Monte Carlo Method for Approximating Integrals and Expected Values of Random Variables
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In this mathematics and statistics tutorial, we explain one very important technique for approximating expectations and integrals of functions. This technique is based on the Monte Carlo Method. It is used in a large number of applications, such as simulation of random processes, state estimation of dynamical systems, machine learning, etc. For us, the most interesting application is state estimation of dynamical systems by using particle filters. Namely, the Monte Carlo method is the basis for the importance sampling method that serves as the basis of particle filters. We will cover the importance sampling methods and particle filters in our future tutorials. In this tutorial, all the theoretical concepts are illustrated by using Python examples.
Watch video Monte Carlo Method for Approximating Integrals and Expected Values of Random Variables online, duration hours minute second in high quality that is uploaded to the channel Aleksandar Haber PhD 21 December 2023. Share the link to the video on social media so that your subscribers and friends will also watch this video. This video clip has been viewed 313 times and liked it 14 visitors.
