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Today's call center managers face multiple operational decision-making tasks. One of the most common is determining the weekly staffing levels to ensure customer satisfaction and meeting their needs while minimizing service costs. An initial step for producing the weekly schedule is forecasting the future system loads which involves predicting both arrival(More)
By investigating a Markov chain whose limiting distribution corresponds to that of the Dirichlet process we are able directly to ascertain conditions for the existence of linear functionals of that process. Together with earlier analyses we are able to characterize those functionals which are a.s. finite in terms of the parameter measure of the process. We(More)
There is a good deal of miscommunication among experimenters and theorists about how to evaluate a theory that can be rejected by sufficient data, but may nevertheless be a useful approximation. A standard experimental design reports whether a general theory can be rejected on an informative test case. This paper, in contrast, reports an experiment designed(More)
We consider the analysis of time series data, with particular emphasis on series which have a heavy-tailed structure | that is, whose marginal distributions have a right tail which is regularly varying at innnity with index ?. A natural model to attempt to t to time series data is an autoregression of order p, where p itself is often determined from the(More)
This paper continues the study of time series models generated by non-negative innovations which was begun in Feigin and Resnick (1992,1994). We concentrate on moving average processes. Estimators for moving average coeecients are proposed and consistency and asymptotic distributions established for the case of an order one moving average assuming either(More)
For autoregressivetime series with positive innovationswhich either have heavy right or left tails, linear programming parameter estimates of the autoregressive coeecients have good rates of convergence. However, the asymptotic distribution of the estimators depends heavily on the distribution of the process and thus cannot be used for inference. A(More)
Bacterial and viral infections are often clinically indistinguishable, leading to inappropriate patient management and antibiotic misuse. Bacterial-induced host proteins such as procalcitonin, C-reactive protein (CRP), and Interleukin-6, are routinely used to support diagnosis of infection. However, their performance is negatively affected by inter-patient(More)
This paper compares two alternative models for autocorrelated count time series. The first model can be viewed as a 'single source of error' discrete state space model, in which a time-varying parameter is specified as a function of lagged counts, with no additional source of error introduced. The second model is the more conventional 'dual source of error'(More)