Package: PDFEstimator 4.5

PDFEstimator: Multivariate Nonparametric Probability Density Estimator

Farmer, J., D. Jacobs (2108) <doi:10.1371/journal.pone.0196937>. A multivariate nonparametric density estimator based on the maximum-entropy method. Accurately predicts a probability density function (PDF) for random data using a novel iterative scoring function to determine the best fit without overfitting to the sample.

Authors:Jenny Farmer <[email protected]> and Donald Jacobs <[email protected]>

PDFEstimator_4.5.tar.gz
PDFEstimator_4.5.zip(r-4.7)PDFEstimator_4.5.zip(r-4.6)PDFEstimator_4.5.zip(r-4.5)
PDFEstimator_4.5.tgz(r-4.6-x86_64)PDFEstimator_4.5.tgz(r-4.6-arm64)PDFEstimator_4.5.tgz(r-4.5-x86_64)PDFEstimator_4.5.tgz(r-4.5-arm64)
PDFEstimator_4.5.tar.gz(r-4.7-arm64)PDFEstimator_4.5.tar.gz(r-4.7-x86_64)PDFEstimator_4.5.tar.gz(r-4.6-arm64)PDFEstimator_4.5.tar.gz(r-4.6-x86_64)
PDFEstimator_4.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
PDFEstimator/json (API)

# Install 'PDFEstimator' in R:
install.packages('PDFEstimator', repos = c('https://jennyfarmer.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

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

cpp

1.00 score 2 scripts 212 downloads 8 exports 3 dependencies

Last updated from:19e26609a3. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK114
linux-devel-x86_64OK144
source / vignettesOK166
linux-release-arm64OK124
linux-release-x86_64OK114
macos-release-arm64OK137
macos-release-x86_64OK427
macos-oldrel-arm64OK162
macos-oldrel-x86_64OK275
windows-develOK120
windows-releaseOK106
windows-oldrelOK118
wasm-releaseOK111

Exports:approximatePointsconvertToPDFeestimatePDFestimatePDFmvgetTargetplot2dplot3dplotBeta

Dependencies:misc3dMultiRNGplot3D