Log-Concave Density Estimation in Arbitrary Dimensions

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Documentation for package ‘LogConcDEAD’ version 1.6-9

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

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