Partitioning a distribution

Abstract
Suppose it is desired to partition a distribution into k groups (classes) using squared error or absolute error as the mea¬sure of information retained. An algorithm to obtain the optimal boundaries (or class probabilities) is giTen. For the case of squared error optimal class probabilities were obtained for k = 2 to 15 for beta (for various values of the parameters), chi-square (12 d.f.) exponential, normals and uniform distributions. Results obtained are compared and analysed in light of existing papers, Special attention is given to the case k =5, corresponding to the assignment of the letter grades A, B, C, D9 P in courses, and to the case k = 9 corresponding to stanines.

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