We develop an estimation procedure for a discrete probability mass function (pmf) with unknown support. We derive its maximum likelihood estimator under the mild and natural shape-constraint of ...

Nonparametric methods provide a flexible framework for estimating the probability density function of random variables without imposing a strict parametric model. By relying directly on observed ...

Advances in Applied Probability, Vol. 19, No. 3 (Sep., 1987), pp. 632-651 (20 pages) We consider a class of functions on [0,∞), denoted by Ω , having Laplace transforms with only negative zeros and ...

Building on the widely-used double-lognormal approach by Bahra (1997), this paper presents a multi-lognormal approach with restrictions to extract risk-neutral probability density functions (RNPs) for ...