Nonparametric Estimation and Inference Procedures using Partitioning-Based Least Squares Regression

Tools for statistical analysis using partitioning-based least squares regression as described in Cattaneo, Farrell and Feng (2018) . lsprobust() for nonparametric point estimation of regression functions and derivatives thereof, and for robust bias-corrected (pointwise and uniform) inference procedures. lspkselect() for data-driven procedure for selecting the IMSE-optimal number of knots. lsprobust.plot() for regression plots with robust confidence intervals and confidence bands. lsplincom() for estimation and inference for linear combinations of regression functions from different groups.


Reference manual

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0.2 by Yingjie Feng, 5 months ago

Browse source code at

Authors: Matias D. Cattaneo , Max H. Farrell , Yingjie Feng

Documentation:   PDF Manual  

GPL-2 license

Imports ggplot2, pracma, mgcv, combinat, matrixStats, MASS, dplyr

See at CRAN