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Publicado por Springer International Publishing AG, CH, 2022
ISBN 10: 3031124111 ISBN 13: 9783031124112
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Publicado por Springer International Publishing AG, Cham, 2022
ISBN 10: 3031124111 ISBN 13: 9783031124112
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Añadir al carritoPaperback. Condición: new. Paperback. This open access book discusses the statistical modeling of insurance problems, a process which comprises data collection, data analysis and statistical model building to forecast insured events that may happen in the future. It presents the mathematical foundations behind these fundamental statistical concepts and how they can be applied in daily actuarial practice. Statistical modeling has a wide range of applications, and, depending on the application, the theoretical aspects may be weighted differently: here the main focus is on prediction rather than explanation. Starting with a presentation of state-of-the-art actuarial models, such as generalized linear models, the book then dives into modern machine learning tools such as neural networks and text recognition to improve predictive modeling with complex features. Providing practitioners with detailed guidance on how to apply machine learning methods to real-world data sets, and how to interpret the results without losing sight of the mathematical assumptions on which these methods are based, the book can serve as a modern basis for an actuarial education syllabus. This open access book discusses the statistical modeling of insurance problems, a process which comprises data collection, data analysis and statistical model building to forecast insured events that may happen in the future. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Añadir al carritoCondición: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
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Librería: Revaluation Books, Exeter, Reino Unido
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Añadir al carritoPaperback. Condición: Brand New. 617 pages. 9.25x6.10x1.22 inches. In Stock.
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Publicado por Springer International Publishing AG, CH, 2022
ISBN 10: 3031124111 ISBN 13: 9783031124112
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Añadir al carritoPaperback. Condición: New. 1st ed. 2023.
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Publicado por Springer International Publishing AG, Cham, 2022
ISBN 10: 3031124111 ISBN 13: 9783031124112
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Añadir al carritoPaperback. Condición: new. Paperback. This open access book discusses the statistical modeling of insurance problems, a process which comprises data collection, data analysis and statistical model building to forecast insured events that may happen in the future. It presents the mathematical foundations behind these fundamental statistical concepts and how they can be applied in daily actuarial practice. Statistical modeling has a wide range of applications, and, depending on the application, the theoretical aspects may be weighted differently: here the main focus is on prediction rather than explanation. Starting with a presentation of state-of-the-art actuarial models, such as generalized linear models, the book then dives into modern machine learning tools such as neural networks and text recognition to improve predictive modeling with complex features. Providing practitioners with detailed guidance on how to apply machine learning methods to real-world data sets, and how to interpret the results without losing sight of the mathematical assumptions on which these methods are based, the book can serve as a modern basis for an actuarial education syllabus. This open access book discusses the statistical modeling of insurance problems, a process which comprises data collection, data analysis and statistical model building to forecast insured events that may happen in the future. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Librería: preigu, Osnabrück, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. Statistical Foundations of Actuarial Learning and its Applications | Mario V. Wüthrich (u. a.) | Taschenbuch | XII | Englisch | 2022 | Springer | EAN 9783031124112 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 49,09
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This open access book discusses the statistical modeling of insurance problems, a process which comprises data collection, data analysis and statistical model building to forecast insured events that may happen in the future. It presents the mathematical foundations behind these fundamental statistical concepts and how they can be applied in daily actuarial practice. Statistical modeling has a wide range of applications, and, depending on the application, the theoretical aspects may be weighted differently: here the main focus is on prediction rather than explanation. Starting with a presentation of state-of-the-art actuarial models, such as generalized linear models, the book then dives into modern machine learning tools such as neural networks and text recognition to improve predictive modeling with complex features. Providing practitioners with detailed guidance on how to apply machine learning methods to real-world data sets, and how to interpret the results without losing sight of the mathematical assumptions on which these methods are based, the book can serve as a modern basis for an actuarial education syllabus.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 41,76
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Añadir al carritoPaperback. Condición: Brand New. 617 pages. 9.25x6.10x1.22 inches. In Stock. This item is printed on demand.