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We study an inventory system in which a doctor provides service for two patient types over a main surgery day of T periods. As the horizon starts, patient demands arrive in each period, for either type of patients, following a stationary Poisson process with random service time. The model we consider is the doctor may choose to provide service on that main surgery day, or may choose to next main surgery...
A state space approach for the modeling of nonstationary time series is presented. Based on the concept of smoothness priors constraint, the overall model is fitted by using the Kalman filler and Akaike's AIC criterion. Whenever an autoregressive (AR) model with time-varying coefficient is fitted in state space model, it can be used for the time-varying spectrum estimation. Some numerical results...
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