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|a HCDD
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1 |
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|a Clarke, Brenton R.,
|e author.
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|a Robustness theory and application /
|c Brenton R. Clarke.
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| 264 |
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1 |
|a Hoboken, NJ :
|b John Wiley & Sons,
|c 2018.
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| 264 |
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4 |
|c ©2018
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| 300 |
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|a 1 online resource (xxiii, 215 pages)
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| 336 |
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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| 338 |
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|a online resource
|b cr
|2 rdacarrier
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| 490 |
0 |
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|a Wiley series in probability and statistics
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| 504 |
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|a Includes bibliographical references and index.
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| 505 |
0 |
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|a Introduction to asymptotic convergence -- The functional approach -- More results on differentiability -- Multiple roots -- Differentiability and bias reduction -- Minimum distance estimation and mixture estimation -- L-estimates and trimmed likelihood estimates -- Trimmed likelihood for multivariate data -- Further directions and conclusion.
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| 588 |
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|a Online resource; title from digital title page (viewed on July 13, 2018).
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| 520 |
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|a A preeminent expert in the field explores new and exciting methodologies in the ever-growing field of robust statistics Used to develop data analytical methods, which are resistant to outlying observations in the data, while capable of detecting outliers, robust statistics is extremely useful for solving an array of common problems, such as estimating location, scale, and regression parameters. Written by an internationally recognized expert in the field of robust statistics, this book addresses a range of well-established techniques while exploring, in depth, new and exciting methodologies. Local robustness and global robustness are discussed, and problems of non-identifiability and adaptive estimation are considered. Rather than attempt an exhaustive investigation of robustness, the author provides readers with a timely review of many of the most important problems in statistical inference involving robust estimation, along with a brief look at confidence intervals for location. Throughout, the author meticulously links research in maximum likelihood estimation with the more general M-estimation methodology. Specific applications and R and some MATLAB subroutines with accompanying data sets-available both in the text and online-are employed wherever appropriate. Providing invaluable insights and guidance, Robustness Theory and Application: -Offers a balanced presentation of theory and applications within each topic-specific discussion -Features solved examples throughout which help clarify complex and/or difficult concepts -Meticulously links research in maximum likelihood type estimation with the more general M-estimation methodology -Delves into new methodologies which have been developed over the past decade without stinting on coverage of "tried-and-true" methodologies -Includes R and some MATLAB subroutines with accompanying data sets, which help illustrate the power of the methods described Robustness Theory and Application is an important resource for all statisticians interested in the topic of robust statistics. This book encompasses both past and present research, making it a valuable supplemental text for graduate-level courses in robustness.
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| 650 |
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|a Robust statistics.
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| 650 |
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7 |
|a MATHEMATICS
|x Applied.
|2 bisacsh
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| 650 |
|
7 |
|a MATHEMATICS
|x Probability & Statistics
|x General.
|2 bisacsh
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| 650 |
|
7 |
|a Robust statistics
|2 fast
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| 758 |
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|i has work:
|a Robustness theory and application (Text)
|1 https://id.oclc.org/worldcat/entity/E39PCGgXMRKJd7pqyb6tDHw7gX
|4 https://id.oclc.org/worldcat/ontology/hasWork
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| 776 |
0 |
8 |
|i Print version:
|a Clarke, Brenton R.
|t Robustness theory and application.
|d Hoboken, NJ : John Wiley & Sons, 2018
|z 9781118669303
|w (DLC) 2018007658
|
| 856 |
4 |
0 |
|u https://ebookcentral.proquest.com/lib/holycrosscollege-ebooks/detail.action?docID=5434899
|y Click for online access
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| 880 |
0 |
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|6 505-00/(S
|a 48 2.6 Efficiency for Multivariate Parameters, 51 2.7 Other Approaches, 52 3 More Results on Differentiability 59 3.1 Further Results on Fréchet Differentiability, 59 3.2 M-Estimators: Their Introduction, 59 3.2.1 Non-Smooth Analysis and Conditions A', 61 3.2.2 Existence and Uniqueness for Solutions of Equations, 65 3.2.3 Results for M-estimators with Non-Smooth Ψ, 67 3.3 Regression M-Estimators, 70 3.4 Stochastic Fréchet Expansions and Further Considerations, 73 3.5 Locally Uniform Fréchet Expansion, 74 3.6 Concluding Remarks, 76 4 Multiple Roots 79 4.1 Introduction to Multiple Roots, 79 4.2 Asymptotics for Multiple Roots, 80 4.3 Consistency in the Face of Multiple Roots, 82 4.3.1 Preliminaries, 83 4.3.2 Asymptotic Properties of Roots and Tests, 92 4.3.3 Application of Asymptotic Theory,
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| 903 |
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|a EBC-AC
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|a 92
|b HCD
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