Sentence examples for datasets dispersion from inspiring English sources

Exact(1)

Expression values were normalized for the libraries size with the trimmed mean of M‐values method followed by estimation of the datasets dispersion.

Similar(59)

The ambient margins around the curves in the ratio panels illustrate the standard deviations of the SEA process, which measure the spread of datasets and the dispersion from the SEA mean values.

In this paper, data of multiple field experiments are brought to common platform and, based on the statistical investigation of this dataset, an atmospheric dispersion model is proposed, which allows for the reconstruction of the pointwise concentration statistics as functions of windward and lateral coordinates.

A complete single-wavelength anomalous dispersion dataset was collected at the selenium-absorption high-remote wavelength (0.96369 Å, determined by fluorescence scan).

The SAD (single-wavelength anomalous dispersion) dataset was collected at one wavelength (λpeak=0.9790 Å), and both native and SAD data were processed using HKL2000 [ 19] and programs in the CCP4 package [ 20].

Figure 9 shows the higher data dispersion of Dataset II compared to Dataset I. Content independency was tested using the cross-validation method.

Keeping the concept of chemical space in mind, it is reasonable to make use of the field of spatial statistics, which offers a wealth of methods for the analysis of clustering, patchiness and dispersion of datasets.

Multi-wavelength anomalous dispersion (MAD) datasets were collected from selenomethionine (SeMet -derivatized LIC crySeMet -derivatizedengths, a high-energy remote waveLICgth and at a wavelength halfway between the peak and inflecrystalsint.

The dataset contains 225 observations ranging in value from 0 to 7, and are over-dispersed with dispersion index (widehat {text {Var}(Y)}/widehat {E(Y)}= 0.693/0.382 = 1.8119); summary information regarding the distribution is provided in Table 4(a).

Based on the manifold learning method, we design neighborhood geometry and target function using the average of similar dispersion of dataset, and then, calculate the linear embedding mapping, according to category information.

Dispersion of dispersed nanoparticles.

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