Machine Learning, Signal Processing, Bayesian Statistics, Editors Pick, Getting Started.
Likelihood (ML) Estimation ML estimation tries to find the estimate of the parameter θ by maximizing the likelihood function. Assume we have i.i.d random samples x₁,x₂, . . .,xₙ that follow a distribution f(x₁,x₂, . . .,xₙ;θ), which depends on the unknown parameter θ. The goal is to estimate this