Package: ModEstM 0.0.1

ModEstM: Mode Estimation, Even in the Multimodal Case

Function ModEstM() is the only one of this package, it estimates the modes of an empirical univariate distribution. It relies on the stats::density() function, even for input control. Due to very good performance of the density estimation, computation time is not an issue. The multiple modes are handled using dplyr::group_by(). For conditions and rates of convergences, see Eddy (1980) <doi:10.1214/aos/1176345080>.

Authors:Jerome Collet [aut, cre]

ModEstM_0.0.1.tar.gz
ModEstM_0.0.1.zip(r-4.7)ModEstM_0.0.1.zip(r-4.6)ModEstM_0.0.1.zip(r-4.5)
ModEstM_0.0.1.tgz(r-4.6-any)ModEstM_0.0.1.tgz(r-4.5-any)
ModEstM_0.0.1.tar.gz(r-4.7-any)ModEstM_0.0.1.tar.gz(r-4.6-any)
ModEstM_0.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
ModEstM/json (API)

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

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 2 scripts 228 downloads 1 exports 15 dependencies

Last updated from:a748f0f3d5. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK110
source / vignettesOK148
linux-release-x86_64OK108
macos-release-arm64OK165
macos-oldrel-arm64OK141
windows-develOK65
windows-releaseOK72
windows-oldrelOK104
wasm-releaseOK87

Exports:ModEstM

Dependencies:clidplyrgenericsgluelifecyclemagrittrpillarpkgconfigR6rlangtibbletidyselectutf8vctrswithr