Lecture

Maximum Likelihood Estimation

Description

This lecture introduces maximum likelihood estimation, a method to estimate parameters by maximizing the probability that a model correctly predicts observations. The instructor explains how to calculate the likelihood function, the log likelihood, and the properties of maximum likelihood estimation. Through a simple example, the lecture demonstrates how to estimate parameters using this method and discusses the validity of the estimates through hypothesis testing.

Official source

https://mediaspace.epfl.ch/media/0_incadl1e

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Ontological neighbourhood

Statistics

Statistical inference: Mathematical statistics, Statistical hypothesis testing

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