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Methods for determining the process noise covariance matrix are provided.
In (13), two alternative solutions for the MIMO LE matrix are provided.
Sufficient conditions to achieve regulation in terms of the steady-state gain matrix are provided, allowing to obtain a systematic procedure for analyzing multiloop control configurations of complex and interacting processes.
The sequencing statistics and the correlation matrix are provided in Additional file 8: Table S7.
The scores plots of the first 3 PCs from PCA performed on the peak table matrix are provided in Fig. 3 and the loadings plot of the first 2 PCs are provided in Fig. 4. The variables with their absolute loadings (either PC1 or PC2) greater than 0.1 are labelled in Fig. 4 along with their corresponding m/ z.
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The correlation matrix is provided in the Appendix.
A recommended risk acceptance criteria or matrix is provided.
To solve the singular problem of small sample inverse covariance matrix estimation, a method of adding band mean value to covariance matrix is provided.
With these notations, a complete data estimator of the separating matrix is provided by B=(X 0), where X 0 has been defined in Equation (18).
The descriptive statistics and correlations matrix is provided in Tables 3 and 4, respectively.16 Table 3 Descriptive statistics Variable Obs Mean Std.
The subarray covariance matrix is provided by begin{array}{*{20}l} {mathbf{R}_{xb}}(t) = {mathbf{T}_{b}}^{H}mathbf{R}(t){mathbf{T}_{b}}.
Related(20)
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