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LogConcDEAD (version 1.5-4)

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

1.5-4

License

LGPL

Maintainer

Yining Chen

Last Published

June 4th, 2011

Functions in LogConcDEAD (1.5-4)

LogConcDEAD-internal

Internal log-concave maximum likelihood estimation functions

interactive2D

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

mlelcd

Compute the maximum likelihood estimator of a log-concave density

dmarglcd

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

rslcd

Sample from a smoothed log-concave maximum likelihood estimate

dslcd

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

cov.LogConcDEAD

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

dlcd

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

rlcd

Sample from a log-concave maximum likelihood estimate

hatA

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

print.LogConcDEAD

Summarizing log-concave maximum likelihood estimator

getinfolcd

Construct an object of class LogConcDEAD

plot.LogConcDEAD

Plot 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

EMmixlcd

Estimate the mixture proportions and component densities using EM algorithm

interplcd

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

getweights

Find appropriate weights for likelihood calculations

interpmarglcd

Finds marginals of multivariate logconcave maximum likelihood estimators by integrating