GitPlanet

Cheap and reliable Node.js hosting starts at $3/month, and $1/month static HTML hosting

Created with love in Canada, visit hostnodejs.com today

Feel like to post an Ad? Learn Details
All Projects → esantorella → hdfe

esantorella / hdfe

Licence: MIT License
No description or website provided.

Programming Languages

python
139335 projects - #7 most used programming language
Dockerfile
14818 projects

Labels

statisticsregressionpandaseconometrics

Projects that are alternatives of or similar to hdfe

Machine Learning With Python
Practice and tutorial-style notebooks covering wide variety of machine learning techniques
Stars: ✭ 2,197 (+9886.36%)
Mutual labels:  statistics, regression, pandas
Data Science Toolkit
Collection of stats, modeling, and data science tools in Python and R.
Stars: ✭ 169 (+668.18%)
Mutual labels:  statistics, regression
Math Php
Powerful modern math library for PHP: Features descriptive statistics and regressions; Continuous and discrete probability distributions; Linear algebra with matrices and vectors, Numerical analysis; special mathematical functions; Algebra
Stars: ✭ 2,009 (+9031.82%)
Mutual labels:  statistics, regression
Peroxide
Rust numeric library with R, MATLAB & Python syntax
Stars: ✭ 191 (+768.18%)
Mutual labels:  statistics, regression
Interactive machine learning
IPython widgets, interactive plots, interactive machine learning
Stars: ✭ 140 (+536.36%)
Mutual labels:  statistics, regression
Tidyversity
🎓 Tidy tools for academics
Stars: ✭ 155 (+604.55%)
Mutual labels:  statistics, regression
Uci Ml Api
Simple API for UCI Machine Learning Dataset Repository (search, download, analyze)
Stars: ✭ 190 (+763.64%)
Mutual labels:  statistics, regression
Weightedcalcs
Pandas-based utility to calculate weighted means, medians, distributions, standard deviations, and more.
Stars: ✭ 83 (+277.27%)
Mutual labels:  statistics, pandas
Mathnet Numerics
Math.NET Numerics
Stars: ✭ 2,688 (+12118.18%)
Mutual labels:  statistics, regression
Simple Statistics
simple statistics for node & browser javascript
Stars: ✭ 2,679 (+12077.27%)
Mutual labels:  statistics, regression
Microeconometrics.jl
Microeconometric estimation in Julia
Stars: ✭ 30 (+36.36%)
Mutual labels:  regression, econometrics
Appelpy
Applied Econometrics Library for Python
Stars: ✭ 136 (+518.18%)
Mutual labels:  statistics, regression
Mlr
Machine Learning in R
Stars: ✭ 1,542 (+6909.09%)
Mutual labels:  statistics, regression
Sweetviz
Visualize and compare datasets, target values and associations, with one line of code.
Stars: ✭ 1,851 (+8313.64%)
Mutual labels:  statistics, pandas
econtools
Econometrics and data manipulation functions.
Stars: ✭ 96 (+336.36%)
Mutual labels:  regression, econometrics
Choochoo
Training Diary
Stars: ✭ 186 (+745.45%)
Mutual labels:  statistics, pandas
Fecon236
Tools for financial economics. Curated wrapper over Python ecosystem. Source code for fecon235 Jupyter notebooks.
Stars: ✭ 72 (+227.27%)
Mutual labels:  statistics, pandas
Openml R
R package to interface with OpenML
Stars: ✭ 81 (+268.18%)
Mutual labels:  statistics, regression
Morpheus Core
The foundational library of the Morpheus data science framework
Stars: ✭ 203 (+822.73%)
Mutual labels:  statistics, regression
FixedEffectjlr
R interface for Fixed Effect Models
Stars: ✭ 20 (-9.09%)
Mutual labels:  regression, econometrics
View All Similar Projects ➔

This package contains functionality useful for econometric work with panel data. Its name, originally standing for "high-dimensional fixed effects," is now misleading.

Useful features are

  • Groupby: A class allowing for fast operations similar to Pandas groupby-apply and groupby-transform functionality, but performing significantly faster with user-written functions. See documentation here.
  • find_collinear_cols and remove_collinear_cols: Functions for dealing with multicollinearity which operate quickly on CSC matrices.
  • make_lags: Makes within-group lags (frequently useful with panel data)

You can install hdfe through pip: "pip install hdfe"

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].