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For obtaining the nominal coverage, the KMS intervals are recommended, providing coverages nearly always between 95%and97%7%.
The simulation results show that the coverage percentages of the proposed generalized confidence intervals are quite close to the nominal coverage probabilities, even for small sample sizes.
However, it is important to note that expanding nominal coverage may not necessarily lead to bridging gaps in access to health services.
We note that, although the nominal coverage of the evaporated In is more than several monolayers (ML), post annealing removes surplus In layers and establishes the ( 7 × 3 )-In surface.
Through Monte Carlo simulation we show that both variance estimators are approximately unbiased, but that the new estimator is more stable (i.e., has lower empirical variance) and provides empirical confidence interval coverage rates that coincide more closely with the nominal coverage rates.
Although these numbers show that there is a higher decrease on the coverage for debug-corrective documentation than for how-to-do-it, the numbers should not be used absolutely to infer the increase in the nominal coverage results we will show for RQ #1 and RQ #2, as the decrease tends to be lower as we enlarge the sample.
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Nominal carbon coverage was approximately 1.0 ML.
A total nominal sequencing coverage of more than 500× allowed the construction of a largely contiguous whole genome sequence.
This has generated over 77,000 paired Sanger reads, at a nominal 6.7× coverage (Nicolas Pollet, personal communication).
Table 1 shows that overall the uncertainty intervals from the BYM model are closest to their nominal 95% coverage levels, with values above 90% for all scenarios.
We note that the actual percentages found here apply only to our sampling of 1053 cells which approaches nominal 1× coverage of the ≈1100 rat ORs.
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