linearmodels 1.0

Instrumental Variable and Linear Panel models for Python

One

Linear Models

Linear (regression) models for Python. Extends statsmodels to include instrumental variable estimators:

• Two-stage Least Squares

• Limited Information Maximum Likelihood

• k-class Estimators

• Generalized Method of Moments, also with continuously updating

Designed to work equally well with NumPy, Pandas or xarray data.

Like statsmodels to include, supports patsy formulas for specifying models. For example,

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.

Installing

The latest release can be installed using pip

pip install linearmodels

The master branch can be installed by cloning the repo and running setup

git clone https://github.com/bashtage/linearmodels
cd linearmodels
python setup.py install

Documentation

Documentation is automatically built using doctr on every successful build of master. The documentation is still rough but should improve quickly.

Plan and status

Should eventually add some useful linear model estimators such as panel regression. Currently only the single variable IV estimators are polished.

• Linear Instrumental variable estimation - complete

• Linear Panel model estimation - incomplete

• Linear IV Panel model estimation - not started

• System regression - not started

Requirements

Running

With the exception of Python 3.5+, 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.

• Python 3.5+: extensive use of @ operator

• NumPy (1.11+)

• SciPy (0.17+)

• Pandas (0.19+)

• xarray (0.9+)

• Statsmodels (0.8+)

Testing

• py.test

Documentation

• sphinx

• sphinx_rtd_theme

• nbsphinx

• nbconvert

• nbformat

• ipython

• jupyter