic control, ridge-augmented SC, conformal tests and structural time series.

Python research code comparing interrupted time series (segmented regression) and Bayesian structural time series counterfactuals. Includes a Gibbs-sampled BSTS, Monte Carlo experiments on trends, seasonality, effect shape and triggered launches, and a placebo study of the 1983 UK seat belt law.

Python research code for synthetic control, donor-pool geometry, and placebo inference. Includes DiD, ridge-augmented SC, synthetic DiD, Monte Carlo experiments, and the California Proposition 99 case study.

Протокол проверки торговых гипотез: walk-forward, PBO/CSCV с калибровкой контрольными семействами, Deflated Sharpe, блочный бутстрап и нулевые модели, реалистичное исполнение

Paper-first market research with deterministic risk controls; live execution is disabled.

Monte Carlo electron transport simulation toolkit based on Magboltz data.

A Fortran program that performs a Monte Carlo simulation to study the interaction and equilibrium behavior of two water molecules using atomistic potentials and periodic boundary conditions.

Fermi-orbital descriptor Monte-Carlo

JavaScript / Game-of-life, Grain growth, Monte-Carlo, Recrystallization

MC event generator based on Laplace's method within phi-3 model. Languages: Fortran, C++.