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Top 22 Econometric Open-Source Projects
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Financial-Models-Numerical-Methods
Collection of notebooks about quantitative finance, with interactive python code.
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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EconML
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of
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I can't find the TimeGPT-1 model.
LICENSE Apache-2
https://github.com/Nixtla/statsforecast/blob/main/LICENSE
Mentions ARIMA, ETS, CES, and Theta modeling
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pmdarima
A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.
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Project mention: 80% faster, 50% less memory, 0% loss of accuracy Llama finetuning | news.ycombinator.com | 2023-12-01
Good point - the main issue is we encountered this exact issue with our old package Hyperlearn (https://github.com/danielhanchen/hyperlearn).
I OSSed all the code to the community - I'm actually an extremely open person and I love contributing to the OSS community.
The issue was the package got gobbled up by other startups and big tech companies with no credit - I didn't want any cash from it, but it stung and hurt really bad hearing other startups and companies claim it was them who made it faster, whilst it was actually my work. It hurt really bad - as an OSS person, I don't want money, but just some recognition for the work.
I also used to accept and help everyone with their writing their startup's software, but I never got paid or even any thanks - sadly I didn't expect the world to be such a hostile place.
So after a sad awakening, I decided with my brother instead of OSSing everything, we would first OSS something which is still very good - 5X faster training is already very reasonable.
I'm all open to other suggestions on how we should approach this though! There are no evil intentions - in fact I insisted we OSS EVERYTHING even the 30x faster algos, but after a level headed discussion with my brother - we still have to pay life expenses no?
If you have other ways we can go about this - I'm all ears!! We're literally making stuff up as we go along!
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fecon235
Notebooks for financial economics. Keywords: Jupyter notebook pandas Federal Reserve FRED Ferbus GDP CPI PCE inflation unemployment wage income debt Case-Shiller housing asset portfolio equities SPX bonds TIPS rates currency FX euro EUR USD JPY yen XAU gold Brent WTI oil Holt-Winters time-series forecasting statistics econometrics
Project mention: Financial Economics: Financial Economics Models. Extended Research - star count:1033.0 | /r/algoprojects | 2023-12-10 -
WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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Robyn
Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry through innovation, reduce human bias in the modeling process & build a strong open source marketing science community. (by facebookexperimental)
With all this talk about Google and other platforms deprecating 3P tracking in favor of more aggregate "tracking", my team is considering a marketing mix modeling tool. One that comes to mind is this tool - Robyn
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lightweight_mmm
LightweightMMM 🦇 is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channel attribution information.
Project mention: Lightweight (Bayesian) Marketing Mix Modeling (Google Unofficial) | news.ycombinator.com | 2023-07-05 -
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hierarchicalforecast
Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.
Project mention: [D] When less is more in the hierarchical forecasting case. | /r/MachineLearning | 2023-07-03 -
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Econometrics-With-Python
Tutorials of econometrics featuring Python programming. This is a crash course for reviewing the most important concepts and techniques of basic econometrics, the theories are presented lightly without hustles of derivation and Python codes are straightforward.
Project mention: Python for Econometrics for Practitioners [Free Online Courses] | /r/CompSocial | 2023-08-24Econometrics with Python: This is a crash course for reviewing the most important concepts and techniques of econometrics. The theories are presented lightly without hustles of mathematical derivation and Python codes are mostly procedural and straightforward. Core concepts covered: multi- linear regression, logistic model, dummy variable, simultaneous equations model, panel data model and time series.
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wooldridge
The official R data package for "Introductory Econometrics: A Modern Approach". A vignette contains example models from each chapter.
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econometrics-cheatsheet
Multiple econometrics cheat sheets with a complete and summarize review going from the basics of an econometric model to the solution of the most popular problems.
Project mention: Econometrics Cheat Sheet (Additional) now includes ANOVA and logit! | /r/econometrics | 2023-05-31 -
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Project mention: Python for Econometrics for Practitioners [Free Online Courses] | /r/CompSocial | 2023-08-24
Bayesian Statistics with Python: Bayesian statistics is the last pillar of quantitative framework, also the most challenging subject. The course will explore the algorithms of Markov chain Monte Carlo (MCMC), specifically Metropolis-Hastings, Gibbs Sampler and etc., we will build up our own toy model from crude Python functions. In the meanwhile, we will cover the PyMC3, which is a library for probabilistic programming specializing in Bayesian statistics.
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Project mention: MarSwitching.jl: New package for Markov Switching regression models | /r/Julia | 2023-10-04
You can read more and check example in the package repo here: https://github.com/m-dadej/MarSwitching.jl
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ols_regression
OLS regression with possibility of controlling for fixed effects and robust standard errors
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SaaSHub
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NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
The latest post mention was on 2023-12-10.
Econometrics related posts
- Lightweight (Bayesian) Marketing Mix Modeling (Google Unofficial)
- [D] When less is more in the hierarchical forecasting case.
- Econometrics Cheat Sheet (Additional) now includes ANOVA and logit!
- Show HN: Marketing software for solopreneurs who don't like marketing
- Mixed Marketing Modeling Approach for attribution?
- statsmodels Release Candidate 0.14.0rc0 tagged
- How to generate Errors using Scipy Minimize with Powell Method
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A note from our sponsor - WorkOS
workos.com | 15 Apr 2024
Index
What are some of the best open-source Econometric projects? This list will help you:
| Project | Stars | |
|---|---|---|
| 1 | statsmodels | 9,513 |
| 2 | Financial-Models-Numerical-Methods | 5,238 |
| 3 | EconML | 3,528 |
| 4 | statsforecast | 3,507 |
| 5 | pmdarima | 1,513 |
| 6 | hyperlearn | 1,510 |
| 7 | fecon235 | 1,088 |
| 8 | Robyn | 1,021 |
| 9 | lightweight_mmm | 771 |
| 10 | collapse | 598 |
| 11 | hierarchicalforecast | 510 |
| 12 | causallift | 332 |
| 13 | Econometrics-With-Python | 250 |
| 14 | wooldridge | 189 |
| 15 | econometrics-cheatsheet | 88 |
| 16 | ARCHModels.jl | 87 |
| 17 | Bayesian-Statistics-Econometrics | 71 |
| 18 | priceR | 55 |
| 19 | MarSwitching.jl | 34 |
| 20 | Statmetrics-Android | 6 |
| 21 | twostage_regress | 1 |
| 22 | ols_regression | 0 |
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