Sentence examples for quantitative estimator from inspiring English sources

K s ( c ) = K s + V ̄ r / τ a is proposed as a quantitative estimator of K m which is independent of patient weight, scan time, and scanner calibration.

We, therefore, believe it is worthwhile to investigate the potential suitability of K s ( c ) as a quantitative estimator (and not just a surrogate) of K m more thoroughly in future studies.

However, when the effect of negative selection is low compared to positive selection, the performance of the MK statistics as a quantitative estimator of the number of adaptive substitutions is determined by the extent of hitch-hiking and clonal interference.

The presence of residual disease in nonresected lymph nodes, which can be measured with a quantitative estimator denoted as the Maruyama index, is an independent prognostic factor in patients with gastric cancer [ 7– 9].

Systematic variations in the control points of these curves allows us to generate multiple realisations of geological interfaces, resulting in stochastic models that were grouped into suites used to apply quantitative estimators of uncertainty.

The score of a swelling contour on the first component was used as a quantitative shape estimator for each sexual swelling contour and averaged across pictures taken during the same cycle of the same female.

We design and analyze a qualitative estimator that estimates the distance of the ruling parameter from the unknown critical value at which the transition between the two behaviors happens without using any quantitative fitting of the measured data.

To determine what the club's winning percentage would have been with average luck, use two common quantitative tools: a run estimator and the Pythagorean equation.

The break down point is used to characterize quantitative robustness of an estimator.

Statistical techniques that have been developed to estimate quantitative genetic parameters, such as the animal model, calculate an unbiased estimator for the effects that genes have.

Elementary decision theory; loss and risk functions, Bayes estimation; UMVU estimator, minimax estimators, shrinkage estimators.