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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:
High-dimensional Regresssion:
Instrumental Variable estimators
Factor Asset Pricing Models:
System Regression:
Designed to work equally well with NumPy, Pandas or xarray data.
Like statsmodels to include, supports patsy 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.
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.
The latest release can be installed using pip
pip install linearmodels
The main branch can be installed by cloning the repo and running setup
git clone https://github.com/bashtage/linearmodels
cd linearmodels
python setup.py install
Stable Documentation is built on every tagged version using doctr. Development Documentation is automatically built on every successful build of main.
Should eventually add some useful linear model estimators such as panel regression. Currently only the single variable IV estimators are polished.
With the exception of Python 3 (3.7+ tested), which is a hard requirement, the others are the version that are being used in the test environment. It is possible that older versions work.