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In the T method [ 19] the differentiation between two matrices is measured as the sum of the absolute differences between the two matrices' elements.
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The reported statistics for each pair of matrices are R, Pearson's correlation coefficient; the estimated error, or bootstrap estimate of the standard deviation of the observed correlation; and the Z-score and corresponding P-value estimating the probability that a particular correlation between two matrices was obtained by chance.
The difference between these two matrices is shown in Figure 6C.
Several authors have proposed the use of blood/VH concentration ratios for estimating survival time (intake-to-death interval) based on the time of distribution from blood to VH: soon after intake, the ratio is higher than when equilibrium between the two matrices is reached.
Equality between the elements of the two matrices is estimated by comparing the extent of departure between their respective ranked eigenvalues after eigen-decomposition of each matrix [ 25].
To measure the similarity between trees, the CC of two matrices is calculated.
The Spearman's correlation coefficients for TSH and T4 between the two matrices were 0.49 and 0.56 (p < 0.05 for both).
More precisely, the RMSE between any two matrices was never larger than 0.02 (corresponding to an ∼2% difference) and the R correlation coefficient was always >0.99 (suggesting that they are almost perfectly correlated).
The differences between the cells in these two matrices are considerably smaller than those in Tables 2 and 3.
If the following conditions are met between two matrices, we can say that the two matrices are equal: the sizes (the row and column of matrix) of sub-graphs are the same; both the numbers of out-degree and that of in-degree are respectively equal; and so the matrices have the same Code value, and furthermore the corresponding symmetrical ternary number are the same.
Two matrices were constructed.
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