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Optimal sample sizes for constructing tolerance limits are determined by minimizing appropriate cost functions.
A Bayesian approach for constructing tolerance limits is also proposed, which may be viewed as a generalization of the frequentist viewpoint since classical and Bayesian perspectives harmonize in the noninformative case.
The appropriate sample size for constructing tolerance intervals is also affected by the assumed underlying distribution of the data from which it is calculated.
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In this paper, we construct tolerance intervals based on the expensive measurements that are obtained using randomized nomination sampling (RNS) with the help of inexpensive auxiliary information.
Minimum and expected percentages of conforming systems are assessed by constructing suitable tolerance limits.
Moreover, Lachhwani and Poonia (2012) proposed fuzzy goal programming approach for multi-level linear fractional programming problem by constructing a tolerance membership functions for the fuzzily described numerator and denominator part of the objective functions of all levels.
To assess each construct's tolerance to DTT, NEMO1 120 proteins at a concentration of 100 μM were incubated in water containing 25 mM DTT at 4 °C for various periods of time, and then analyzed by SDS-PAGE without boiling.
To address the issues, researches have been recently conducted to explore the biofuel tolerance mechanisms and to construct robust high-tolerance strains for non-native biofuel-producing microorganisms.
The efficiency of the constructed RNS-based tolerance intervals compared to their SRS counterparts is discussed.
The proposed algorithm constructs a fault tolerance approach to the P2P VoD advertising service, providing groups of participants in a video session with video loss recovery using replicated chunks of importance.
According to Krishnamoorthy and Mathew (2009), to construct a nonparametric tolerance interval with the confidence level of (100 times left( {1 - alpha } right){text), a pair of order statistics (x_{r}) and (x_{s}) need to be determined by which at least (p times 100percentnt of the population would be covered.
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