Other Measures of Dependence Among Random Variables
The information given by a correlation coefficient is not enough to define the dependence structure between random variables. The correlation coefficient completely defines the dependence structure only in very particular cases, for example when the distribution is a multivariate normal distribution. (See diagram above.) In the case of elliptical distributions it characterizes the (hyper-)ellipses of equal density, however, it does not completely characterize the dependence structure (for example, a multivariate t-distribution's degrees of freedom determine the level of tail dependence).
Distance correlation and Brownian covariance / Brownian correlation were introduced to address the deficiency of Pearson's correlation that it can be zero for dependent random variables; zero distance correlation and zero Brownian correlation imply independence.
The correlation ratio is able to detect almost any functional dependency, and the entropy-based mutual information, total correlation and dual total correlation are capable of detecting even more general dependencies. These are sometimes referred to as multi-moment correlation measures, in comparison to those that consider only second moment (pairwise or quadratic) dependence.
The polychoric correlation is another correlation applied to ordinal data that aims to estimate the correlation between theorised latent variables.
One way to capture a more complete view of dependence structure is to consider a copula between them.
Read more about this topic: Correlation And Dependence
Famous quotes containing the words measures, dependence, random and/or variables:
“To have the fear of God before our eyes, and, in our mutual dealings with each other, to govern our actions by the eternal measures of right and wrong:MThe first of these will comprehend the duties of religion;Mthe second, those of morality, which are so inseparably connected together, that you cannot divide these two tables ... without breaking and mutually destroying them both.”
—Laurence Sterne (1713–1768)
“As, therefore, we can have no dependence upon morality without religion;Mso, on the other hand, there is nothing better to be expected from religion without morality;Mnevertheless, ‘tis no prodigy to see a man whose real moral character stands very low, who yet entertains the highest notion of himself, in the light of a religious man.”
—Laurence Sterne (1713–1768)
“poor Felix Randal;
How far from then forethought of, all thy more boisterous years,
When thou at the random grim forge, powerful amidst peers,
Didst fettle for the great gray drayhorse his bright and battering
sandal!”
—Gerard Manley Hopkins (1844–1889)
“Science is feasible when the variables are few and can be enumerated; when their combinations are distinct and clear. We are tending toward the condition of science and aspiring to do it. The artist works out his own formulas; the interest of science lies in the art of making science.”
—Paul Valéry (1871–1945)