The phrase "admissible error" is correct and usable in written English.
It can be used in contexts such as legal discussions, academic evaluations, or any situation where a mistake is recognized but does not invalidate the overall outcome.
Example: "The judge ruled that the discrepancy in the evidence was an admissible error and did not affect the verdict."
Alternatives: "acceptable mistake" or "permissible error".
Results for low to high cycle fatigue help to obtain design fatigue probability curves or the necessary number of tests for a given admissible error.
In the case of treated patients, working with a sample of 2606 patients afforded us a maximum admissible error of 1 = ±1.98% for sensitivity (70%) and δ2 = ±3.82% for specificity (70%).
In the case of untreated patients, working with a sample of 1968 patients afforded us a maximum admissible error of δ1 = ±2.28 percentage units for sensitivity (70%) and δ2 = ±4.4 percentage units for specificity (70%).
Assuming that, once the optimal point has been chosen, both scales have an S ≥ 70% and an Sp ≥ 70%, and that there would be no differences between patients on and those not on PPI treatment, then, based on a sample of 5621 patients, the sensitivity and specificity of each test could be estimated with a maximum admissible error of δ1 = ±1.35% and δ2 = ±2.60% respectively.
In this paper, we discuss the portfolio selection problem with transaction costs under the assumption that there exist admissible errors on expected returns and risks of assets.
This means that we can approximate the set { H ~ : J ( H ~, H ) ≤ 1 / γ } of all admissible estimation errors H ~ by a (complex) ellipsoid in the parameter space [15]: D adm = { H ~ : vec H ( H ~ ) γ I adm vec ( H ~ ) ≤ 1 }.
The proposed control scheme is the first work on extension to MIMO second-order hyperbolic distributed parameter systems with admissible initial state error.
Observer performance is shown to be high with a mean absolute final carbon content estimation error for admissible heats equal to 0.0012%.
The purpose is to design a mode-dependent linear filtering which ensures that, for all admissible uncertainties, the filtering error system is not only stochastically asymptotically stable in the large, but also satisfies a prescribed H∞-norm level.
We aim to design a non-fragile state estimator such that, in the presence of all admissible gain variations, the estimation error converges to zero exponentially.
Based on this condition, a sufficient LMI-based condition for the existence of the desired H∞ full-order filter is derived to guarantee that the filtering error system is admissible while satisfying a given H∞ performance index.
