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180505 ||| eng |
| 020 |
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|a 9781139020893
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| 050 |
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4 |
|a QA278.8
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| 100 |
1 |
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|a Groeneboom, P.
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| 245 |
0 |
0 |
|a Nonparametric estimation under shape constraints
|b estimators, algorithms, and asymptotics
|c Piet Groeneboom, Delft University of Technology, Geurt Jongbloed, Delft University of Technology
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| 260 |
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|a Cambridge
|b Cambridge University Press
|c 2014
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| 300 |
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|a xi, 416 pages
|b digital
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| 653 |
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|a Nonparametric statistics
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| 653 |
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|a Multivariate analysis
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| 653 |
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|a Mathematical statistics
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| 653 |
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|a Estimation theory
|
| 700 |
1 |
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|a Jongbloed, Geurt
|e [author]
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b CBO
|a Cambridge Books Online
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| 490 |
0 |
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|a Cambridge series on statistical and probabilistic mathematics
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| 028 |
5 |
0 |
|a 10.1017/CBO9781139020893
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| 856 |
4 |
0 |
|u https://doi.org/10.1017/CBO9781139020893
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 519.54
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| 520 |
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|a This book treats the latest developments in the theory of order-restricted inference, with special attention to nonparametric methods and algorithmic aspects. Among the topics treated are current status and interval censoring models, competing risk models, and deconvolution. Methods of order restricted inference are used in computing maximum likelihood estimators and developing distribution theory for inverse problems of this type. The authors have been active in developing these tools and present the state of the art and the open problems in the field. The earlier chapters provide an introduction to the subject, while the later chapters are written with graduate students and researchers in mathematical statistics in mind. Each chapter ends with a set of exercises of varying difficulty. The theory is illustrated with the analysis of real-life data, which are mostly medical in nature
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