Compute an unbiased sample covariance incrementally.

Efficient batch statistics computation library for Python.

Geostatistical models for the GeoStats.jl framework

Geostatistical functions for the GeoStats.jl framework

A Portfolio Object to automatically do portfolio optimization and statistics on historical stock data from Yahoo! Finance in Rstudio

This repository contains a project using the Iris dataset for data visualization, outlier detection, normalization, and classification. The project includes models like GaussianNB, RandomForestClassifier, and DecisionTreeClassifier, with hyperparameter tuning and PCA for dimensionality reduction.

SIMD-enabled descriptive statistics (mean, variance, covariance, correlation)

Fast streaming univariate and bivariate moments and t-statistics

Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity

Proof of principle implementation of a fully covariant filtering scheme for relativistic turbulence.

Synthetic examples and data code related to paper "Ageostrophic corrections for power spectra and wave–vortex decomposition"

Gaussian process regression

Compute a moving sample Pearson product-moment correlation coefficient incrementally.

Java programming exercises from Section 19 - Java Course by Nelio Alves

Project for the Data Science PhD course of Probability

Compute an unbiased sample covariance matrix incrementally.

Compute a sample Pearson product-moment correlation distance matrix incrementally.

Compute a sample Pearson product-moment correlation matrix incrementally.

Compute a sample absolute Pearson product-moment correlation coefficient.