Practical statistical methods for call centres with a case study addressing urgent medical care delivery
DOI10.1007/s10479-014-1529-2zbMath1359.62520OpenAlexW2010750816MaRDI QIDQ889569
S. G. Stirling, David A. Wooff
Publication date: 9 November 2015
Published in: Annals of Operations Research (Search for Journal in Brave)
Full work available at URL: http://dro.dur.ac.uk/11457/1/11457.pdf
prediction intervalnonhomogeneous Poisson processnurse schedulingcall-centre forecastingdaily arrival patternpatient queue
Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Deterministic scheduling theory in operations research (90B35) Case-oriented studies in operations research (90B90)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Forecasting emergency medical service call arrival rates
- Solving the multi-objective nurse scheduling problem with a weighted cost function
- Functional data analysis.
- Modeling Daily Arrivals to a Telephone Call Center
- Locally Weighted Regression: An Approach to Regression Analysis by Local Fitting
- Bayesian Forecasting of an Inhomogeneous Poisson Process With Applications to Call Center Data
- Robust Locally Weighted Regression and Smoothing Scatterplots
- Analysis of call centre arrival data using singular value decomposition
- Seasonal adjustment with the X-11 method
This page was built for publication: Practical statistical methods for call centres with a case study addressing urgent medical care delivery