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Nonparametric inference about service time distribution from indirect measurements

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In studies of properties of queues, for example in relation to Internet traffic, a subject that is of particular interest is the ‘shape’ of service time distribution. For example, we might wish to know whether the service time density is unimodal, suggesting that service time distribution is possibly homogeneous, or whether it is multimodal, indicating that there are two or more distinct customer populations. However, even in relatively controlled experiments we may not have access to explicit service time data. Our only information might be the durations of service time clusters, i.e. of busy periods. We wish to ‘deconvolve’ these concatenations, and to construct empirical approximations to the distribution and, particularly, the density function of service time. Explicit solutions of these problems will be suggested. In particular, a kernel-based ‘deconvolution’ estimator of service time density will be introduced, admitting conventional approaches to the choice of bandwidth.
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Keywords: Alternating renewal process; Bandwidth; Kernel methods; Nonparametric density estimation; Queuing theory; Renewal process

Document Type: Research Article

Affiliations: 1: Australian National University, Canberra, Australia 2: University of North Carolina, Chapel Hill, USA

Publication date: November 1, 2004

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