Judgmental Forecasting (15 results)

Condition: gut. IX, 293 S., Abb., 23 cm, Bibliotheksexemplar, Ecke geknickt. Sprache: Englisch.

Condition: Fair. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. Book contains pencil markings. In fair condition, suitable as a study copy. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,600grams, ISBN:9780471913276.

Condition: Fair. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In fair condition, suitable as a study copy. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,650grams, ISBN:9780471913276.

Condition: Fair. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In fair condition, suitable as a study copy. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,650grams, ISBN:9780471913276.

Condition: Gut. 304 Seiten Exemplar aus einer wissenchaftlichen Bibliothek Altersfreigabe FSK ab 0 Jahre Sprache: Englisch Gewicht in Gramm: 969 24,4 x 16,0 x 2,6 cm, Gebundene Ausgabe.

Condition: New. pp. 308.

Taschenbuch. Condition: Neu. Integration of Judgmental and Statistical Approaches to Forecasting | Error metrics, visual tools, handling unaided judgment, analysis of judgmental adjustments, joint Bayesian modelling | Andrey Davydenko | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786203471229 | Verantwortliche Person für die EU: LAP Lambert Academic Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.

paperback. Condition: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -When it comes to forecasting, it's important to know how good your forecasting is and if there are ways to improve it. This work focuses on finding reliable and informative indicators of forecasting performance and on how to improve forecasts with the use of judgment. Chapter 2 explores limitations of various error measures and introduces a new class of metrics (AvgRel-metrics) for measuring forecasting performance using the following rules: i) relative indicators are averaged across series using the weighted geometric mean, ii) an indicator used to evaluate forecasts must correspond to the loss function used to optimize forecasts. The AvgRelMSE and AvgRelMAE metrics are proposed to measure accuracy under quadratic and linear loss, respectively, and the AvgRelAME to measure bias. Boxplots of logs of relative indicators are used to visualize distributions. Chapters 3 and 4 look at models for handling unaided judgment & judgmental adjustments. In particular, this work introduces advanced models based on using panel data and Bayesian analysis. Chapter 5 proposes a novel approach allowing to incorporate judgment into a joint model and update forecasts as new data becomes available. 308 pp. Englisch.

Condition: New. Print on Demand pp. 308.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Davydenko AndreyAndrey has a rich experience of working as a data scientist/researcher on various projects, including credit scoring and the development of commercial software for business forecasting. He s a Microsoft Certified Solu.

Condition: New. PRINT ON DEMAND pp. 308.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book contains comprehensive analysis of the methods used in new product forecasting, which would provide higher accuracy in managerial practice. These methods include statistical, judgmental and combination methods. For ease of use in managerial practice the book maintains the simplicity in use of difficult concepts. A popular idea of using analogous product data for forecasting sales of a target product has been researched and evaluated. Three methods of new product forecasting were selected for this purpose and their suitability is compared with other existing methods and rigorous evaluation of academic research in this area is carried out and appropriate recommendation made. The selected methods balance sophistication with the easiness for the company managers to understand and use them. It contains the results of a practical research with real sales data in a high technology industry of the US market for the time period from 1946 up to present times. The book provides detailed analysis of the pros and cons of all the methods tested and may well serve as one of the essential resources for a forecasting manager.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -When it comes to forecasting, it's important to know how good your forecasting is and if there are ways to improve it. This work focuses on finding reliable and informative indicators of forecasting performance and on how to improve forecasts with the use of judgment. Chapter 2 explores limitations of various error measures and introduces a new class of metrics (AvgRel-metrics) for measuring forecasting performance using the following rules: i) relative indicators are averaged across series using the weighted geometric mean, ii) an indicator used to evaluate forecasts must correspond to the loss function used to optimize forecasts. The AvgRelMSE and AvgRelMAE metrics are proposed to measure accuracy under quadratic and linear loss, respectively, and the AvgRelAME to measure bias. Boxplots of logs of relative indicators are used to visualize distributions. Chapters 3 and 4 look at models for handling unaided judgment & judgmental adjustments. In particular, this work introduces advanced models based on using panel data and Bayesian analysis. Chapter 5 proposes a novel approach allowing to incorporate judgment into a joint model and update forecasts as new data becomes available.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 308 pp. Englisch.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - When it comes to forecasting, it's important to know how good your forecasting is and if there are ways to improve it. This work focuses on finding reliable and informative indicators of forecasting performance and on how to improve forecasts with the use of judgment. Chapter 2 explores limitations of various error measures and introduces a new class of metrics (AvgRel-metrics) for measuring forecasting performance using the following rules: i) relative indicators are averaged across series using the weighted geometric mean, ii) an indicator used to evaluate forecasts must correspond to the loss function used to optimize forecasts. The AvgRelMSE and AvgRelMAE metrics are proposed to measure accuracy under quadratic and linear loss, respectively, and the AvgRelAME to measure bias. Boxplots of logs of relative indicators are used to visualize distributions. Chapters 3 and 4 look at models for handling unaided judgment & judgmental adjustments. In particular, this work introduces advanced models based on using panel data and Bayesian analysis. Chapter 5 proposes a novel approach allowing to incorporate judgment into a joint model and update forecasts as new data becomes available.