🍿 Kernel Density Estimation

Kernel density estimation constructs an estimate of a distribution given only samples . We essentially make a smoothed-out histogram of the samples using a kernel. Formally, our estimate

where is a bandwidth parameter that controls how smooth our estimate is. For our estimate to be a valid, the function chosen as our kernel must satisfy the following:

1. Normalization: .
2. Symmetry: .