Implements a test of coefficient stability under different assumptions of unobservable selection.

Fork from https://github.com/MCG-NKU/NSFC-LaTex, 但用楷体作为主要字体

A lightweight Model Context Protocol (MCP) server for Stata. Execute commands, inspect data, retrieve stored results (r()/e()), and view graphs in your chat interface. Built for economists who wan…

Difference-in-Differences via Common Correlated Effects

Generalized Imputation Estimator

Quasi-long Differencing Panel Data Estimator

A series of notebook about various data analysis related to finance concepts, which are assignment of the course '20598 - Finance with Big Data''

Penalized Poisson Pseudo Maximum Likelihood

Python code for "Probabilistic Machine learning" book by Kevin Murphy

Specification Curve is a Python package that performs specification curve analysis: exploring how a coefficient varies under multiple different specifications of a statistical model.

R package for Panel Tree method and replication file for the paper "Growing the Efficient Frontier on Panel Trees", forthcoming in the Journal of Financial Economics.

A modern, high customizable, responsive Jekyll theme for documentation with built-in search.

TimeGPT-1: production ready pre-trained Time Series Foundation Model for forecasting and anomaly detection. Generative pretrained transformer for time series trained on over 100B data points. It's …

A python library for user-friendly forecasting and anomaly detection on time series.

A Python toolkit/library for reality-centric machine/deep learning and data mining on partially-observed time series, including SOTA neural network models for scientific analysis tasks of imputatio…

Examples of PyMC models, including a library of Jupyter notebooks.

Doing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC3 code

My solutions to the assignments in the book: "A Student’s Guide to Bayesian Statistics" by Ben Lambert.

Bayesian Modeling and Probabilistic Programming in Python

PyMC educational resources

Master the Toolkit of AI and Machine Learning. Mathematics for Machine Learning and Data Science is a beginner-friendly Specialization where you’ll learn the fundamental mathematics toolkit of mach…

Code / solutions for Mathematics for Machine Learning (MML Book)

Companion webpage to the book "Mathematics For Machine Learning"

Bringing BERT into modernity via both architecture changes and scaling

NanoGPT (124M) in 2 minutes

Machine Learning and Causal Inference taught by Brigham Frandsen