Vector of independent and identically distributed numbers, not necessarily unique.

Parameter that governs the generation of weights: If xgrid = NULL a new sample of unique observations is generated with corresponding vector of weights. If xgrid is a positive number, observations are binned in a grid with grid length xgrid. Finally, an entire vector specifying a user-defined grid can be supplied.

Vector of unique and sorted observations deduced from the input x according to the specification given by xgrid.

Vector of corresponding weights, normalized to sum to one.

Standard deviation of the inputed observations. This quantity is needed when computing the smoothed log-concave density estimator via evaluateLogConDens.

Number of initial observations.