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Автор: V. Roshan Joseph
Издательство: CRC Press
Год: 2026
Страниц: 246
Язык: английский
Формат: pdf (true)
Размер: 45.3 MB
Theory, experiments, computation, and data are considered as the four pillars of science and engineering. Experimental Design for Data Science and Engineering describes efficient statistical methods for making the experiments cheaper and computations faster for extracting valuable information from data and help identify discrepancies in the theory. The book also includes recent advances in experimental designs for dealing with large amounts of observational data. Traditionally the design and analysis of physical and computer experiments are treated differently, but this book attempts to create a unified framework using Gaussian process models. Although optimal designs are formulated using Gaussian process models, the focus is on obtaining practical experimental designs that are robust to model assumptions. All the numerical illustrations in the book are reproducible using R and Python codes provided in the author’s GitHub site.
