Probabilistic forecasting of heterogeneous consumer transaction-sales time series
Year of publication: |
2020
|
---|---|
Authors: | Berry, Lindsay R. ; Helman, Paul ; West, Mike |
Published in: |
International journal of forecasting. - Amsterdam [u.a.] : Elsevier, ISSN 0169-2070, ZDB-ID 283943-X. - Vol. 36.2020, 2, p. 552-569
|
Subject: | Bayesian forecasting | Decouple/recouple | Dynamic binary cascade | Forecast calibration | Intermittent demand | Multi-scale forecasting | Predicting rare events | Sales per transaction | Supermarket sales forecasting | Prognoseverfahren | Forecasting model | Prognose | Forecast | Absatz | Sales | Lebensmitteleinzelhandel | Food retailing | Bayes-Statistik | Bayesian inference | Zeitreihenanalyse | Time series analysis | Marktforschung | Market research | Theorie | Theory | Nachfrage | Demand |
-
Bayesian forecasting of many count-valued time series
Berry, Lindsay R., (2020)
-
Bayesian forecasting of demand time-series data with zero values
Corberán-Vallet, Ana, (2013)
-
Romanus, Eduardo E., (2024)
- More ...
-
Bayesian forecasting of many count-valued time series
Berry, Lindsay R., (2020)
-
Bayesian Weibull Tree Models for Clinico-Genomic Prediction of Survival
Clarke, Jennifer, (2007)
-
Bayesian multi- and matrix-variate modelling: Graphical models and time series
Wang, Hao, (2010)
- More ...