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CSOP and RLSE need to access (quantised) coefficients, thus are applied after the coefficient prediction stage.
After the coefficient vector ({{mathbf {m}}}) has been determined, the equations are re-weighted according to the difference between modeled and measured values (residuals), (epsilon _i).
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After analyzing the coefficient histogram after BDCT and difference operation, we find that most coefficients are small and centering on zero, and a similar situation is also found in the DWT domain.
After the coefficients in a logistic regression model have been estimated, goodness-of-fit of the resulting model should be examined, particularly if the purpose of the model is to estimate probabilities of event occurrences.
After the coefficients a(m) have been determined, the polynomial F z) can be obtained: F z)={displaystyle sum_{m=0}^M}a(m){z}^{M-m} (9).
After the coefficients (a_{i,j,k}) are determined, we compute the approximate solution (u_{N,M,K} x,y,t)) at any value of ((x,y,t)) in the given domain.
After the coefficients β are computed for each probeset, one can test various hypotheses on the structure of considered factors.
Thus, only one model needs to be built at the sensor level, and after the coefficients are projected in source space, PDC can be efficiently computed for a wide range of frequencies.
The total amount of individual elements comprising the reactants should equal the amount of individual elements comprising the products after the coefficients are placed.
After determining the coefficient, we calculate the out-of-sample return.
However, its interaction in the temporal dimension shows that this possibility increase significantly in every following year after 2003 (the coefficient in 2008 is only marginally significant).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com