Sentence examples for setting variance from inspiring English sources

Persistent cultural factors, in other words, seem very important in setting variance ratios.

The PSNR values equal to 30, 27, 24, and 21 dB mentioned above are provided for AWGN and spatially correlated noise by setting variance values σ2 equal to 65, 130, 260, and 520, respectively, for images with 8-bit representation in each color (R, G, and B) component.

Table 8 Principle Component Decomposition of the Imagery Datasets Image set Variance explained by first eight Variance explained next eight RGB 76.00% 13.40% CIR 75.10% 13.70% CHM 72.60% 14.70%.

Principal components (PC s are those which: (1) account for the majority of set variance (usually >> 10% each); (2) are necessary for adequate reconstruction of all spectra in the set; (3) meet various empirical and statistical selection criteria [38].

35% of the data set variance was in this case explained by these three parameters.

We also directly compared the data set variance and fold change distribution in these data sets (Figure S1).

This is in contrast to fold changes in which increased data set variance can randomly produce more extreme fold-changes.

In this scenario SAM offers the best estimate of the magnitude of regulation since the internal data set variance directly influences the significance estimates through the sample permutation strategy built into this approach.

Since differences in data set variance are controlled in the SAM algorithm, we conclude that there is substantial translational deregulation in IPF fibroblasts compared to controls that cannot be explained by transcriptional regulation.

This finding indicates that the difference between the translational and the transcriptional regulation cannot be explained by higher data set variance for the total RNA data sets (as the fold differences in the translational estimate have been normalized to the fold differences in the transcriptional estimate and therefore contain the variance from both of these comparisons).

Final variance estimation is a weighted average between traditional variance estimation value and the whole data set variance estimation.