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hyuhongzi's Projects

539b icon 539b

(Advanced) Applied Econometrics

advanced-did icon advanced-did

Advanced Differnce-in-Differences Mixtape Track taught by Jonathan Roth

awesome-python icon awesome-python

An opinionated list of awesome Python frameworks, libraries, software and resources.

awesome-quant icon awesome-quant

A curated list of insanely awesome libraries, packages and resources for Quants (Quantitative Finance)

climate-econ icon climate-econ

A repository for tracking developments in the climate/environmental/ecological economics literature

dadengandhispython icon dadengandhispython

【微信公众号：大邓和他的python】, Python语法快速入门https://www.bilibili.com/video/av44384851 Python网络爬虫快速入门https://www.bilibili.com/video/av72010301, 我的联系邮箱[email protected]

did_handbook icon did_handbook

This repository summarizes the traditional and recently proposed estimators for the difference-in-differences specifications.

dotfiles icon dotfiles

Dot files for Evan Chen (Arch Linux on i3)

gformula icon gformula

The gfoRmula package implements the parametric g-formula in R. The parametric g-formula (Robins, 1986) uses longitudinal data with time-varying treatments and confounders to estimate the risk or mean of an outcome under hypothetical treatment strategies specified by the user.

latex-templates icon latex-templates

A collection of awesome LaTeX Thesis/Dissertation templates and beyond! （LaTeX / Word / Typst / Markdown 格式的学位论文、演示文稿、报告、项目申请书、简历、书籍等模板收藏）

lean icon lean

Lean Algorithmic Trading Engine by QuantConnect (Python, C#)

llmbox icon llmbox

A comprehensive library for implementing LLMs, including a unified training pipeline and comprehensive model evaluation.

mathmodel icon mathmodel

研究生数学建模，本科生数学建模、数学建模竞赛优秀论文，数学建模算法，LaTeX论文模板，算法思维导图，参考书籍，Matlab软件教程，PPT

mixtape icon mixtape

Data and Program files for Causal Inference: The Mixtape

phdmacro2021 icon phdmacro2021

This is the course homepage of Advanced Macroeconomics II of Jinan University in Fall, 2021.

py4fi2nd icon py4fi2nd

Jupyter Notebooks and code for Python for Finance (2nd ed., O'Reilly) by Yves Hilpisch.

pydata-book icon pydata-book

Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media

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