Package: wsbackfit 1.0-5

Javier Roca-Pardinas

wsbackfit: Weighted Smooth Backfitting for Structured Models

Non- and semiparametric regression for generalized additive, partial linear, and varying coefficient models as well as their combinations via smoothed backfitting. Based on Roca-Pardinas J and Sperlich S (2010) <doi:10.1007/s11222-009-9130-2>; Mammen E, Linton O and Nielsen J (1999) <doi:10.1214/aos/1017939138>; Lee YK, Mammen E, Park BU (2012) <doi:10.1214/12-AOS1026>.

Authors:Javier Roca-Pardinas [aut, cre], Maria Xose Rodriguez-Alvarez [aut], Stefan Sperlich [aut], Alan Miller [ctb]

wsbackfit_1.0-5.tar.gz
wsbackfit_1.0-5.zip(r-4.7-x86_64)wsbackfit_1.0-5.zip(r-4.7-arm64)wsbackfit_1.0-5.zip(r-4.6-x86_64)wsbackfit_1.0-5.zip(r-4.6-arm64)
wsbackfit_1.0-5.tar.gz(r-4.7-arm64)wsbackfit_1.0-5.tar.gz(r-4.7-x86_64)wsbackfit_1.0-5.tar.gz(r-4.6-arm64)wsbackfit_1.0-5.tar.gz(r-4.6-x86_64)
wsbackfit_1.0-5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
wsbackfit/json (API)

# Install 'wsbackfit' in R:
install.packages('wsbackfit', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • fortran– Runtime library for GNU Fortran applications
Datasets:
  • infect - Postoperative Infection Data.

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

fortran

1.04 score 11 scripts 220 downloads 7 exports 0 dependencies

Last updated from:5ec463b506. Checks:9 OK, 1 WARNING. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK77
linux-devel-x86_64OK104
source / vignettesOK169
linux-release-arm64OK72
linux-release-x86_64OK92
windows-devel-arm64OK173
windows-devel-x86_64OK110
windows-release-arm64WARNING212
windows-release-x86_64OK67
wasm-releaseOK68

Exports:plot.sbackpredict.sbackprint.sbackresiduals.sbacksbsbacksummary.sback

Dependencies: