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This paper introduces the concept of distribution distance for the measurement of errors in exact and approximate methods for stochastic simulation of chemically reacting systems.
These data also facilitate the assessment and measurement of errors of omission, i.e., the lack of use of appropriate drugs when needed.
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Much work currently has been focused on the measurement of error motions and spindle balancing.
There is a term in the measurement of
To characterize the misclassification process, we consider a practical situation where replicated measurements of error-prone covariates are available.
In Section 4, we develop inferential procedures to accommodate misclassification effects with the availability of replicated measurements of error-contaminated covariates.
Our development is carried out under a practical setting where a validation sample is impossible but repeated measurements of error-contaminated variables are available.
By this approach, the statistical errors are reduced which enables a very precise measurement of systematic errors between both setups.
The present results will assist in establishing a method for the reliable measurement of refractive errors in individuals.
The resulting knowledge would be instrumental to lay the foundation for both retrospective and more proactive measurement of diagnostic errors.
First, measurements of intensity errors and color errors present in the short-exposure image are performed.
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