It relates to probability density functions by explaining how the distribution of these averages or sums tends to approach a specific shape: the normal distribution (bell curve).

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, ...

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.

The notion of probability density for a random function is not as straight-forward as in finite-dimensional cases. While a probability density function generally does not exist for functional data, we ...