Sigma_fun               Variance-covariance of sample central moments
                        (root-n approximation) given the vector mu with
                        the theoretical moments of order 1 to 8.
                        CAREFUL: the result must be divided by n (=
                        sample size)!
ddegross                Density function based on an object resulting
                        from the estimation procedure in degross.
degross                 Density estimation from tabulated data with
                        given frequencies and group central moments.
degross.object          Object resulting from the estimation of a
                        density from grouped (tabulated) summary
                        statistics
degrossData             Creates a degrossData.object from the observed
                        tabulated frequencies and central moments.
degrossData.object      Object generated from grouped summary
                        statistics, including tabulated frequencies and
                        central moments of order 1 up to 4, to estimate
                        the underlying density using 'degross'.
degross_lpost           Log-posterior (with gradient and Fisher
                        information) for given spline parameters, small
                        bin frequencies, tabulated sample moments and
                        roughness penalty parameter. This function is
                        maximized during the M-step of the EM algorithm
                        to estimate the B-spline parameters entering
                        the density specification.
degross_lpostBasic      Log-posterior for given spline parameters, big
                        bin (and optional: small bin) frequencies,
                        tabulated sample moments and roughness penalty
                        parameter. Compared to degross_lpost, no Fisher
                        information matrix is computed and the gradient
                        evaluation is optional, with a resulting
                        computational gain.
pdegross                Cumulative distribution function (cdf) based on
                        an object resulting from the estimation
                        procedure in degross.
plot.degross            Plot the density estimate obtained from grouped
                        summary statistics using degross and superpose
                        it to the observed histogram.
print.degross           Print a 'degross' object.
print.degrossData       Print a 'degrossData' object.
qdegross                Quantile function based on an object resulting
                        from the estimation procedure in degross.
simDegrossData          Simulation of grouped data and their sample
                        moments to illustrate the degross density
                        estimation procedure
