Sentence examples for estimator to detect from inspiring English sources

The usefulness of any estimator to detect a decline can be jeopardized by false positives, that is detection of a reduction in N e when none occurred.

Taking into consideration that f 0 is the only known a priori information, in this section, we will introduce a MMSE estimator for determination of the finite bandwidth signals a n, and then, we develop our estimator to detect the presence of the UWB signal and extract the target's range and velocity.

As such we also assess how often each estimator to detect a decline when there is none (false positive rate).

We evaluated the performance of two N e estimators to detect population declines: the two-sample temporal method and a one-sample method based on linkage disequilibrium (LD).

Such alleles may have been introgressed into a population through historical crossbreeding and, thus, be included in various haplotypes, which prevents LD-based estimators to detect the selection signature.

Rather, the more difficult problem (handled by the target acceleration estimator) is to detect a single, randomly timed maneuver direction switch (MDS) during the endgame [4] (denoted as type II maneuver).

The Mann Kendal (MK) and Theil Sen Slope estimator (TSE) statistics to detect the direction and magnitude of an available monotonic trend in any given data, respectively, were used for the statistical analysis of the new data sequences.

The proportion of misclassifications moreover, is known to yield estimators with low power to detect signals in data when compared to other metrics such as area under the receiver operating characteristic (ROC) curve (AUC) [27].

Using computer simulations, Antao et al. (2010) evaluated the ability of NeD and NeV estimators to (i) detect a population decline, (ii) correctly identify a bottleneck with low bias and high precision, and (iii) evaluate whether the methods were subject to a high rate of false positives (i.e., indicate a bottleneck when none had occurred).

Secondly, monitoring programs need to be designed with adequate estimator precision and statistical power to detect a desired change, for example an increase in species abundance in response to interventions [11] [13].

Particle filters are nonlinear estimators that can be used to detect anomalies in manufacturing processes.