A simple utility to perform sampling from multivariate distributions (supported by a PyTorch backend)

Machine Learning algorithms using Sklearn and Scikit python libraries for comparing their behaviour on anomaly detection

Implemented from scratch a sampling method to draw samples from a multivariate Normal (MVN) distribution in JAX.

Programa Computarizado, elaborado en el lenguaje de programacion MATLAB, referente al Trabajo Especial de Grado para optar al Título de Ingeniero Industrial, en la Facultad de Ingeniería de la Universidad de Carabobo, año 2015; la cual fue reconocida con mención honorífica.

A Collection of Basic Utilities for Statistical Analyses

Implementation of the Extreme Joint Distribution algorithm in C++

UniBG modelli stocastici prova 00 a.a. 2017-2018

Simulation of Partition-of-Unity copulas in R, e.g. for the purpose of modeling risk or for the creation of synthetic data based on restricted datasets

Provides multivariate normal distribution sampling and matrix inversion for Jetbrain's new NDArray library Multik, by bodging it with some classes (including tests) from Apache Commons Maths 3 & 4, translated into Kotlin and made JVM independent for a Kotlin Multi-Platform project.

Here all my machine learning notebooks will be uploaded

Random data generator from scratch. (Using numpy for simple mathematical functions only)

Collection of missing multivariate random number distributions for Modern C++ with STL-like API.

Multivariate independent comparison of observations.

A Python Package to Create Synthetic Tabular Data

Multivariate independent comparison of observations

Lottery analysis

Robust estimation using heavy-tailed distributions