Sentence examples for cumulative deviations from inspiring English sources

But in more-scattered communities and in larger language areas, especially when cultural and administrative ties are weakened and broken, these cumulative deviations in the course of generations give rise to wider regional differences.

The eigenvalues of the first 30 eigenvectors and their relative cumulative deviations of these two G-quadruplex ensembles were shown in Fig. 6A.

As our FM fits differ from the actual data set by less than 2% in maximum cumulative deviations and yield compression ratios ranging from 76:1 to 228 1, our models can be considered, for all practical purposes, faithful and parsimonious deterministic representations of the storm.

The accuracy of the developed VFM was also analyzed using cumulative deviation plot where the predictions are within a maximum deviation of  ± 15%.

For measuring the performance of the clustering algorithms and also to define a parameter that allows for comparison and classification of modulation schemes, we define a term called relative error or Cumulative Deviation Error (CDE) and denote it εCDE.

The EL5 scheme is evidently much better at conserving mass in this test than MP5, leading to a cumulative deviation of ({sim}10^{-7}~M_{odot}) whish is almost three orders of magnitude smaller than the MP5 value.

The notations in Table 1 are as follows: MD minimum deviation, SPT shortest processing time, SLK slack, DD due date, GCMD generalized cumulative minimum deviation, COST, VALUE, COV cost over time, and LPT longest processing time.

More recently it has been applied to the early detection of disease outbreaks [20] and to adverse drug events.[21], [22] The CUSUM, a type of control chart, detects sudden changes in the mean value of a quantity of interest and provides estimates of the timing and magnitude of change.[23] Specifically, the analysis calculates the cumulative sum of deviations from a set value in successive samples.

In this study, we use simulations to assess the cumulative effect of deviations from normality and homoscedasticity on the overall performance of quantitative Model-Based Multifactor Dimensionality Reduction (MB-MDR) with variable association tests to detect 2-locus epistasis signals.

In this study, we assess through simulations, the cumulative effect of deviations from normality and homoscedasticity on the overall performance of quantitative Model-Based Multifactor Dimensionality Reduction (MB-MDR) to detect 2-locus epistasis signals in the absence of main effects.

Calculation of GR deviation cumulative distribution exactly showed the Kangan-Dalan (Permian Triassic) boundary.