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LogConcDEAD (version 1.5-8)

Log-concave Density Estimation in Arbitrary Dimensions

Description

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

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Version

Install

install.packages('LogConcDEAD')

Monthly Downloads

247

Version

1.5-8

License

GPL (>= 2)

Maintainer

Yining Chen

Last Published

November 27th, 2013

Functions in LogConcDEAD (1.5-8)

LogConcDEAD-internal

Internal log-concave maximum likelihood estimation functions

mlelcd

Compute the maximum likelihood estimator of a log-concave density

rslcd

Sample from a smoothed log-concave maximum likelihood estimate

LogConcDEAD-package

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

getweights

Find appropriate weights for likelihood calculations

EMmixlcd

Estimate the mixture proportions and component densities using EM algorithm

rlcd

Sample from a log-concave maximum likelihood estimate

getinfolcd

Construct an object of class LogConcDEAD

interplcd

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

dslcd

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

dmarglcd

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

interpmarglcd

Finds marginals of multivariate logconcave maximum likelihood estimators by integrating

interactive2D

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

cov.LogConcDEAD

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

print.LogConcDEAD

Summarizing log-concave maximum likelihood estimator

plot.LogConcDEAD

Plot a log-concave maximum likelihood estimator

hatA

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

dlcd

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