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Applied Stochastic Models in Business and Industry

Artikelnummer: 9771526402005
Medium: Zeitschrift
ISSN / ISBN: 15264025
Verlag: John Wiley & Sons
Erscheinungsweise: 6 Ausgaben pro Jahr
Lieferfrist: bis zu 10 Tage
Applied Stochastic Models in Business and Industry is a peer-reviewed journal at the interface of stochastic modelling, data analysis and their applications in business, finance, insurance, management and production.

As the official journal of the International Society for Business and Industrial Statistics, our articles are mathematically rigorous, featuring innovative stochastic modelling and sound applications. We welcome technical and practical submissions on quality control, managerial processes, and supply chains and inventories.

Section on Data Science in Business and Industry
Data science is a publicly recognized label for problem-solving using ever-growing, large datasets and new data sources. This section will feature articles which address interesting problems in business and industry using innovative approaches and algorithms. Papers can present novel adaptations of existing methods as well as the development of new statistical methods in the context of an interesting application.

Practitioner’s Corner
Applied Stochastic Models in Business and Industry has an article type entitled Practitioner's Corner which serves two purposes. First, state-of-the-art stochastic models in business and industry are presented to practitioners, discussing their pros and cons, illustrating their use through examples, and making data and code available when possible. Second, this is a forum for practitioners to present innovative use of novel stochastic modeling in an interesting data based application in their business or industry.

Produkteigenschaften


  • Artikelnummer: 9771526402005
  • Medium: Zeitschrift
  • ISBN: 977-152640200-5
  • ISSN: 15264025
  • Verlag: John Wiley & Sons
  • Erscheinungsweise: 6 Ausgaben pro Jahr
  • Sprache(n): Englisch
  • Produktform: Other printed item
  • Ausgabetyp: Kein, Unbekannt