Package: rmargint 2.0.3

rmargint: Robust Marginal Integration Procedures

Three robust marginal integration procedures for additive models based on local polynomial kernel smoothers. As a preliminary estimator of the multivariate function for the marginal integration procedure, a first approach uses local constant M-estimators, a second one uses local polynomials of order 1 over all the components of covariates, and the third one uses M-estimators based on local polynomials but only in the direction of interest. For this last approach, estimators of the derivatives of the additive functions can be obtained. All three procedures can compute predictions for points outside the training set if desired. See Boente and Martinez (2017) <doi:10.1007/s11749-016-0508-0> for details.

Authors:Alejandra Martinez [aut, cre], Matias Salibian-Barrera [aut]

rmargint_2.0.3.tar.gz
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rmargint_2.0.3.tgz(r-4.6-x86_64)rmargint_2.0.3.tgz(r-4.6-arm64)rmargint_2.0.3.tgz(r-4.5-x86_64)rmargint_2.0.3.tgz(r-4.5-arm64)
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rmargint_2.0.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
rmargint/json (API)

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

Bug tracker:https://github.com/alemermartinez/rmargint/issues

On CRAN:

Conda:

2.70 score 140 downloads 10 exports 0 dependencies

Last updated from:749f936599. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK132
linux-devel-x86_64OK110
source / vignettesOK169
linux-release-arm64OK129
linux-release-x86_64OK108
macos-release-arm64OK135
macos-release-x86_64OK227
macos-oldrel-arm64OK141
macos-oldrel-x86_64OK283
windows-develOK90
windows-releaseOK77
windows-oldrelOK86
wasm-releaseOK94

Exports:k.epankernel10kernel4kernel6kernel8margint.clmargint.robmy.norm.2psi.huberpsi.tukey

Dependencies: