sm: Smoothing Methods for Nonparametric Regression and Density Estimation

This is software linked to the book 'Applied Smoothing Techniques for Data Analysis - The Kernel Approach with S-Plus Illustrations' Oxford University Press.

Version: 2.2-6.0
Depends: R (≥ 3.1.0)
Suggests: rgl, misc3d, interp, gam, tkrplot, rpanel (≥ 1.1-4), tcltk
Published: 2024-02-17
DOI: 10.32614/
Author: Adrian Bowman and Adelchi Azzalini. Ported to R by B. D. Ripley up to version 2.0, version 2.1 by Adrian Bowman and Adelchi Azzalini, version 2.2 by Adrian Bowman.
Maintainer: Adrian Bowman <adrian.bowman at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: sm citation info
Materials: NEWS ChangeLog
CRAN checks: sm results


Reference manual: sm.pdf


Package source: sm_2.2-6.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): sm_2.2-6.0.tgz, r-oldrel (arm64): sm_2.2-6.0.tgz, r-release (x86_64): sm_2.2-6.0.tgz, r-oldrel (x86_64): sm_2.2-6.0.tgz
Old sources: sm archive

Reverse dependencies:

Reverse depends: compcodeR, irtoys, vioplot
Reverse imports: bite, brinton, clustComp, consICA, DepthProc, GWSDAT, magicaxis, mem, MuViCP, otinference, regplot, spef, wxgenR
Reverse suggests: kedd, npsm, rpanel, Sim.DiffProc, sirt, spatstat.explore, spatstat.model, tsDyn, wrGraph, wrProteo
Reverse enhances: sfsmisc


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