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 (2019a, ) and Cattaneo, Farrell and Feng (2019b, ): lsprobust() for nonparametric point estimation of regression functions and their derivatives and for robust bias-corrected (pointwise and uniform) inference; lspkselect() for data-driven selection of 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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0.4 by Yingjie Feng, a year 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