An interpretable framework for inferring nonlinear multivariate Granger causality based on self-explaining neural networks.
The asympPDC Package is a MATLAB and Octave package for Partial Directed Coherence (PDC) and Directed Transfer Function (DTF) estimation with asymptotic statistics, allied functions and routines for Granger Causality Test and results pretty plotting.
Source localization and connectivity analysis of high-density EEG data
This project is about energy efficiency and renewable energy topic. Developed multivariate time series model to forecast global warming. Analyzed various causes of global warming including energy consumption, emissions; examined correlation and causality of temperature, CO2 concentration, population time series. Discovered the logical connection…
Functional connectivity tools, classifiers and visualizers (Py-MNE, EEG)
This repository contains the Matlab code for implementing the bootstrap panel Granger causality procedure proposed by Kónya (Kónya, L. Exports and growth: Granger causality analysis on OECD countries with a panel data approach. Economic Modelling, 23(6), 978-992, 2006), which is based on the seemingly unrelated regressions (SUR) systems and the …
Top-Down Investment Strategy Optimization with Time Series Forecasting
Explore omnichannel marketing and how a company can optimally allocate their budget across marketing channels to maximise sales using the VAR model.
"CauFR-TS: Causal Time Series Identifiability via Factorized Representations." [TMLR 2026]
This project is related to news coverage regarding COVID-19 around the world. Using LDA topic modeling, we have extracted topics in news about COVID- 19 over time and from different parts of the world.
This study investigates the relationship between weather conditions and tea prices across different market catalogues and develops machine learning approaches for price forecasting.
Time series analysis and forecasting project based on Walmart Sales Data.
Minutes played by under 21 players in Serie A
Additional statistical tests conducted using R as part of my masters dissertation.
Investment Analysis and Asset Mgmt, Time Series Analysis & Forecasting, Machine Learning in Finance & Causal Inference Methods
VAR analysis of monetary policy transmission channels in Morocco using quarterly data from 2007 to 2018.
This repository explores the relationship between foreign direct investment and economic growth in regional comprehensive partnership (RCEP) countries
🚗 Advanced LSTM-based transportation demand forecasting achieving MAPE: 2.8% with multivariate time-series analysis ⚡ Real-time prediction API with external regressors (weather, events) and statistical validation using Granger causality tests
Time-Varying Partial-Correlation Network with Granger-Causal Edge Direction
Library of causal analisys alorthims which was created as main subject of BSc thesis. It was further developted as part of MA thesis. It implements various implementations of Granger Analisys algorithms with modifications. It is also designed to allow easy customization and development.
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