O'Reilly logo

IPython Interactive Computing and Visualization Cookbook - Second Edition by Cyrille Rossant

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

Estimating a probability distribution nonparametrically with a kernel density estimation

In the previous recipe, we applied a parametric estimation method. We had a statistical model (the exponential distribution) describing our data, and we estimated a single parameter (the rate of the distribution). Nonparametric estimation deals with statistical models that do not belong to a known family of distributions. The parameter space is then infinite-dimensional instead of finite-dimensional (that is, we estimate functions rather than numbers).

Here, we use a Kernel Density Estimation (KDE) to estimate the density of probability of a spatial distribution. We look at the geographical locations of tropical cyclones from 1848 to 2013, based on data provided ...

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required