# Restricted Maximum Likelihood

Why don't we use restricted maximum likelihood to estimate parameters in non-mixed models?

• You use it: REML is for estimating variance parameters, and in non-mixed models there is only one such, $\sigma^2$. When dividing by $n-1$ to get a variance estimate, you are using REML. See stats.stackexchange.com/questions/48671/… – kjetil b halvorsen May 4 '15 at 17:02

For REML under fixed effects the variance estimator equivalent to $S^2=\frac{\sum_{i=1}^n (y_i - x_i \hat{\beta})^2}{n-p}$ where $\hat{\beta}$ is the OLS estimator, but as a bonus with OLS you also get to use Gauss-Markov Theorem for $\hat{\beta}$.