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LogConcDEAD (version 1.6-12)

Log-Concave Density Estimation in Arbitrary Dimensions

Description

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, ).

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Version

Install

install.packages('LogConcDEAD')

Monthly Downloads

465

Version

1.6-12

License

GPL (>= 2)

Maintainer

Yining Chen

Last Published

March 13th, 2025

Functions in LogConcDEAD (1.6-12)

Sample from a log-concave maximum likelihood estimate

A GUI for classification in two dimensions using smoothed log-concave

print.LogConcDEAD

Summarizing log-concave maximum likelihood estimator

Finds marginals of multivariate logconcave maximum likelihood estimators by integrating

plot.LogConcDEAD

Plot a log-concave maximum likelihood estimator

Compute the maximum likelihood estimator of a log-concave density

Construct an object of class LogConcDEAD

Sample from a smoothed log-concave maximum likelihood estimate

Find appropriate weights for likelihood calculations

Evaluate the log-concave maximum likelihood estimator of 2-d data on a grid for plotting

Compute the smoothing matrix of the smoothed log-concave maximum likelihood estimator

cov.LogConcDEAD

Compute the covariance matrix of a log-concave maximum likelihood estimator

LogConcDEAD-package

Computes a log-concave (maximum likelihood) estimator for i.i.d. data in any number of dimensions

Evaluation of a smoothed log-concave maximum likelihood estimator at given points

Evaluation of a log-concave maximum likelihood estimator at a point

Evaluate the marginal of multivariate log-concave maximum likelihood estimators at a point

Estimate the mixture proportions and component densities using EM algorithm

LogConcDEAD-internal

Internal log-concave maximum likelihood estimation functions