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

zbMATH Keywords

prediction intervalnonhomogeneous Poisson processnurse schedulingcall-centre forecastingdaily arrival patternpatient queue

Mathematics Subject Classification ID

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

• R
• RExcelInstaller

Cites Work

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• 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

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