Assume \(\pmb{y}\), the response on \(P\) measured items, is centered multivariate Gaussian distributed with variance-covariance matrix \(\pmb{\Sigma}\):
\[ \pmb{y} \sim N_P\left( \pmb{0}, \pmb{\Sigma} \right) \]
- The goal is to find some model for \(\pmb{\Sigma}\) with positive degrees of freedom in which \(\pmb{\Sigma}\) closely resembles the observed variance-covariance matrix
- The number of parameters should be less than \(P(P+1)/2\)