Traffic prediction is the task of predicting future traffic measurements (e.g. volume, speed, etc.) in a road network (graph), using historical data (timeseries).

📓 Utility provides a more meaningful measure of forecast skill than goodness-of-fit

Literature Survey about the available Diffusion Models capable of Time-Series Forecasting

Repo to showcase solution examples and learning content curated by the advanced analytics experts within Microsoft Finance

Understanding, evaluating, and improving forecasts of infectious disease burden

Does the mind have statistical models? Even if it does, are these models Bayesian? We explore these questions as a part of my Masters capstone project guided by Prof. Glenn Shafer

Python package for Singular Spectrum Analysis

We are presenting a Bayesian local-level model and its extensions

Evaluation of a simplified forecasting model designed to emulate the performance of the ECDC forecasting hub.

[READ-ONLY MIRROR] LaTeX files for the paper "Real-time Demand Forecasting for an Urban Delivery Platform"

Feng Li's texmf database

A collaborative repository highlighting Bayesian autoregressive analysis with extensions. It is prepared by the students of Macroeconometrics at the University of Melbourne.

Latex project for the paper that I wrote for my thesis.

AI Explainability 360 Toolkit for Time-Series and Industrial Use Cases

Repositório do ferranaData, modelo preditor de eleições proporcionais no Brasil

Time series analysis project: forecasting brazilian inflation.

Companion analysis to a paper published in the Journal of Digital Imaging.

Masters Project: Forecasting Unemployment

Repo for a study project in Forecasting in R during my Masters Degree in Data Science.

Slides for the 26th International Conference on Computational Statistics (COMPSTAT 2024)