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 data, ...

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 ...

We propose a method for reconstructing a probability density function (pdf) from a sample of an n-dimensional probability distribution. The method works by iteratively applying some simple ...

In this paper, we consider the function f p ( t )= 2p X 2 ( 2p t+p;p ) , where χ²(x; n) defined by X 2 ( x;p )= 2 −p/2 Γ( p/2 ) e −x/2 x p/2−1 , is the density function of a χ²-distribution with n ...

This paper develops a new scheme for improving an approximation method of a probability density function, which is inspired by the idea in the Hilbert space projection theorem. Moreover, we apply ...

Our eLibrary offers over 25,000 IMF publications in multiple formats. Building on the widely-used double-lognormal approach by Bahra (1997), this paper presents a multi-lognormal approach with ...