Package: lspartition
Type: Package
Title: Nonparametric Estimation and Inference Procedures using
        Partitioning-Based Least Squares Regression
Version: 0.5
Date: 2025-04-29
Authors@R: c(person(given = c("Matias", "D."),
                    family = "Cattaneo",
                    role = "aut"),
             person(given = c("Max", "H."),
                    family = "Farrell",
                    role = "aut"),
             person(given = "Yingjie",
                    family = "Feng",
                    role = c("aut", "cre"),
                    email = "fengyingjiepku@gmail.com"))
Description: Tools for statistical analysis using partitioning-based
        least squares regression as described in Cattaneo, Farrell and
        Feng (2020a, <doi:10.48550/arXiv.1804.04916>) and Cattaneo,
        Farrell and Feng (2020b, <doi:10.48550/arXiv.1906.00202>):
        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.
Depends: R (>= 3.1)
License: GPL-2
Encoding: UTF-8
Imports: ggplot2, pracma, mgcv, combinat, matrixStats, MASS, dplyr
RoxygenNote: 7.3.1
NeedsCompilation: no
Packaged: 2026-10-21 09:58:20 UTC; root
Author: Matias D. Cattaneo [aut], Max H. Farrell [aut], Yingjie Feng
        [aut, cre]
Maintainer: Yingjie Feng <fengyingjiepku@gmail.com>
Repository: https://yingjieum.r-universe.dev
Date/Publication: 2025-04-29 10:30:06 UTC
RemoteUrl: https://github.com/cran/lspartition
RemoteRef: HEAD
RemoteSha: 1c3142028e808bbb5fb4e38febef5e1e1fdf8d4c