LSPARTITION

The lspartition package provides an R implementation of tuning parameter selection, point estimation, and pointwise and uniform inference procedures for partitioning-based least squares series estimators, including B-splines, wavelets, and piecewise polynomial regression estimators.

This work was supported in part by the National Science Foundation through grant SES-1459931.

Queries and Requests

Please email: lspartition@googlegroups.com

R Implementation

To install/update in R type:

install.packages('lspartition')

• Help: R Manual, CRAN repository.

• Replication: R-script, data.

Repository

For source code and related files, visit lspartition repository.

References

Software and Implementation

• Cattaneo, Farrell and Feng (2020): lspartition: Partitioning-Based Least Squares Regression.
  R Journal 12(1): 172-187.

Technical and Methodological

• Cattaneo and Farrell (2013): Optimal Convergence Rates, Bahadur Representation, and Asymptotic Normality of Partitioning Estimators.
  Journal of Econometrics 174(2): 127-143.
  Supplemental Appendix.

• Cattaneo, Farrell and Feng (2020): Large Sample Properties of Partitioning-Based Series Estimators.
  Annals of Statistics 48(3): 1718-1741.
  Supplemental Appendix.