Search results
Results from the WOW.Com Content Network
In statistics, a concordant pair is a pair of observations, each on two variables, (X 1,Y 1) and (X 2,Y 2), having the property that = (), where "sgn" refers to whether a number is positive, zero, or negative (its sign).
Somers’ D takes values between when all pairs of the variables disagree and when all pairs of the variables agree. Somers’ D is named after Robert H. Somers, who proposed it in 1962. [1] Somers’ D plays a central role in rank statistics and is the parameter behind many nonparametric methods. [2]
The concordance correlation coefficient is nearly identical to some of the measures called intra-class correlations. Comparisons of the concordance correlation coefficient with an "ordinary" intraclass correlation on different data sets found only small differences between the two correlations, in one case on the third decimal. [ 2 ]
where is the number of concordant pairs, and is the number of discordant pairs in the data set. The denominator in the definition of can be interpreted as the total number of pairs of items. So, a high value in the numerator means that most pairs are concordant, indicating that the two rankings are consistent. Note that a tied pair is not ...
All points in the gray area are concordant and all points in the white area are discordant with respect to point (,). With = points, there are a total of () = possible point pairs. In this example there are 395 concordant point pairs and 40 discordant point pairs, leading to a Kendall rank correlation coefficient of 0.816.
In statistics, inter-rater reliability (also called by various similar names, such as inter-rater agreement, inter-rater concordance, inter-observer reliability, inter-coder reliability, and so on) is the degree of agreement among independent observers who rate, code, or assess the same phenomenon.
calculation of () Radial distribution function for the Lennard-Jones model fluid at =, =.. In statistical mechanics, the radial distribution function, (or pair correlation function) () in a system of particles (atoms, molecules, colloids, etc.), describes how density varies as a function of distance from a reference particle.
data randomization or Y-scrambling for verifying the absence of chance correlation between the response and the modeling descriptors. The success of any QSAR model depends on accuracy of the input data, selection of appropriate descriptors and statistical tools, and most importantly validation of the developed model.