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The design matrix has dimension n-by-p, where n is the number of samples observed, and p is the number of variables measured in all samples. [4] [5]In this representation different rows typically represent different repetitions of an experiment, while columns represent different types of data (say, the results from particular probes).
Even though the row is indicated by the first index and the column by the second index, no grouping order between the dimensions is implied by this. The choice of how to group and order the indices, either by row-major or column-major methods, is thus a matter of convention. The same terminology can be applied to even higher dimensional arrays.
Chromatographic peak resolution is given by = + where t R is the retention time and w b is the peak width at baseline. The bigger the time-difference and/or the smaller the bandwidths, the better the resolution of the compounds.
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The column space of a matrix is the image or range of the corresponding matrix transformation. Let be a field. The column space of an m × n matrix with components from is a linear subspace of the m-space. The dimension of the column space is called the rank of the matrix and is at most min(m, n). [1]
If column dimensions Length×diameter×film are divided by 2 and gas velocity is doubled by using H2 in place of Helium, the hold times must be divided by 4 and the ramps must be multiplied by 4 to keep the same index and the same retention temperature for the same compound analyzed. Method translation rules are incorporated in some ...
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