The Theory of Probability Distributions of Points on a Lattice

This paper discusses the theory of certain probability distributions arising from points arranged in the form of lattices in two, three and higher dimensions. The points are of k characters which for convenience are described as colors. A two-dimensional lattice will consist of m \ n points in m columns and n rows. In a three-dimensional lattice there will be l \ m \ n points in the form of a rectangular parallelopiped. Two situations arise for consideration. They are, to use the term of Mahalanobis, free and non-free sampling. In free sampling the color of each point is determined, on null hypothesis, independently of the color of the other points. The probabilities of the points belonging to the different colors, say black, white, etc. are p₁, p₂ \ pₖ, such that \₁ᵏpᵣ = 1. In non-free sampling the number of points of each color is specified in advance, say n₁, n₂ \ nₖ so that \₁ᵏnᵣ = mn or lmn according as the lattice is two- or three-dimensional. Only the arrangements of these points in the lattice are varied. The distributions considered in this paper are the following: -- (i) the number of joins between adjacent points of the same color, say black-black joins, (ii) the number of joins between adjacent points of two specified colors, say black-white joins, and (iii) the total number of joins between points of different colors, along mutually perpendicular axes. The methods used here are the same as those developed by the author 3 for the linear case. All the distributions tend to the normal form when l, m and n tend to infinity, provided the p's are not very small. Before considering the various distributions, we shall have a brief review of the work done on this topic by other people. For free sampling, Moran 5 and 6 has discussed the distribution of black-white and black-black joins for an m \ n lattice of points of two colors. For a three-dimensional lattice, he has given the first and the second moments for the distribution of black-white joins. Levene 4 has announced some results closely allied to those of Moran for a square of side N (with N² cells) each cell taking the characteristic A or B with probabilities p and q = 1 - p respectively. Bose 2 has found the expectation of x = the number of black patches - the number of embedded white patches, for a square divided into n² small cells, having p and q = 1 - p as the probability of the cells being black or white. An embedded white patch is one that lies completely inside a black patch. The above review shows that the work done so far is confined entirely to the free sampling distributions, the points taking only two characters. As mentioned in the beginning of this article, we shall deal here with the free and non-free sampling distributions for points possessing k characters or colors.