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Bayesian forecasting of an inhomogeneous Poisson process with applications to call center data
This article proposes a multiplicative model for modeling and forecasting within-day arrival rates to a US commercial bank's call center. Markov chain Monte Carlo sampling methods are used to estimate both latent states and model parameters.
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- http://id.worldcat.org/fast/1068210
- http://id.loc.gov/authorities/subjects/sh85103958
- http://id.loc.gov/authorities/subjects/sh96005575
- http://id.worldcat.org/fast/1010347
- http://id.worldcat.org/fast/829019
- http://id.loc.gov/authorities/subjects/sh85012506
- http://id.loc.gov/authorities/subjects/sh85081369
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- http://experiment.worldcat.org/entity/work/data/116402725#Organization/wharton_singapore_management_university_research_center
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- http://worldcat.org/entity/person/id/2718348045
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- "This article proposes a multiplicative model for modeling and forecasting within-day arrival rates to a US commercial bank's call center. Markov chain Monte Carlo sampling methods are used to estimate both latent states and model parameters."@en
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- "Bayesian forecasting of an inhomogeneous Poisson process with applications to call center data"@en