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

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 simple transformations ...

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 ...

Nonparametric estimation of probability density functions, both marginal and joint densities, is a very useful tool in statistics. The kernel method is popular and applicable to dependent data, ...

In many experimental observation systems where the goal is to record a three-dimensional observation of an object, or a set of objects, a lower-dimensional projection of the intended subject is ...