£83.29

Wiley Uncertainty Analysis - High Dimensional Dependence Modelling

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Description

Mathematical models are essential for simulating complex real-world phenomena across various science and technology sectors. However, large complex models often rely on input values that are not known with certainty. This book by Wiley provides the necessary framework to quantify overall uncertainty within a model, helping problem owners make informed, model-based decisions. As interest in uncertainty analysis continues to grow, this text addresses the technical requirements of modern modeling. It covers essential topics including uncertainty and dependence elicitation, dependence modelling, and model inference. Readers will find detailed information on efficient sampling, screening, sensitivity analysis, and probabilistic inversion. This resource is designed to support researchers and professionals working with high dimensional dependence modelling to improve the accuracy and reliability of their simulations.

Key Features

Quantify model uncertainty to support better decision-making processes in science and technology applications.

Learn advanced techniques for uncertainty and dependence elicitation to improve model input accuracy.

Explore methods for dependence modelling and model inference to handle complex data relationships.

Gain knowledge on efficient sampling and screening methods to optimize computational resources.

Study sensitivity analysis and probabilistic inversion to understand model behavior and outcomes.

Product Specifications

Brand
Wiley
Format
hardcover
Domain
Amazon UK
Release Date
24 February 2006
Listed Since
13 December 2006

Barcode

No barcode data available

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