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

Probability density function is a statistical expression defining the likelihood of a series of outcomes for a continuous variable, such as a stock or ETF return.

By using one of the common stock probability distribution methods of statistical calculations, an investor may determine the likelihood of profits from a holding.

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 ...

Probability density function (PDF) Original research An iterative copula method for probability density estimation This paper puts forward a technique with which to reconstruct a probability density ...

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 ...

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 ...