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The estimation of the optimal transformation is modelled either as a combinatorial or a numerical optimization problem.
Mathematical statistics was applied in the estimation of the optimal process conditions.
A nonparametric estimation of the optimal importance sampling density is then obtained using the MEDE technique.
A Monte Carlo method for estimation of the optimal design of a nonlinear parametric regression problem is presented.
The approximate solutions obtained from the design of flow passages are an excellent estimation of the optimal solutions.
In some commonly used longitudinal clinical trials designs, the quadratic inference functions (QIF) method fails to work due to non-invertible estimation of the optimal weighting matrix.
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The estimations of the optimal error rate are shown in Section 4.
Fig. 12 Convergence performance of DSPSA: J(ϕ (n)), the value of the objective function at the nth iteration of DSPSA (left); (phi _{1}^{(n)}(1,6,4)), the estimations of the optimal threshold to queue 1 when b 2=1, g 1=6 and g 2=4 (right).
A planned blinded re-estimation of the optimal sample size was done by an appointed independent person after 55 patients had completed the study, the variability for the primary efficacy measure was estimated using their data, and the sample size was increased to 170 patients.
The two-part decomposition is used in the estimation process of the optimal reception filter.
An estimation of the unknowns optimal in the least square sense was obtained by pseudoinverting the rectangular matrix containing the conditions (11) for each considered pair of maps.
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