Gibbs sampler in C, Python, Node.js, Julia, and R
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Updated
Nov 27, 2017 - R
Julia is a high-level dynamic programming language designed to address the needs of high-performance numerical analysis and computational science. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library.
Gibbs sampler in C, Python, Node.js, Julia, and R
Working with data in Python, R, and Julia
Work related to statistical learning, computational statistics and applications to finance.
Worked problems and examples from Statistical Rethinking
An agent-based model to test the effect of different social-psychological aspects on the spread of epidemics
Code that might be useful to others for learning/demonstration purposes, specifically along the lines of modeling and various algorithms. **Superseded by the models-by-example repo**.
Methods of scientific computing - direct methods for sparse matrices
Can peacekeeping improve health outcomes? Looking at violence reduction and health infrastructure contributions as mechanisms for UNPKOs to improve healthy life expectancy.
My attempts at solving the programming puzzles in the Advent of Code (in R and Julia)
Statistical Learning, Machine Learning and Deep Learning algorithms
Handy reusable bioinformatic scripts
Example of a SAS-based Quarto document
Created by Jeff Bezanson, Stefan Karpinski, Viral B. Shah, Alan Edelman
Released February 14, 2012