Maximum Likelihood

In Statistical Inference, you met the method of Maximum Likelihood Estimation (MLE). This approach can also be used to fit a Linear Model, i.e. to estimate the model parameters in:

$$Y_i = f(x_i,\boldsymbol{\beta} ) + \epsilon_i$$ where $f(x_i,\boldsymbol{\beta} )$ is a linear function of $\boldsymbol{\beta}$ and we assume the $\epsilon_ i$ are Normally distributed with mean 0 and variance $\sigma^2$.