Pages that link to "Item:Q3632581"
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The following pages link to Bayesian Forecasting of an Inhomogeneous Poisson Process With Applications to Call Center Data (Q3632581):
Displaying 25 items.
- On the estimation of the true demand in call centers with redials and reconnects (Q319755) (← links)
- Inter-dependent, heterogeneous, and time-varying service-time distributions in call centers (Q322500) (← links)
- Operator-based intensity functions for the nonhomogeneous Poisson process (Q324613) (← links)
- Predicting the continuation of a function with applications to call center data (Q389291) (← links)
- Staffing a call center with uncertain non-stationary arrival rate and flexibility (Q443817) (← links)
- A stochastic programming model for scheduling call centers with global service level agreements (Q613494) (← links)
- Empirical Bayes predictive densities for high-dimensional normal models (Q634558) (← links)
- Forecasting emergency medical service call arrival rates (Q641084) (← links)
- The root-unroot algorithm for density estimation as implemented via wavelet block thresholding (Q846741) (← links)
- Practical statistical methods for call centres with a case study addressing urgent medical care delivery (Q889569) (← links)
- Workload forecasting for a call center: methodology and a case study (Q965108) (← links)
- Sequential Bayesian analysis of multivariate count data (Q1631552) (← links)
- The impact of special days in call arrivals forecasting: a neural network approach to modelling special days (Q1681423) (← links)
- Analytics for labor planning in systems with load-dependent service times (Q2023944) (← links)
- Decision making under uncertain and dependent system rates in service systems (Q2029984) (← links)
- Statistical theory powering data science (Q2194583) (← links)
- Modeling latent sources in call center arrival data (Q2267665) (← links)
- Forecasting time series of inhomogeneous Poisson processes with application to call center workforce management (Q2271338) (← links)
- Adaptive policies for perimeter surveillance problems (Q2286935) (← links)
- Call center service process analysis: Bayesian parametric and semi-parametric mixture modeling (Q2514772) (← links)
- Call center arrival modeling: A Bayesian state-space approach (Q2994799) (← links)
- FORECAST ERRORS IN SERVICE SYSTEMS (Q3645160) (← links)
- Rate-Based Daily Arrival Process Models with Application to Call Centers (Q5740227) (← links)
- Estimation and monitoring of traffic intensities with application to control of stochastic systems (Q6570568) (← links)
- Hierarchical nonparametric survival modeling for demand forecasting with fragmented categorical covariates (Q6574624) (← links)