Reliability engineering toolkit for Python - https://reliability.readthedocs.io/en/latest/

Probabilistic Machine Learning for Finance and Investing: A Primer to Generative AI with Python

By-hand code for models and algorithms. An update to the 'Miscellaneous-R-Code' repo.

This project used GARCH type models to estimate volatility and used delta hedging method to make a profit.

David Mackay's book review and problem solvings and own python codes, mathematica files

Gauss Naive Bayes in Python From Scratch.

Maximum Likelihood estimation and Simulation for Stochastic Differential Equations (Diffusions)

A Python implementation of Naive Bayes from scratch.

A High Performance Unified Framework for Geostatistics on Manycore Systems.

Python+Rust implementation of the Probabilistic Principal Component Analysis model

A comprehensive bundle of utilities for the estimation of probability of informed trading models: original PIN in Easley and O'Hara (1992) and Easley et al. (1996); Multilayer PIN (MPIN) in Ersan (2016); Adjusted PIN (AdjPIN) in Duarte and Young (2009); and volume-synchronized PIN (VPIN) in Easley et al. (2011, 2012). Implementations of various …

Slides and notebooks for my tutorial at PyData London 2018

This repo contains code for GeoMLE intrinsic dimension estimation algorithm

🐙: Maximum likelihood model estimation using scipy.optimize

Developed a Windows-based app for analyzing data distributions and identifying the best-fitted distribution using the Maximum Likelihood Estimation algorithm. The app features histogram analysis, error ranking, and allows users to directly save results along with distribution charts.

This repository has scripts and other files that are part of the lecture notes and assignments of the course "Advanced Statistical Inference" taught at FME, UPC Barcelonatech.

Implementation of Neural Nets for Communications Channel Decoding using Log Likelihood Ratios

Accucopy is a computational method that infers Allele-Specific Copy Number alterations from low-coverage low-purity tumor sequencing data.

Python tools for working with the IceCube public data.

Fit multievent capture-recapture models in R (maximum-likelihood), Nimble and JAGS (Bayesian)