Therefore, when lacking available genotyping data to estimate sensitivity and specificity, Mendelian inconsistencies derived from available pedigree structures can assist in gauging overall levels of genotype error and could aid in the optimization of genotype calling algorithms.
This error model has two components: (1) the error in the gauge measurement itself, and (2) the error introduced by the gauge not capturing the spatial variability within a radar pixel.
This is not a new idea, using prediction error to gauge cluster quality has appeared in several earlier studies: Dudoit and Fridlyand (2002), Dudoit, Fridlyand, and Speed (2002), and Tibshirani and Walther (2005).
Even workers in nuclear power plants make "errors in reading gauges, interpreting indicator lights, and selecting the wrong button to push," Casner writes.
Following standard practice, error awareness was gauged by giving participants the opportunity to signal error commission by pressing a second verification button [41].
Since scale's sensitivity to change is affected by measurement error, we used values of 95% confidence intervals (CI; calculated as 1.96*SEM) around SF-36 scores from a normative population-based sample [ 36] to gauge measurement error in SF-36 scores in orthopedic settings.
Errors in the data mainly occur through uncertainty in gauging (measurement uncertainty) and uncertainty in the determination of the stage-discharge relationship based on gaugings (rating curve uncertainty).
Lastly, consideration of errors in typically available gauging station and inundation extent data shows the raster-based model to be close to the current prediction limit for this class of problem.
More than 40 rain gauges are required to reduce the potential error in areal rainfall estimation to values <0.1 mm h−1.
Furthermore, it has been found that a minimum of 10 strain gauges is necessary to allow for a low error in the reconstructed forces.
