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Summarizing, the problem to solve consists in finding the frequency that the compressed candidate correlation has to be modulated to best fit the data autocorrelation matrix R ^ y and to find the contribution of this modulated candidate autocorrelation contained in R ^ y.
Our elicitation is based on an approximate Gaussian likelihood, and produces a set of candidate correlation structures for the residual spatial autocorrelation.
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The accuracy of the candidate correlations are performed in terms of the two widely used statistical indicators, mean bias and root mean square errors; standard deviation, standard error and F-test, were also introduced.
Gene-wise and condition-wise expanded biclusters are also candidate correlation-based biclusters that BICLIC algorithm has found.
Our microarray analysis has revealed a group of highly correlated pros candidate genes (correlation index: 0.9) that are either controlled by the insulin/TOR signalling pathway or are directly involved in the signalling cascade.
We determined broad-sense heritability of candidates, Pearson correlation of candidates with healing phenotypes, and Ward minimum variance cluster analysis for strains.
For each marker candidate the correlation between different blood samplings was assessed by scatterplots together with Spearman's correlation coefficient ρ and a Passing Bablok linear regression fit [ 20].
There is no doubt that all these candidate negative correlation miRNA/target genes should be emphasized.
According to the PCC and linear regression analysis, the candidate negative correlation miRNA/target genes were further analyzed.
For the 393 examiners who had seen between 100 and 199 candidates the correlation was 0.533 (p <.001), and for the 152 examiners who had seen 50 to 99 candidates the correlation was 0.411 (p <.001).
Finally for the 47 examiners who had seen less than 40 candidates, the correlation was only 0.129 (p =.387).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com