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Outstanding statistical problems in tele-traffic

机译:远程交通中的突出统计问题

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Summary form only given. Despite the enormous volume of telecommunications traffic data, which allows rich models to be realistically tested and estimation variance to be made 'as small as desired' in some contexts, there are many important gaps in the statistical wish-list for tele-traffic measurement and modeling. A selection of important current problems is in detail, including the apparently simple problem of confidence intervals on mean estimates, and the effects of traffic thinning on recent models of packet arrival processes. Each is described, their importance in the tele-traffic context explained, and progress towards solutions outlined.
机译:仅提供摘要表格。尽管电信流量数据量巨大,可以在某些情况下实际测试丰富的模型并使估算方差“按需减小”,但在电信流量测量和服务的统计愿望清单中仍存在许多重要空白造型。详细介绍了一些重要的当前问题,包括表面上均值估计上的置信区间看似简单的问题,以及流量稀疏对最新的数据包到达过程模型的影响。描述了每种方法,说明了它们在远程交通环境中的重要性,并概述了解决方案的进展。

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