Estimate confidence intervals in means of correlated time series with a small number of effective samples (like molecular dynamics simulations).
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Updated
Dec 27, 2022 - Python
Estimate confidence intervals in means of correlated time series with a small number of effective samples (like molecular dynamics simulations).
This package implements a non-parametric method that makes use of the wavelet cross-covariance at different scales to combine the measurements coming from an array of sensors in order to deliver an optimal measurement signal with weak assumptions on the processes underlying the individual error signals.
Analysis of spatial distribution of income in Italy
Open-source investment analytics platform bridging academic research and retail finance. Features include portfolio risk decomposition [Fama-French Five Factor Model], retirement sustainability modeling [Block Bootstrap Monte Carlo], max drawdown/CVaR dashboards, and risk-return optimisation [Markowitz, Ledoit-Wolf] via an intuitive user interface.
Monte Carlo study of dollar-cost-averaging strategies, 1980–2026. Ranks 56 portfolios (static, age-glide, momentum/signal) by median final wealth vs. terminal drawdown pain via block-bootstrap simulation in taxable and tax-free accounts. Full write-up in wealth_report.pdf.
A statistics package with a variety of bootstrap and other resampling tools
A statistics package with a variety of bootstrap and other resampling tools. This repository is synced to the same-named repository owned by GNU-Octave. It exists to facilitate publication of the developmental version of the statistics-resampling toolbox at MathWorks FileExchange.
15. Višestruko / panel sečenje sliding window stability, expanding window, block bootstrap, stratified by era, cohort split, concept-drift detectors (ADWIN, DDM, Page-Hinkley)
Non-parametric portfolio risk simulator using circular block bootstrap (Politis-Romano). Simulates outcome distributions, VaR/CVaR, drawdown, DCA/SIP -- with walk-forward calibration and 52 + 58 QA invariant checks.
Probabilistic forecasting and walk-forward validation for Brazilian markets.
R package with a set of functions to select the optimal block-length for a dependent bootstrap (block-bootstrap). Includes the Hall, Horowitz, and Jing (1995) cross-validation method and the Politis and White (2004) Spectral Density Plug-in method.
How often a nominal 95% bootstrap confidence interval actually covers, when the data are autocorrelated. One file, numpy only, reproducible.
Monte Carlo blackjack engine measuring conditional edge by true count, then Kelly bet sizing with risk of ruin from a block bootstrap
Paper VII of Statistical Pharmacology via Kakutani Dichotomy: kakutani_pharma, a Python pipeline for Kakutani indices of MD conformational ensembles. Ledoit-Wolf regularized CKI with an exact three-way decomposition, split-trajectory null subtraction, within-half block bootstrap, and pocket-centred shell-scaling exponents. Validated on a synthetic
Paper VIII of Statistical Pharmacology via Kakutani Dichotomy: validation on real PDB ensembles (ubiquitin NMR, adenylate kinase), Isserlis bound and influence-function block selection, bootstrap coverage calibration. Code, data, paper.
Pre-registered market-signal studies: sha256-frozen hypotheses, block-bootstrap p-values, Benjamini-Hochberg correction and a hold-out opened once. Both studies failed and were abandoned.
Fast, dependence-aware resampling and uncertainty for time series and ragged panels.
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