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 \(\sigma^2\).