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.tar.gz(r-4.5-noble)wsbackfit_1.0-5.tar.gz(r-4.4-noble)
wsbackfit_1.0-5.tgz(r-4.4-emscripten)wsbackfit_1.0-5.tgz(r-4.3-emscripten)
wsbackfit.pdf |wsbackfit.html
wsbackfit/json (API)
NEWS

# Install 'wsbackfit' in R:
install.packages('wsbackfit', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • fortran– Runtime library for GNU Fortran applications
Datasets:
  • infect - Postoperative Infection Data.

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

7 exports 0.00 score 0 dependencies 11 scripts 215 downloads

Last updated 3 years agofrom:5ec463b506. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 25 2024
R-4.5-linux-x86_64OKAug 25 2024

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

Dependencies: