end{aligned} (3)We optimized the parameters (alpha) and (beta) to minimize the evaluation function (E_{m}).
By designing the objective function and determining the constraints, the optimization problem of minimizing the evaluation criteria function is solved.
Red line shows PM solution of the MCMC calculations; gray line shows the top 5% of solutions that minimize the evaluation function (Eq. 4).
We take possible candidate sets of the model parameters in order to minimize the evaluation function in Eq. 4, i.e., the probability distribution function of the posterior probability p(s|d; α ', β ', ν) in terms of the Bayesian estimation.
The model parameter (s), which minimizes the evaluation function in Eq. 4, is expected to be the best solution in terms of satisfying the reproducibility of the observation, the continuity of the slip with a discontinuous boundary, and the sparsity of a slip area.
In the depth profile in Fig. 4i, several solutions of the top 5% of solutions that minimize the evaluation function (Eq. 4) showed a few zero- and nearly-zero-slip subfaults within the coseismic slip area (gray lines in Fig. 4i).
Figure 4 shows the root-mean-square (RMS) errors (the square root of the average of the squared residuals between the true and estimated values) for the values of ϕ and α that minimize the evaluation function E for each iteration of the steepest descent method.
The retained values are α1 = 1, α2 = 0.1, β1 = 0.1, and β2 = 0.1, which are chosen to minimize the average evaluation errors for synthetic data.
Their approach minimized the distance between under evaluation and virtual DMUs.
To the extent possible, subjects were instructed to maintain the same dosages of established lipid-lowering agents throughout the double-blind treatment period to minimize confounding the evaluation of the lipid-lowering effects of colesevelam versus placebo.
