We denote such correlation between the tests i and j by c ij. 2. Given a missing value in the test i for the subject k, we found the test j = j0 which had the highest value of |c ij | among the tests with the value x jk available and set where the coefficients a and b were found by computing linear regression of the test j0 on the test i using only subjects with results available for both tests.
Estimating directions by computing linear regression of neighbors of the three pixels in bold (c).
PCA works by computing linear projections of greatest variance from the top eigenvectors of the data covariance matrix, thereby preserving the covariance structure of the data.
We generated predictions for the fourth quarter of 2001 by computing linear combinations of the appropriate parameters from the above models.
Model accuracies were estimated by computing the linear correlation, the mean prediction error (MPE) and mean absolute prediction error (MAPE) of the observations and predictions to a 10% hold-out dataset.
Here, differential Granger causality maps (dGCM) were computed for each source voxel with an order of 1 TR (1.3s) by computing the linear direct influence of source to target (I→J) and of target to source (J→I), and subtracting the latter from the former.
We ran univariate analyses by computing the linear contrast across the repetition sequence at each voxel in both runs, and we sorted voxels as RS versus RE in a post hoc manner, depending on whether their response was negative versus positive.
By the note following Lemma 2.8, the deviation of ΔJC from additivity in an interval [ t0, t1] can be evaluated by computing the linear interpolation Δint= At + B of ΔJC in [ t0, t1], and finding t ∈[ t0, t1] which maximizes ΔJC(t )− Δint(t ) (see Figure 1a).
Moreover, the contribution of both modalities to the overall quality can be measured by computing the linear Pearson correlation between those quantities.
CS utilizes an efficient encoding framework in which we directly acquire a compressed representation of the underlying signal by computing simple linear inner products with a small set of randomly generated test functions.
