Some aspects of the sampling distribution of the Apportionment Index and related inference

As customer-oriented production strategies have gained ground in the sawmill industry, proper measurement of the fit between the log demand and log output distributions has become of crucial importance. The prevailing means of measuring the outcome is the so-called Apportionment Index (AI), which is calculated from the relative proportions of the observed and required distributions. Although some statistical properties of the AI have recently been examined and alternative means of measuring the bucking outcome have been suggested, properties of the sampling distribution of the AI have not yet been widely studied. In this article we examine the asymptotic sampling distribution for the AI by assuming a multinomial distribution for the outcome. Our results are based mainly on large-sample normal approximations. Also some studies of the determination of the number of logs needed to obtain a specified level of accuracy of the AI have been carried out.

Abstract licence: CC BY-SA

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