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Gebunden. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. KlappentextrnrnUncertainty quantification may appear daunting for practitioners due to its inherent complexity but can be intriguing and rewarding for anyone with mathematical ambitions and genuine concern for modeling quality. Uncertainty quant.

Gebunden. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. KlappentextrnrnStatistical practices have recently been questioned by numerous independent authors, to the extent that a significant fraction of accepted research findings can be questioned. This suggests that statistical methodologies may have .

Buch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -A numerical simulation is a computing calculation following a program that develops a mathematical model for a physical, social, economic, or biological system. Numerical simulations are required for analyzing and studying the behavior of systems whose mathematical models are very complex, as in the case of nonlinear systems. Capturing the resulting uncertainty of models based on uncertain parameters and constraints in confidence intervals (1-D), or more generally (>1-D) confidence regions, is very common for expressing to which degree the computed result is believed to be consistent with possible values of the targeted observable. This book examines the different methods used in numerical simulations, including adaptive and stochastic methods as well as finite element analysis research. This work is accompanied by studies of confidence regions, often utilized to express the credibility of such calculations and simulations. 290 pp. Englisch.

Buch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Statistical practices have recently been questioned by numerous independent authors, to the extent that a significant fraction of accepted research findings can be questioned. This suggests that statistical methodologies may have gone too far into an engineering practice, with minimal concern for their foundation, interpretation, assumptions, and limitations, which may be jeopardized in the current context. Disguised by overwhelming data sets, advanced processing, and stunning presentations, the basic approach is often intractable to anyone but the analyst. The hierarchical nature of statistical inference, exemplified by Bayesian aggregation of prior and derived knowledge, may also be challenging. Conceptual simplified studies of the kind presented in this book could therefore provide valuable guidance when developing statistical methodologies, but also applying state of the art with greater confidence. 158 pp. Englisch.

Buch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Uncertainty quantification may appear daunting for practitioners due to its inherent complexity but can be intriguing and rewarding for anyone with mathematical ambitions and genuine concern for modeling quality. Uncertainty quantification is what remains to be done when too much credibility has been invested in deterministic analyses and unwarranted assumptions. Model calibration describes the inverse operation targeting optimal prediction and refers to inference of best uncertain model estimates from experimental calibration data. The limited applicability of most state-of-the-art approaches to many of the large and complex calculations made today makes uncertainty quantification and model calibration major topics open for debate, with rapidly growing interest from both science and technology, addressing subtle questions such as credible predictions of climate heating. 226 pp. Englisch.

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Hardback. Zustand: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

Buch. Zustand: Neu. Uncertainty Quantification and Model Calibration | Jan Peter Hessling | Buch | 226 S. | Englisch | 2017 | IntechOpen | EAN 9789535132790 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu Print on Demand.

Buch. Zustand: Neu. Statistical Methodologies | Jan Peter Hessling | Buch | Gebunden | Englisch | 2020 | IntechOpen | EAN 9781789239973 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.

Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. KlappentextrnrnA numerical simulation is a computing calculation following a program that develops a mathematical model for a physical, social, economic, or biological system. Numerical simulations are required for analyzing and studying the beh.

Buch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Uncertainty quantification may appear daunting for practitioners due to its inherent complexity but can be intriguing and rewarding for anyone with mathematical ambitions and genuine concern for modeling quality. Uncertainty quantification is what remains to be done when too much credibility has been invested in deterministic analyses and unwarranted assumptions. Model calibration describes the inverse operation targeting optimal prediction and refers to inference of best uncertain model estimates from experimental calibration data. The limited applicability of most state-of-the-art approaches to many of the large and complex calculations made today makes uncertainty quantification and model calibration major topics open for debate, with rapidly growing interest from both science and technology, addressing subtle questions such as credible predictions of climate heating.Books on Demand GmbH, Überseering 33, 22297 Hamburg 226 pp. Englisch.

Buch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -A numerical simulation is a computing calculation following a program that develops a mathematical model for a physical, social, economic, or biological system. Numerical simulations are required for analyzing and studying the behavior of systems whose mathematical models are very complex, as in the case of nonlinear systems. Capturing the resulting uncertainty of models based on uncertain parameters and constraints in confidence intervals (1-D), or more generally (>1-D) confidence regions, is very common for expressing to which degree the computed result is believed to be consistent with possible values of the targeted observable. This book examines the different methods used in numerical simulations, including adaptive and stochastic methods as well as finite element analysis research. This work is accompanied by studies of confidence regions, often utilized to express the credibility of such calculations and simulations.Books on Demand GmbH, Überseering 33, 22297 Hamburg 290 pp. Englisch.

Buch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Statistical practices have recently been questioned by numerous independent authors, to the extent that a significant fraction of accepted research findings can be questioned. This suggests that statistical methodologies may have gone too far into an engineering practice, with minimal concern for their foundation, interpretation, assumptions, and limitations, which may be jeopardized in the current context. Disguised by overwhelming data sets, advanced processing, and stunning presentations, the basic approach is often intractable to anyone but the analyst. The hierarchical nature of statistical inference, exemplified by Bayesian aggregation of prior and derived knowledge, may also be challenging. Conceptual simplified studies of the kind presented in this book could therefore provide valuable guidance when developing statistical methodologies, but also applying state of the art with greater confidence.Books on Demand GmbH, Überseering 33, 22297 Hamburg 158 pp. Englisch.

Buch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Statistical practices have recently been questioned by numerous independent authors, to the extent that a significant fraction of accepted research findings can be questioned. This suggests that statistical methodologies may have gone too far into an engineering practice, with minimal concern for their foundation, interpretation, assumptions, and limitations, which may be jeopardized in the current context. Disguised by overwhelming data sets, advanced processing, and stunning presentations, the basic approach is often intractable to anyone but the analyst. The hierarchical nature of statistical inference, exemplified by Bayesian aggregation of prior and derived knowledge, may also be challenging. Conceptual simplified studies of the kind presented in this book could therefore provide valuable guidance when developing statistical methodologies, but also applying state of the art with greater confidence.

Buch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Uncertainty quantification may appear daunting for practitioners due to its inherent complexity but can be intriguing and rewarding for anyone with mathematical ambitions and genuine concern for modeling quality. Uncertainty quantification is what remains to be done when too much credibility has been invested in deterministic analyses and unwarranted assumptions. Model calibration describes the inverse operation targeting optimal prediction and refers to inference of best uncertain model estimates from experimental calibration data. The limited applicability of most state-of-the-art approaches to many of the large and complex calculations made today makes uncertainty quantification and model calibration major topics open for debate, with rapidly growing interest from both science and technology, addressing subtle questions such as credible predictions of climate heating.

Buch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - A numerical simulation is a computing calculation following a program that develops a mathematical model for a physical, social, economic, or biological system. Numerical simulations are required for analyzing and studying the behavior of systems whose mathematical models are very complex, as in the case of nonlinear systems. Capturing the resulting uncertainty of models based on uncertain parameters and constraints in confidence intervals (1-D), or more generally (>1-D) confidence regions, is very common for expressing to which degree the computed result is believed to be consistent with possible values of the targeted observable. This book examines the different methods used in numerical simulations, including adaptive and stochastic methods as well as finite element analysis research. This work is accompanied by studies of confidence regions, often utilized to express the credibility of such calculations and simulations.

Buch. Zustand: Neu. Recent Advances in Numerical Simulations | Francisco Bulnes (u. a.) | Buch | Gebunden | Englisch | 2021 | IntechOpen | EAN 9781839681684 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.