Sentence examples for the upper probability from inspiring English sources

In the first case, the upper probability is computed as the supremum of the probabilities that g(Xλ) lies in B. In the second case, one considers the random set generated by all g(Xλ), λ∈Λ, e.g. by transforming Xλ to standard normal as a common probability space, and computes the corresponding upper probability.

In this section, we investigated the upper probability using the saddlepoint approximations to (S_n).

Finally, the p-value can be calculated as the upper probability of the empirical distribution of the maximum EIFs.

Comparison of yellow fever predicted probability map with Yellow Fever Vaccination Recommendations map: counties in the upper probability classes correlated spatially with the recommended vaccination areas prior recent outbreaks.

These simulations suggested that use of a threshold value based on the upper probability limit balanced the low sensitivity of the diagnostic methods and improved survey performance, compared with basing decisions on prevalence estimates.

With the error rate q i,j,d, the upper probability (P) that the number of reads (R) with a certain sequence alteration of category j in position i is equal or greater than the number of observed reads r out of N reads with a sequenced direction d for an unknown sample was defined as: (2) where, λi,j,d = N i,d × q i,j,d.

The parameter δ is determined by the PMRN width w as (4) with, where pl and pu specify the lower and upper probability bounds, respectively, chosen for defining the PMRN width (in our model, we choose quartiles, pl = 0.25 and pu = 0.75; Fig. 1A).

In the multivariate case, a number of ways of combination is highlighted and the corresponding upper probabilities are computed.

6 Here, the maximum numbers positive for STH in order for an EU to be classified as below a given treatment threshold is based on the upper 95% probability limit, to minimize Type I error (probability of incorrectly classifying an area as below a given threshold) while maintaining a certain level of power in acceptance.

6 These suggested sample sizes are based on LQAS critical cut-off points, which enable classification of an EU below a given prevalence threshold based on the upper 95% probability limit, to minimize Type I error (probability of incorrectly classifying an area as below a given threshold).

Thus, the upper bound probability of a symbol (code word) error is given by.