Tables for use in rank correlation

Reduced rank models for contingency tables

In recent years much attention has been given to models for two-way contingency tables that can be formulated in terms of reduced rank of a matrix with probabilities. A well-known reduced rank model is the independence model, where the rank is one. For rank higher than one distinct classes of reduced rank models are possible. Each has the independence model as the special case for rank one. A f...

Tensor rank-one decomposition of probability tables

We propose a new additive decomposition of probability tables tensor rank-one decomposition. The basic idea is to decompose a probability table into a series of tables, such that the table that is the sum of the series is equal to the original table. Each table in the series has the same domain as the original table but can be expressed as a product of one-dimensional tables. Entries in tables ...

Set Correlation and Contingency Tables

Set correlation is a realization of the general multivariate linear model, can be viewed as a multivariate generalization of multiple correlation analysis, and may be employed in the analysis of multivariate data in any form. Set correlation supplements the four methods for analyzing two-way contingency tables described by Zwick and Cramer (1986), and its application to their example is illustr...

Spearman Rank Correlation Coefficient

Efficient Algorithms for Computing Correlation Tables in Stereoscopic Vision

An efficient algorithm for computing correlation tables of binocularly and trinocularly rectified stereo images is described. It is shown the proposed algorithms have a low complexity linearly proportional to a size of the images, independent on the correlation window size.