Sentence examples for maximal information coefficient from inspiring English sources
The maximal information coefficient (MIC) is part of this class and a novel measure to quantify nonlinear relationships.
In 2011, Reshef et al. [ 28] proposed a new measure named maximal information coefficient (MIC), which can capture both linear and nonlinear association between two variables.
Four tests for investigating linear and non-linear dependencies between variables are implemented: Pearson correlation, Spearman's rank, Distance correlation (Szekely and Rizzo, 2009) and the recently described Maximal Information Coefficient (MIC) (Reshef et al., 2011).
Also, despite a recent debate [ 87] as to which information-theory based measure provides the highest statistical power (maximal information coefficient or a related measure, mutual information), both measures clearly identify nonlinear trends that are missed by Pearson correlation.
On the one hand, we analyzed bivariate associations by using the following: 1) the Wilcoxon exact test, 2) the Pearson correlation coefficient, 3) the Spearman's rank correlation coefficient, and 4) the maximal information coefficient (MIC) (Reshef et al. 2011).
The larger sample size available for physiological traits (n = 32) made it possible to search for both linear and non-linear relationships between gene expression and physiology using maximal information coefficient (MIC) as implemented in the MINE software [ 54].
To verify the potential statistical relevance of these associations, we estimated their maximal information coefficients (MICs) and confirmed the high co-expression relationships of these genes (MIC > 0.95).
Their painterly intensity and formal composition derive from Henri Cartier-Bresson's definition of photography as "the decisive moment," the juncture of maximal effect and maximal information.
Therefore it is desired to use configurations, which provide maximal information gain and low statistical uncertainty.
In today's world, there is a quest for moving and devising optimal strategies to seek maximal information.
This paper also found that the reduced alphabets with size 13 simplify PSSM structures efficiently while reserving its maximal information.
