Linear Models
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Linear (regression) models for Python. Extends statsmodels with Panel regression, instrumental variable estimators, system estimators and models for estimating asset prices:
-
Panel models:
- Fixed effects (maximum two-way)
- Random effects
- First difference regression
- Between estimator for panel data
- Pooled regression for panel data
- Fama-MacBeth estimation of panel models
- Specification tests: the Hausman test of random effects against fixed effects and the Pesaran CD test of cross-sectional dependence
-
High-dimensional Regression:
- Absorbing Least Squares
-
Instrumental Variable estimators
- Two-stage Least Squares
- Limited Information Maximum Likelihood
- k-class Estimators
- Generalized Method of Moments, also with continuously updating
- Jackknife IV (JIVE)
- Specification tests: the Cragg-Donald and Kleibergen-Paap rank tests of the first stage (underidentification)
-
Factor Asset Pricing Models:
- 2- and 3-step estimation
- Time-series estimation
- GMM estimation
-
System Regression:
- Seemingly Unrelated Regression (SUR/SURE)
- Three-Stage Least Squares (3SLS)
- Generalized Method of Moments (GMM) System Estimation
Designed to work equally well with NumPy, Pandas or xarray data.
Panel models
Like statsmodels to include, supports formulas for specifying models. For example, the classic Grunfeld regression can be specified
import numpy as np
from statsmodels.datasets import grunfeld
data = grunfeld.load_pandas().data
data.year = data.year.astype(np.int64)
# MultiIndex, entity - time
data = data.set_index(['firm','year'])
from linearmodels import PanelOLS
mod = PanelOLS(data.invest, data[['value','capital']], entity_effects=True)
res = mod.fit(cov_type='clustered', cluster_entity=True)
Models can also be specified using the formula interface.
from linearmodels import PanelOLS
mod = PanelOLS.from_formula('invest ~ value + capital + EntityEffects', data)
res = mod.fit(cov_type='clustered', cluster_entity=True)
The formula interface for PanelOLS supports the special values
EntityEffects and TimeEffects which add entity (fixed) and time
effects, respectively.
Formula support comes from the formulaic package which is a replacement for patsy.
Instrumental Variable Models
IV regression models can be similarly specified.
import numpy as np
from linearmodels.iv import IV2SLS
from linearmodels.datasets import mroz
data = mroz.load()
mod = IV2SLS.from_formula('np.log(wage) ~ 1 + exper + exper ** 2 + [educ ~ motheduc + fatheduc]', data)
The expressions in the [ ] indicate endogenous regressors (before ~)
and the instruments.
Installation
The latest release can be installed using pip
pip install linearmodels
Binary wheels are available for Windows, macOS and Linux. Without a wheel, pip builds linearmodels from source, which requires a C compiler.
The main branch can be installed by cloning the repo and building it with pip. The build uses meson-python, and pip installs the other build requirements (Cython, NumPy and setuptools_scm) automatically.
git clone https://github.com/bashtage/linearmodels
cd linearmodels
pip install .
To work on linearmodels, install the requirements and then build an editable install
python -m pip install -r requirements.txt -r requirements-dev.txt
python -m pip install -e . --no-build-isolation
Documentation
Stable Documentation is built by GitHub Actions when a release is published. Development Documentation is built by the same workflow on every push to main.
Plan and status
- Linear Instrumental variable estimation - complete
- Linear Panel model estimation - complete
- Fama-MacBeth regression - complete
- Linear Factor Asset Pricing - complete
- System regression - complete
- Linear IV Panel model estimation - not started
- Dynamic Panel model estimation - not started
Requirements
linearmodels 7.1 is the last release that supports Python 3.10 and NumPy 1.x (NumPy < 2). Later releases will raise the minimum supported versions of Python, NumPy and the other dependencies.
Running
- Python 3.10+
- NumPy (1.23.5+)
- SciPy (1.8+)
- pandas (1.4+)
- statsmodels (0.14.6+)
- formulaic (1.2.1+)
- pyhdfe (0.2.0+)
- mypy_extensions (0.4+)
- packaging
- xarray (0.16+, optional)
Building from source
- A C compiler
- Cython (3.1.0+)
- meson-python
- NumPy (2.0+)
- setuptools_scm (9.2+)
Testing
- pytest (9.0+)
Documentation
- sphinx
- sphinx-immaterial
- nbsphinx
- nbconvert
- nbformat
- ipython
- jupyter
1 maintainer
Metadata
1 maintainer
Release files for linearmodels 7.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| linearmodels-7.1.tar.gz | 2.2 MB | Details |
Built distributions (wheels)
Total release size: 77.6 MB
Release files / linearmodels-7.1.tar.gz
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Release files / linearmodels-7.1-cp312-cp312-macosx_11_0_arm64.whl
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Release files / linearmodels-7.1-cp312-cp312-macosx_10_13_x86_64.whl
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Release files / linearmodels-7.1-cp311-cp311-win_amd64.whl
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Release files / linearmodels-7.1-cp311-cp311-musllinux_1_2_x86_64.whl
| Download URL | linearmodels-7.1-cp311-cp311-musllinux_1_2_x86_64.whl |
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Release files / linearmodels-7.1-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
| Download URL | linearmodels-7.1-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl |
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Release files / linearmodels-7.1-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl
| Download URL | linearmodels-7.1-cp311-cp311-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl |
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Release files / linearmodels-7.1-cp311-cp311-macosx_11_0_arm64.whl
| Download URL | linearmodels-7.1-cp311-cp311-macosx_11_0_arm64.whl |
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Release files / linearmodels-7.1-cp311-cp311-macosx_10_9_x86_64.whl
| Download URL | linearmodels-7.1-cp311-cp311-macosx_10_9_x86_64.whl |
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Release files / linearmodels-7.1-cp310-cp310-win_amd64.whl
| Download URL | linearmodels-7.1-cp310-cp310-win_amd64.whl |
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| Size | 2.1 MB |
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Release files / linearmodels-7.1-cp310-cp310-musllinux_1_2_x86_64.whl
| Download URL | linearmodels-7.1-cp310-cp310-musllinux_1_2_x86_64.whl |
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Release files / linearmodels-7.1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
| Download URL | linearmodels-7.1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl |
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Release files / linearmodels-7.1-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl
| Download URL | linearmodels-7.1-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl |
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Release files / linearmodels-7.1-cp310-cp310-macosx_11_0_arm64.whl
| Download URL | linearmodels-7.1-cp310-cp310-macosx_11_0_arm64.whl |
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| Size | 2.1 MB |
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Release files / linearmodels-7.1-cp310-cp310-macosx_10_9_x86_64.whl
| Download URL | linearmodels-7.1-cp310-cp310-macosx_10_9_x86_64.whl |
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| Size | 2.1 MB |
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