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Matrix step III assesses the three dimensions of errors in studies.
The matrix is constructed from the three dimensions of errors: systematic error ('bias'), random error ('play of chance'), and design error ('wrong design to answer the question posed' or 'wrong context').
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This is where the three dimensions of error are of central importance in providing a tool for reliability assessment.
The phonological/semantic nature of the facts as well as the varying dimensions of error types is explained in more detail in the Additional file 1.
Matrix step I ranks the identified studies according to the dimensions of systematic errors and random errors.
A four-step matrix was constructed using the three dimensions of systematic error, random error, and design error.
For each state estimate, in (4), matrix inversion is computed with asymptotic complexity O ( R 3 ) [58], where R is the dimension of measurement noise covariance R or the number of available measurements; in (6), matrix multiplication is computed with asymptotic complexity O ( P 3 ) [58], where P is the dimension of error covariance or the dimension of the state vector.
For any integers L and r, the list-L decoder with multiplicityr guarantees successful recovery of the message subspace provided that the normalized dimension of error is at most ( frac{2left(L+1right)}{r+1}-1-frac{Lleft(L+1right)}{rleft(r+1right)}{R}^{ast } ) where R∗ is the normalized packet rate.
James, supremely utilitarian, regarded the moral dimension of the error as a failing; it didn't capture the nuances of what had really occurred on the field.
The dimension of the error vector ({mathbf{e}}) is (N times 1).
Errors in the azimuthal angle result from the compass calibration and the dimensions of the antenna while errors for the zenith angle are mainly governed by the binning of the direction reconstruction algorithm.
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