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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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Install
install.packages('LogConcDEAD')
Monthly Downloads
587
Version
1.5-8
License
GPL (>= 2)
Maintainer
Yining Chen
Last Published
November 27th, 2013
Functions in LogConcDEAD (1.5-8)
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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