LSTM vs GRU

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This project combines weekly epidemiological case counts of pneumonic plague in Madagascar (Aug–Nov 2017) with Google Trends data for related search terms to explore how online interest tracks—and even predicts—disease spread.

ggplot2 extension for multivariable data visualizations, spun off from ordr

Flexible Statistics and Data Analysis (FSDA) extends MATLAB for a robust analysis of data sets affected by different sources of heterogeneity. It is open source software licensed under the European Union Public Licence (EUPL). FSDA is a joint project by the University of Parma and the Joint Research Centre of the European Commission.

an R package for structural equation modeling and more

Multivariate analysis of the Titanic dataset, including descriptive statistics, exploration of demographic and socioeconomic variables, data standardization, clustering methods (k-means and hierarchical), and visualizations. The repository provides R scripts for interpreting passenger profiles.

MSPC application to seismic data developed as part of the DigiVolCan project.

Complex / 2d multivariate bivariate colormap / Domain coloring for Matplotlib, Plotly etc. (pure-numpy)

Github repo for my in-progress book, "Visualizing Multivariate Data and Models in R" to be published by Taylor & Francis (CRC Press), 2026

Advanced Time Series Forecasting using a custom Attention-LSTM architecture. Compares performance against standard LSTM and ARIMA, focusing on interpreting temporal dependencies via attention weights.

A numerical computation library for C#

Integrate your chemometric tools with the scikit-learn API 🧪 🤖

Wine data multivariate analysis with MDS, PCA and Correspondence Analysis.

A repository of our work for the Data Mining competition held by Intelecta Cup, Telkom University 2025

A repository of our work for the Data Science Competition held by Gelar Rasa, UPN Veteran Jawa Timur 2025

KNIME Statistics and Social Science Extension is designed to provide Python-based nodes for advanced statistical and social science analysis. This extension enables researchers and analysts to integrate sophisticated statistical methods into their KNIME workflows, enhancing their ability to conduct robust data analysis.

R package for high-dimensional multivariate Bayesian variable and covariance selection in linear regression

The Definitive Principal Component Analysis Application