Package: sharpData 1.4

sharpData: Data Sharpening

Functions and data sets inspired by data sharpening - data perturbation to achieve improved performance in nonparametric estimation, as described in Choi, E., Hall, P. and Rousson, V. (2000). Capabilities for enhanced local linear regression function and derivative estimation are included, as well as an asymptotically correct iterated data sharpening estimator for any degree of local polynomial regression estimation. A cross-validation-based bandwidth selector is included which, in concert with the iterated sharpener, will often provide superior performance, according to a median integrated squared error criterion. Sample data sets are provided to illustrate function usage.

Authors:W. John Braun <[email protected]>

sharpData_1.4.tar.gz
sharpData_1.4.zip(r-4.7)sharpData_1.4.zip(r-4.6)sharpData_1.4.zip(r-4.5)
sharpData_1.4.tgz(r-4.6-x86_64)sharpData_1.4.tgz(r-4.6-arm64)sharpData_1.4.tgz(r-4.5-x86_64)sharpData_1.4.tgz(r-4.5-arm64)
sharpData_1.4.tar.gz(r-4.7-arm64)sharpData_1.4.tar.gz(r-4.7-x86_64)sharpData_1.4.tar.gz(r-4.6-arm64)sharpData_1.4.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html
card.svg |card.png
sharpData/json (API)

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

On CRAN:

Conda:

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

1.00 score 199 downloads 5 exports 2 dependencies

Last updated from:e0e336ee02. Checks:12 OK, 1 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK109
linux-devel-x86_64OK101
source / vignettesOK111
linux-release-arm64OK119
linux-release-x86_64OK94
macos-release-arm64OK92
macos-release-x86_64OK168
macos-oldrel-arm64OK85
macos-oldrel-x86_64OK347
windows-develOK89
windows-releaseOK109
windows-oldrelOK75
wasm-releaseFAIL95

Exports:CVsharpLLsharpenMonolpolyMonoMatsharpiteration

Dependencies:KernSmoothquadprog