EMmixlcd                Estimate the mixture proportions and component
                        densities using EM algorithm
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
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
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
