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https://github.com/weijie-chen/bayesian-statistics-econometrics
Bayesian Statistics-Econometrics
https://github.com/weijie-chen/bayesian-statistics-econometrics
bayesian-inference bayesian-methods bayesian-statistics econometrics statistics
Last synced: 2 days ago
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Bayesian Statistics-Econometrics
- Host: GitHub
- URL: https://github.com/weijie-chen/bayesian-statistics-econometrics
- Owner: weijie-chen
- License: mit
- Created: 2022-01-13T19:43:20.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2024-06-09T19:16:05.000Z (5 months ago)
- Last Synced: 2024-06-10T13:40:04.045Z (5 months ago)
- Topics: bayesian-inference, bayesian-methods, bayesian-statistics, econometrics, statistics
- Language: Jupyter Notebook
- Homepage:
- Size: 14.7 MB
- Stars: 76
- Watchers: 1
- Forks: 31
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Bayesian Statistics and Econometrics
This is a training session of Bayesian statistical methods, the content presented are essential elements of machine learning framework. The session is prepared for senior quantitative analysts/researchers in hedge fund or other research institutes who wants to refresh Bayesian methods quickly, also perfect for grad student who are interested in quantitative methods in industry. All proprietary data and cases are censored, thus no institutional information or data are revealed in these training materials.
## Prerequisites
The courses are not for beginners, the attendees must have working knowledge of linear algrebra, statistics and probability theory, and ideally advanced econometrics skills too.
And also the attendees are assumed to have constant exposure of
- [x] Python
- [x] NumPy
- [x] Matplotlib
- [x] Statsmodels
- [x] Pandas
If you are not familiar with linear regression mechanism, take a look at these notes first.
## Contents
### Advanced Econometric and Statistical Methods
[Chapter 1 - Geometry of Odinary Least Squares](https://nbviewer.org/github/MacroAnalyst/Advanced_Quantitative_Methods/blob/main/Chapter%201%20-%20Geometry%20of%20Ordinary%20Least%20Squares.ipynb)
[Chapter 2 - Statistical Properties of OLS](https://github.com/MacroAnalyst/Advanced_Quantitative_Methods/blob/main/Chapter%202%20-%20Statistical%20Properties%20of%20OLS.ipynb)
[Chapter 3b - Hypothesis Test and Confidence Interval](https://nbviewer.org/github/MacroAnalyst/Advanced_Quantitative_Methods/blob/main/Chapter%203%20-%20Hypothesis%20Test%20and%20Confidence%20Interval.ipynb)
It is advised that you download all material and browse in your own computer, since nbviewer has persistent LaTeX rendering errors.
### Bayesian Methods
[Chapter 1 - Introduction to Bayesian Methods](https://nbviewer.org/github/MacroAnalyst/Advanced_Quantitative_Methods/blob/main/Chapter%201%20-%20Overview%20of%20Bayesian%20Approach.ipynb)
[Chapter 2 - Bayesian Conjugates](https://nbviewer.org/github/MacroAnalyst/Advanced_Quantitative_Methods/blob/main/Chapter%202%20-%20%20Bayesian%20Conjugates.ipynb)
[Chapter 3 - Bayesian Simple Linear Regression](https://nbviewer.org/github/MacroAnalyst/Advanced_Quantitative_Methods/blob/main/Chapter%203%20-%20Bayesian%20Simple%20Linear%20Regression.ipynb)
[Chapter 4 - Markov Chain Monte Carlo](https://nbviewer.org/github/MacroAnalyst/Advanced_Quantitative_Methods/blob/main/Chapter%204%20-%20Markov%20Chain%20Monte%20Carlo.ipynb)
[Chapter 5 - Metropolis-Hastings Algorithm](https://nbviewer.org/github/MacroAnalyst/Advanced_Quantitative_Methods/blob/main/Chapter%205%20-%20Metropolis-Hastings%20Algorithm.ipynb)
[Chapter 6 - Gibbs Sampler](https://nbviewer.org/github/MacroAnalyst/Advanced_Quantitative_Methods/blob/main/Chapter%206%20-%20Gibbs%20Sampler.ipynb)
[Chapter 7 - Revisit Linear Regression](https://nbviewer.org/github/MacroAnalyst/Advanced_Quantitative_Methods/blob/main/Chapter%207%20-%20Revisit%20Linear%20Regression%20With%20MCMC.ipynb)
### Screen Captures
