 Minimum sum of errors in a simple hypothesis test

For two simple hypotheses with probability densities $f_0,f_1$, a critical region $C$ has sum of Type I error and Type II error probabilities ${\int }_C{f}_0+{\int }_{C^c}{f}_1$. Pointwise minimization chooses $C=\{f_1>f_0\}$, with either decision allowed on the equality set. Thus the optimal likelihood ratio threshold is $1$, and the minimum is $\int \min (f_0,f_1)=1-\frac{1}{2}\int |f_1-f_0|$. This criterion weights the two error probabilities equally; unequal costs or prior probabilities change the threshold.