An algorithm to test divisibility of continuous distributions,applied to the uniform distribution

We present an algorithm to test if a continuous random variable is n-divisible. Through the algorithm, testing for divisibility is put in the format of numerical analysis amenable to computer processing. This is illustrated with the uniform distribution which is known to be non-divisible. New evidence and new proofs arising out of the insight developed with this style are given. This algorithm, along with the analytical methods should provide much needed versatility to tackle problems in this area. The fact that Bondesson [1987] works on the divisibility of the Half Cauchy Distribution gives evidence that there are many distributions which can use the combination of the analytical and the algorithmic tools to settle the divisibility issue.     

On Extending Russell and Krajewski's Algorithm for Economic Purchase Order Quantities*

Russell and Krajewski presented an optimal purchase order quantity algorithm that considered the effect of the transportation rate structure for less-than-truckload (LTL) shipments. The authors applied the Russell and Krajewski algorithm to a variety of freight classes and lengths-of-haul. Anomalous cases were found in which the freight rate schedule, when used with the suggested algorithm, resulted in incorrect order size decisions. In this comment, the authors consider the impact of these anomalies on the optimal order quantity and associated total costs. A procedure is presented to adjust the Russell and Krajewski algorithm to arrive at the optimal purchase order quantity and the lowest total annual cost.     

San Diego's 6 to 6: a community's commitment to out-of-school time

San Diego is the first major city in the nation to provide free before- and after-school services to every public elementary and middle school within its borders.     

Sampling distribution after splitting experimental units

It has been a common practice to recommend one distribution for a large class of problems. An example is the use of the logarithmic distribution for count data - the point of concern in this paper is its recommendation without regard to the size of the experimental unit. References for this particular distribution go back to Fisher et al. [1943]. Look up Douglas [1980], Patil et al. [1984] and Kotz and Johnson [1985] to pick up additional references in this area -especially through sorting the data base of the American Mathematical Society. We will show a fallacy in this structure; provide a computer algorithm find the actual distributions; and then to check on the divisibility. The language used is APL2. But the users can make up their own programs.