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BINSREG

The binsreg package provides tools for statistical analysis using the binscatter methods.

  • binsreg: implements binscatter least squares regression with robust inference and plots, including curve estimation, pointwise confidence intervals and uniform confidence band.
  • binsqreg: implements binscatter quantile regression with robust inference and plots, including curve estimation, pointwise confidence intervals and uniform confidence band.
  • binsglm: implements binscatter generalized linear regression with robust inference and plots, including curve estimation, pointwise confidence intervals and uniform confidence band.
  • binstest: implements binscatter-based hypothesis testing procedures for parametric specifications of and shape restrictions on the unknown function of interest.
  • binspwc: implements hypothesis testing procedures for pairwise group comparison of binscatter estimators.
  • binsregselect: implements data-driven number of bins selectors for binscatter implementation using either quantile-spaced or evenly-spaced binning/partitioning.

All the commands allow for covariate adjustment, smoothness restrictions, and clustering, among other features. See Cattaneo, Crump, Farrell and Feng (2024, 2025, 2026) for references.

Website: https://nppackages.github.io/.

Source code: https://github.com/nppackages/binsreg.

Authors

Matias D. Cattaneo (matias.d.cattaneo@gmail.com)

Richard K. Crump (richard.crump@gmail.com)

Max H. Farrell (mhfarrell@gmail.com)

Yingjie Feng (fengyingjiepku@gmail.com)

Ricardo Masini (ricardo.masini@gmail.com)

Installation

To install/update use pip

pip install binsreg

Usage

from binsreg import binsregselect, binsreg, binsqreg, binsglm, binstest, binspwc

Dependencies

  • numpy
  • pandas
  • scipy
  • statsmodels
  • plotnine

References

For overviews and introductions, see NP Packages website.

Software and Implementation

Technical and Methodological

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