Stock price prediction using a Temporal Fusion Transformer

Python package for Singular Spectrum Analysis

A seminar paper on causal discovery from log data, focusing on time-series analysis and computational methods in causal inference.

Machine Learning case study including an exploratory data analysis and fitting a Decision Tree, Random Forest, and XGBoost Model. Interactive notebook with outputs and visualizations: https://yaldan.github.io/ml_case_study/

A seminar paper on efficient correlation discovery in time-series streams, exploring global and local correlation detection methods.

Building a vector autoregressive model with R. My coursework for the course Time Series Analysis II (offered by University of Helsinki's Master's Programme in Mathematics and Statistics), spring 2020.

Testing the hyphotesis of cointegration of two term structures through Dickey-Fuller tests and Engle-Granger causality. Finally I exploit the VECM to infer the model and through the Cholesky decomposition I analyze SIRF and FEVD

Supplementary material for the chapter "Vector Autoregressive Moving Average Models" in Vol 41 of Handbook of Statistics

R book created for the course Advanced Data Analysis 2

Talk on Australian COVID-19-related disruptions in health services and data

This repository accompanies the publication: '​A Gentle Introduction and Application of Feature-Based Clustering with Psychological Time Series'.

Large-scale Dynamic Models of Complex Networks

Monitoring parallel file system usage in a high-performance computer cluster

Talk on Newey-West estimator for ITS

source code for evaluating restoration projects in Tampa Bay

Exploration of environmental variables and death over time