• K-component Mixture Model:
  Random variables distributed according to a mixture of K components with each component belonging to the same parametric family of distributions (e.g., all normal, all Zipfian, etc.) but with different parameters

• Two terms Gaussian model fit: f(s)=a_{1}\exp\left[-\frac{(s-b_{1})^2}{\sigma^2_{1}}\right]+a_{2}\exp\left[-\frac{(s-b_{2})^2}{\sigma^2_{2}}\right]