文件名称：Uncertainty Analysis of Experimental Data with R
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更新时间：2022-01-29 18:23:30
Analysis，R
Uncertainty Analysis of Experimental Data with R By 作者: Benjamin David Shaw ISBN-10 书号: 1498797326 ISBN-13 书号: 9781498797320 Edition 版本: 1 出版日期: 2017-07-10 pages 页数: 331 The books discusses both basic and more complex methods including linear regression, nonlinear regression, and kernel smoothing curve fits, as well as Taylor Series, Monte Carlo and Bayesian approaches. Features: 1. Extensive use of modern open source software (R). 2. Many code examples are provided. 3. The uncertainty analyses conform to accepted professional standards (ASME). 4. The book is self-contained and includes all necessary material including chapters on statistics and programming in R. Benjamin D. Shaw is a professor in the Mechanical and Aerospace Engineering Department at the University of California, Davis. His research interests are primarily in experimental and theoretical aspects of combustion. Along with other courses, he has taught undergraduate and graduate courses on engineering experimentation and uncertainty analysis. He has published widely in archival journals and became an ASME Fellow in 2003. Contents Chapter 1.Introduction Chapter 2.Aspects Of R Chapter 3.Statistics Chapter 4.Curve Fits Chapter 5.Uncertainty Of A Measured Quantity Chapter 6.Uncertainty Of A Result Calculated Using Experimental Data Chapter 7.Taylor Series Uncertainty Of A Linear Regression Curve Fit Chapter 8.Monte Carlo Methods Chapter 9.The Bayesian Approach Appendix: Probability Density Functions