By Winifred Beaumont
Hardcover 1st variation released by way of the British Broadcasting company 1977, is great, one hundred sixty pages. A funny account of a nurse's reports in Burma WWII.
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Extra info for A Detail on the Burma Front
Dunsmuir and Snyder 1989; Kwan 1991; Willemain et al. 1994; Janssen 1998; Eaves 2002). With Poisson arrivals of demands and an arbitrary distribution of demand sizes, the resulting distribution of total demand over a fixed lead time is compound Poisson. Inter-demand intervals following the geometric distribution in conjunction with an arbitrary distribution for the sizes, results in a compound binomial distribution. Regarding the compound Poisson distributions, the stuttering Poisson, which is a combination of a Poisson distribution for demand occurrence and a geometric distribution for demand size, has received the attention of many researchers (for example: Gallagher 1969; Ward 1978; Watson 1987).
In other cases, and depending on the objectives or constraints imposed on the system, such estimates are also necessary, although they do not constitute the ‘key’ quantities to be determined. We may consider, for example, an (R, S) or an (s, Q) policy operating under a fill-rate constraint—known as P2. (In the former case, the inventory position is reviewed periodically, every R periods, and enough is ordered to bring it up to S. ) In those cases we wish to ensure that x% of demand is satisfied directly off-the-shelf and estimates are required for the probabilities of any demands exceeding S or s (for the (R, S) an (s, Q) policy, respectively).
The same distribution has appeared in the literature under the name ‘hypothetical SKU’ (h-SKU) Poisson distribution (Williams 1984), where demand is treated as if it occurs as a multiple of some constant, or ‘clumped Poisson’ distribution, for multiple item orders for the same SKU of a fixed ‘clump size’ (Ritchie and Kingsman 1985). The ‘Package Poisson’ distribution requires, as the Poisson distribution itself, an estimate of the mean demand only. The short review of the literature presented above indicates that it is worthwhile testing the empirical goodness-of-fit of the following distributions: (i) Poisson; (ii) NBD; (iii) stuttering Poisson; (iv) Gamma; and (v) Normal.
A Detail on the Burma Front by Winifred Beaumont