Sentence examples for order of correlation from inspiring English sources

Specifically, eight CASH indicators (in order of correlation strength: Protein, ActC, Mn, Resp, AgStab, P, Mg, and OM) displayed significant linear relationships to mean corn yields (Figure 1).

As a further contribution of this paper, we prove that except for very few cases, the sum of the degree of avalanche and the order of correlation immunity of a Boolean function of n variables is at most n−2.

In one subband, the order of correlation matrices F is not large, so this operation is efficient.

The authors stated especially that: (i) scaffold 6 is higher active on the CA II and CA IV than on CA I (ii) the descending order of correlation is: CA II and CA IV > CA I and CA IV > CA I and CA II (iii) the descending order of strength of activity is: CA II > CA IV > CA I (iv) they predicted compounds A13 and D16 too good for CA I and CA II in some cases for D16.

The VMC variables that correlated significantly with the right limb's clinical deficit were, in a descending order of correlation strength: Directional error during tracing (R = 0.53), frequency of tracking Interruptions (R = 0.50), tracking speed (R = −0.49), % lost tracking time (R = 0.47) and directional error during tracking (R = 0.42).

To summarize briefly, for each test exome we rank the remaining samples by order of correlation with the test exome.

A fundamental question that arises as we seek to quantify these population dynamics is the statistical order of correlations among spiking activity in different neurons.

I N can be uniquely broken down to the sum of exact contributions of each order of correlations, when the contribution of order k to I N, is given by I (k ) = H [ p (k − 1 ) ] − H [ p k ], where H [ p k ] is the entropy of the ME models of order k (Schneidman et al., 2003).

Our analysis of the social interaction network underlying the group behavior relied on a family of maximum entropy models, which enabled us to uniquely dissect the contribution of different orders of correlations in the group.

We see that p(3) gave a very good approximation to the empirical data (left bottom panel), and was very close to the accuracy of p(4) that relies on all orders of correlations among mice (bottom right panel).

We built a hierarchy of maximum entropy models to describe the group configurations, based on successive orders of correlations between the mice (one that relies only on individual behavior of the mice, one that adds pairwise dependencies between mice, third order, etc).