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 ...

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, ...

Two estimates of the density function f(x, y) of points in a plane are defined from a sample of n points by (1) counting how many points lie within a square of side 2h and center at (x, y), and (2) by ...

The KDE procedure performs either univariate or bivariate kernel density estimation. Statistical density estimation involves approximating a hypothesized probability density function from observed ...

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 ...

Will Kenton is an expert on the economy and investing laws and regulations. He previously held senior editorial roles at Investopedia and Kapitall Wire and holds a MA in Economics from The New School ...