This package is considered a duplicate. The official version of this package is found at:https://ychen101.r-universe.dev/LogConcDEAD

Package: LogConcDEAD 1.6-12

Yining Chen

LogConcDEAD: Log-Concave Density Estimation in Arbitrary Dimensions

Software for computing a log-concave (maximum likelihood) estimator for independent and identically distributed data in any number of dimensions. For a detailed description of the method see Cule, Samworth and Stewart (2010, Journal of Royal Statistical Society Series B, <doi:10.1111/j.1467-9868.2010.00753.x>).

Authors:Madeleine Cule [aut], Robert Gramacy [aut], Richard Samworth [aut], Yining Chen [aut, cre], Lutz Duembgen [ctb], Vikneswaran Gopal [ctb], George Casella [ctb], C. Bradford Barber [cph], The Geometry Center [cph], Kai Habel [cph], Raoul Grasman [cph], Alexei Kuntsevich [cph], Franz Kappel [cph]

LogConcDEAD_1.6-12.tar.gz
LogConcDEAD_1.6-12.tar.gz(r-4.7-arm64)LogConcDEAD_1.6-12.tar.gz(r-4.7-x86_64)LogConcDEAD_1.6-12.tar.gz(r-4.6-arm64)LogConcDEAD_1.6-12.tar.gz(r-4.6-x86_64)
LogConcDEAD_1.6-12.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
LogConcDEAD/json (API)
NEWS

# Install 'LogConcDEAD' in R:

install.packages('LogConcDEAD', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Uses libs:

openblas– Optimized BLAS

On CRAN:

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

openblas

2.84 score 1 packages 23 scripts 295 downloads 14 exports 3 dependencies

Last updated from:ad8be88ffc. Checks:4 NOTE, 2 OK. Indexed: no.

Target	Result	Time
linux-devel-arm64	NOTE	163
linux-devel-x86_64	NOTE	132
source / vignettes	OK	222
linux-release-arm64	NOTE	123
linux-release-x86_64	NOTE	123
wasm-release	OK	99

Exports:cov.LogConcDEAD dlcd dmarglcd dslcd EMmixlcd getinfolcd getweights hatA interactive2D interplcd interpmarglcd mlelcd rlcd rslcd

Dependencies:MASS mclust mvtnorm

a guide to the LogConcDEAD package

Rendered fromLogConcDEAD.Rnwusingutils::Sweaveon May 25 2026.

Last update: 2023-04-05
Started: 2013-07-12

Help page	Topics
Computes a log-concave (maximum likelihood) estimator for i.i.d. data in any number of dimensions	LogConcDEAD-package LogConcDEAD
Compute the covariance matrix of a log-concave maximum likelihood estimator	cov.LogConcDEAD
Evaluation of a log-concave maximum likelihood estimator at a point	dlcd
Evaluate the marginal of multivariate log-concave maximum likelihood estimators at a point	dmarglcd
Evaluation of a smoothed log-concave maximum likelihood estimator at given points	dslcd
Estimate the mixture proportions and component densities using EM algorithm	EMmixlcd
Construct an object of class LogConcDEAD	getinfolcd
Find appropriate weights for likelihood calculations	getweights
Compute the smoothing matrix of the smoothed log-concave maximum likelihood estimator	hatA
A GUI for classification in two dimensions using smoothed log-concave	interactive2D
Evaluate the log-concave maximum likelihood estimator of 2-d data on a grid for plotting	interplcd
Finds marginals of multivariate logconcave maximum likelihood estimators by integrating	interpmarglcd
Compute the maximum likelihood estimator of a log-concave density	mlelcd
Plot a log-concave maximum likelihood estimator	plot.LogConcDEAD
Summarizing log-concave maximum likelihood estimator	print.LogConcDEAD summary.LogConcDEAD
Sample from a log-concave maximum likelihood estimate	rlcd
Sample from a smoothed log-concave maximum likelihood estimate	rslcd

Package: LogConcDEAD 1.6-12

LogConcDEAD: Log-Concave Density Estimation in Arbitrary Dimensions

a guide to the LogConcDEAD package

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)