The Design and Analysis of Computer Experiments (Springer Series in Statistics)
暫譯: 計算實驗的設計與分析（斯普林格統計系列）
Thomas J. Santner, Brian J. Williams, William I. Notz
- 出版商: Springer
- 出版日期: 2019-01-09
- 售價: $6,000
- 貴賓價: 9.5 折 $5,700
- 語言: 英文
- 頁數: 436
- 裝訂: Hardcover
- ISBN: 149398845X
- ISBN-13: 9781493988457
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相關分類:
機率統計學 Probability-and-statistics
海外代購書籍(需單獨結帳)
相關主題
商品描述
This book describes methods for designing and analyzing experiments that are conducted using a computer code, a computer experiment, and, when possible, a physical experiment. Computer experiments continue to increase in popularity as surrogates for and adjuncts to physical experiments. Since the publication of the first edition, there have been many methodological advances and software developments to implement these new methodologies. The computer experiments literature has emphasized the construction of algorithms for various data analysis tasks (design construction, prediction, sensitivity analysis, calibration among others), and the development of web-based repositories of designs for immediate application. While it is written at a level that is accessible to readers with Masters-level training in Statistics, the book is written in sufficient detail to be useful for practitioners and researchers.
New to this revised and expanded edition:
• An expanded presentation of basic material on computer experiments and Gaussian processes with additional simulations and examples
• A new comparison of plug-in prediction methodologies for real-valued simulator output
• An enlarged discussion of space-filling designs including Latin Hypercube designs (LHDs), near-orthogonal designs, and nonrectangular regions
• A chapter length description of process-based designs for optimization, to improve good overall fit, quantile estimation, and Pareto optimization
• A new chapter describing graphical and numerical sensitivity analysis tools
• Substantial new material on calibration-based prediction and inference for calibration parameters
• Lists of software that can be used to fit models discussed in the book to aid practitioners
商品描述(中文翻譯)
這本書描述了使用電腦程式碼進行的實驗設計和分析方法，包括電腦實驗，並在可能的情況下進行實體實驗。隨著電腦實驗作為實體實驗的替代品和輔助工具的受歡迎程度不斷上升，自第一版出版以來，已經有許多方法論的進展和軟體的開發來實現這些新方法論。電腦實驗文獻強調了為各種數據分析任務（設計構建、預測、敏感度分析、校準等）構建算法的重要性，以及開發基於網路的設計庫以便立即應用。雖然本書的寫作水平適合具有碩士級統計訓練的讀者，但內容詳細到足以對實務工作者和研究人員有用。
本修訂和擴充版的新內容包括：
• 擴展了有關電腦實驗和高斯過程的基本材料，並增加了模擬和範例
• 新增了對實值模擬器輸出的插入預測方法的比較
• 擴大了對空間填充設計的討論，包括拉丁超立方設計（LHDs）、近正交設計和非矩形區域
• 對基於過程的優化設計進行了章節長度的描述，以改善整體擬合、分位數估計和帕累托優化
• 新增了一章描述圖形和數值敏感度分析工具
• 大量新增有關基於校準的預測和校準參數推斷的材料
• 列出可以用來擬合書中討論模型的軟體，以幫助實務工作者
作者簡介
Thomas J. Santner is Professor Emeritus in the Department of Statistics at The Ohio State University. At Ohio State, he has served as department Chair and Director of the Department's Statistical Consulting Service. Previously, he was a professor in the School of Operations Research and Industrial Engineering at Cornell University. His research interests include the design and analysis of experiments, particularly those involving computer simulators, Bayesian inference, and the analysis of discrete response data. He is a Fellow of the American Statistical Association, the Institute of Mathematical Statistics, the American Association for the Advancement of Science, and is an elected ordinary member of the International Statistical Institute. He has held visiting appointments at the National Cancer Institute, the University of Washington, Ludwig Maximilians Universität (Munich, Germany), the National Institute of Statistical Science (NISS), and the Isaac Newton Institute (Cambridge, England).
Brian J. Williams has been Statistician at the Los Alamos National Laboratory RAND Corporation since 2003. His research interests include experimental design, computer experiments, Bayesian inference, spatial statistics and statistical computing. Williams was named a Fellow of the American Statistical Association in 2015 and is also the recipient of the Los Alamos Achievement Award for his leadership role in the Consortium for Advanced Simulation of Light Water Reactors (CASL) Program. He holds a doctorate in statistics from The Ohio State University.
William I. Notz is Professor Emeritus in the Department of Statistics at The Ohio State University. At Ohio State, he has served as acting department chair, associate dean of the College of Mathematical and Physical Sciences, and as director of the department's Statistical Consulting Service. His research focuses on experimental designs for computer experiments and he is particularly interested in sequential strategies for selecting points at which to run a computer simulator in order to optimize some performance measure related to the objectives of the computer experiment. A Fellow of the American Statistical Association, Notz has also served as Editor of the journals Technometrics and the Journal of Statistics Education.
作者簡介(中文翻譯)
湯瑪斯·J·桑特納是俄亥俄州立大學統計系的名譽教授。在俄亥俄州立大學，他曾擔任系主任及該系統計諮詢服務的主任。之前，他是康奈爾大學運籌學與工業工程學院的教授。他的研究興趣包括實驗的設計與分析，特別是涉及計算機模擬器的實驗、貝葉斯推斷以及離散反應數據的分析。他是美國統計協會、數學統計學會、美國科學促進會的會士，並且是國際統計學會的當選普通會員。他曾在國家癌症研究所、華盛頓大學、慕尼黑路德維希·馬克西米利安大學、國家統計科學研究所（NISS）以及艾薩克·牛頓研究所（劍橋，英國）擔任訪問職位。
布萊恩·J·威廉斯自2003年以來一直擔任洛斯阿拉莫斯國家實驗室RAND公司統計師。他的研究興趣包括實驗設計、計算機實驗、貝葉斯推斷、空間統計學和統計計算。威廉斯於2015年被評選為美國統計協會的會士，並因其在輕水反應堆高級模擬聯盟（CASL）計劃中的領導角色而獲得洛斯阿拉莫斯成就獎。他擁有俄亥俄州立大學的統計學博士學位。
威廉·I·諾茲是俄亥俄州立大學統計系的名譽教授。在俄亥俄州立大學，他曾擔任代理系主任、數學與物理科學學院的副院長，以及該系統計諮詢服務的主任。他的研究專注於計算機實驗的實驗設計，特別對於選擇運行計算機模擬器的點的序列策略感興趣，以優化與計算機實驗目標相關的某些性能指標。諾茲是美國統計協會的會士，並曾擔任期刊Technometrics和Journal of Statistics Education的編輯。
