Slides for the 26th International Conference on Computational Statistics (COMPSTAT 2024)
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Updated
Jun 6, 2024 - TeX
Slides for the 26th International Conference on Computational Statistics (COMPSTAT 2024)
Forward-backward conditional sampling
Bayesian spatio-temporal methods for small-area estimation of HIV indicators (PhD, Imperial College London, 2023)
Monte Carlo (MC) Integration and simulations in R and Python
A repository for the various functions and programs I've made in the area's of: Data Science, Analytics, Machine Learning & Statistics.
This is a project repo of Umich 2022-2023 Fall course STATS406, using computational statistical methods to analyze potential bias in hand-written digit prediction process
Code for the nested hybrid filters (NHFs), including four different implementations using sequential Monte Carlo (SMC), sequential quasi-Monte Carlo (SQMC), extended Kalman filters (EKFs) and ensemble Kalman filters (EnKFs). I have also included the implementation of the nested particle filter (NPF) and the two-stage filter to compare performance.
A machine learning approach to categorize NBA players by role using shot characteristic data, highlighting the game's evolution over three decades.
Course of computational statistics of the course of studies in applied computer science and data analysis (IADA)
Course materials for Computational Statistics, PhD course at EMAp.
A modernised ✨ version of the Gaussian Processes in Python package 📦 to be used natively with Python 3 🐍
Statistical Methods for Heart Disease & Indicators Using R Programming
Using R language to conduct data analysis and computational statistic projects
Project for the Computational Statistics course of the MSc in Mathematical Engineering @ Polimi (A.Y. 2022-2023).
Antithetic Variates for Monte Carlo Variance Reduction
Code for the nested Gaussian filters (NGFs), in particular, an implementation of an unscented Kalman filter (UKF) combined with a bank of extended Kalman filters (EKFs). Other algorithms are implemented to compare performance.
A Python framework for working with random variables
Computational Statistics
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