Course materials for Computational Statistics, PhD course at EMAp.

Fast Weight of Evidence (WOE) Encoding and Inference

Bayesian spatio-temporal methods for small-area estimation of HIV indicators (PhD thesis, Imperial College London, 2023)

Class notes for the computational statistics class (Spanish), master in Data Science ITAM

CE083 - Estatística Computacional I

Forward-backward conditional sampling

An introduction to computational statistics with examples and comparison to analytical methods

Python implementation (from scratch) of some MCMC samplers that can leverage pyTorch's autodifferentiation (with examples).

Python Library for Hamiltonian Markov-Chain Monte-Carlo in Computational Statistics (pyHaiCS).

Algorithms and case studies for the paper "Accelerating delayed-acceptance Markov chain Monte Carlo algorithms".

Work from the PhD-Level Computation Statistics Course from FSU taken Spring 2019

Computational Statistics, STAT525, 2020Spring, UIUC

Markov Chain Monte Carlo(MCMC), Approximate Bayesian Computation(ABC), Bayesian Synthetic Likelihood(BSL), Variational Inference(VI)

A visual, hands-on introduction to Monte Carlo methods with clean simulations, intuitive explanations, and from-scratch implementations.

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.

Bayesian parameter estimation of HMMs in Julia

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.

Looking for the number of sticker packages one should buy in order to fully complete Panini's World Cup Album 2022.

:a: :b: :copyright: An Implementation of the ABC permutation test using R and C++ for Computational Statistics course CM0527

Work done for the Fall 2018 class of Computational Statistics at ENSAE

Computational Statistics

Extremely fast and scalable algorithms for phase-type distributions (including discrete, multivariate, rewarded, and time-inhomogeneous). Interface to both C and R

Third year mathematics dissertation on variational, laplace and mcmc approximations of bayesian logistic regression

Repository hosting website for the Neural Networks reading group at the University of Bristol.

Code for the PhD thesis. The topic was on defect detection of 3D printing using x-rays. The repository includes an implementation of the mode filter and empirical null filter.

Monte Carlo (MC) Integration and simulations in R and Python

Using R language to conduct data analysis and computational statistic projects

Probably not a bad way to manipulate random variables in Python

This is a repository for Yale course BIS 557 Computational Statistics.

Professional-grade presentations on advanced statistics, MCMC methods, and data science applications. Created by ESMAD faculty and Mysense.ai Lead Data Scientist. Includes theoretical foundations, modern algorithms, and industry implementations.