Sentence examples for estimate whose from inspiring English sources

However, the results can be improved by using the lower-order CCs in the estimate, whose variance is shown to be less than that of corresponding higher orders.

In Additional File 3, we prove an oracle inequality for a slight modification of the present estimate, whose exact form can also be found in [58].

Since the observed data is regarded as a sample from an underlying distribution, the optimal latency ϕm as inferred from the data is an estimate, whose distribution is again obtained by simulation.

24 25 A commonly cited estimate, whose provenance is unclear, is that 10% of clinical ED cases occur in men, 2 26 but some data suggest that this prevalence could be as high as 25%.

Moreover, Figure 8 shows that in multipath channel A the AML1 CFO estimator outperforms the AML2 estimator and assures estimates whose accuracy is quite similar to that provided by the SC estimator.

For this reason, an EGARCH (1,1) model is estimated whose empirical results are reported in Table 3.

The Pred measures the percentage of the estimates whose error is less than % and it is usually set at 25. Pred is simply the percentage of estimates that are within m % of the actual value (the % of the estimates with MRE ≤0.25).

He pointed out that, like the mark-recapture estimates of population numbers, the gene frequencies themselves were estimates whose variation, based on the reported sample sizes, accounted for more than half (55.2%) of the observed variance that Fisher and Ford were trying to explain.

[Derivatives are] financial weapons of mass destruction.. Derivatives generate reported earnings that are often wildly overstated and based on estimates whose inaccuracy may not be exposed for many years.. Large amounts of risk have becomes concentrated in the hands of relatively few derivatives dealers... which can trigger serious systematic problems.

From the individual ORs, a pooled OR was estimated, whose statistical significance was determined using the Z-test.

Only estimates whose posterior distribution dropped to zero within the prior intervals were trusted.