A probability density function (PDF) describes the likelihood of different outcomes for a continuous random variable.

Estimation of a Probability Density Function and Its Derivatives Let X 1, X 2, ⋯ be independent identically distributed random variables having a common probability density function f.

Ushio Sumita, Yasushi Masuda, Classes of Probability Density Functions Having Laplace Transforms with Negative Zeros and Poles, Advances in Applied Probability, Vol. 19, No. 3 (Sep., 1987), pp.

In this paper, we propose a functional linear regression model in the space of probability density functions. We treat a cross-sectional distribution of individual earnings as an infinite dimensional ...

Nonparametric method for multivariate density estimation using neural networks In this paper, a parameter-free method is proposed to determine the probability density function of multi-dimensional ...

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 ...