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$\sigma^{2(t+1)}_{1} = \frac{\sum\limits_{i=1}^n T^{(t)}_{1,i}(x_i-\mu^{(t+1)}_{1})^2}{\sum\limits_{i=1}^n T^{(t)}_{1,i}}$  Initial guess:  1. Assume that $\textbf{x} \sim N(\mu, \sigma^2)$ (unimodal). Calculate $\mu$ and $\sigma^2$  2. Assume that $\textbf{x} \sim N(\mu_1, \mu_2, \sigma^2_1, \sigma^2_2, p)$ (bimodal)  Initial guess: $\mu_1 = \mu - \sigma, \mu_2 = \mu + \sigma, \sigma^2_1 = \sigma^2_2 = \sigma^2, p = 0.5$  Continue iterations t until $|\log L^{(t+1)} - \ log \log  L^{(t)}| < 10^{-3}$ \subsection{Excess-mass method (EMM)} \label{sec:methods-emm}