Kernel Density Estimation: Non-parametrically estimating the probability density function from data using kernel functions, enabling flexible adaptation to complex distributions.

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, ...

B. W. Silverman, On the Estimation of a Probability Density Function by the Maximum Penalized Likelihood Method, The Annals of Statistics, Vol. 10, No. 3 (Sep., 1982), pp. 795-810 ...