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Parametric and Nonparametric Inference from Record-Breaking Data (Lecture Notes in Statistics, 172) - Softcover
Synopsis
By providing a comprehensive look at statistical inference from record-breaking data in both parametric and nonparametric settings, this book treats the area of nonparametric function estimation from such data in detail.
Its main purpose is to fill this void on general inference from record values.
Statisticians, mathematicians, and engineers will find the book useful as a research reference. It can also serve as part of a graduate-level statistics or mathematics course.
"synopsis" may belong to another edition of this title.
Review
New record values in sports, finances, climate, ... are of interest to most people, and for about half a century, probabilists and statisticians have taken up the challenge of modelling their behaviour. The present monograph provides results on statistical inference problems for record-breaking data. For example: how to fit a parametric or nonparametric model to such data? Or also: how to predict the next record, based on the values of the past records. The main body of the book (Chapters 4-7) is a discussion of all the known work on nonparametric inference for this type of data.
The book will be a useful reference for researchers in this area. There could also be interest from engineers working in destructive stress testing and quality control.
ISI Short Book Reviews, Vol. 23/2, August 2003
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Parametric and Nonparametric Inference from Record-Breaking Data
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Parametric and Nonparametric Inference from Record-Breaking Data.
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XI, 113 p. Softcover Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Lecture Notes in Statistics, 172. Sprache: Englisch. Seller Inventory # 36898HB
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Parametric and Nonparametric Inference from Record-Breaking Data
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Parametric and Nonparametric Inference from Record-Breaking Data
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Springer New York Jan 2003, 2003
ISBN 10: 0387001387
ISBN 13: 9780387001388
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -By providing a comprehensive look at statistical inference from record-breaking data in both parametric and nonparametric settings, this book treats the area of nonparametric function estimation from such data in detail. Its main purpose is to fill this void on general inference from record values. Statisticians, mathematicians, and engineers will find the book useful as a research reference. It can also serve as part of a graduate-level statistics or mathematics course. 128 pp. Englisch. Seller Inventory # 9780387001388
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Parametric and Nonparametric Inference from Record-Breaking Data
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Parametric and Nonparametric Inference from Record-Breaking Data
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ISBN 10: 0387001387
ISBN 13: 9780387001388
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Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. By providing a comprehensive look at statistical inference from record-breaking data in both parametric and nonparametric settings, this book treats the area of nonparametric function estimation from such data in detail. Its main purpose is to fil. Seller Inventory # 5908814
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Parametric and Nonparametric Inference from Record-Breaking Data
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - As statisticians, we are constantly trying to make inferences about the underlying population from which data are observed. This includes estimation and prediction about the underlying population parameters from both complete and incomplete data. Recently, methodology for estimation and prediction from incomplete data has been found useful for what is known as 'record-breaking data,' that is, data generated from setting new records. There has long been a keen interest in observing all kinds of records-in particular, sports records, financial records, flood records, and daily temperature records, to mention a few. The well-known Guinness Book of World Records is full of this kind of record information. As usual, beyond the general interest in knowing the last or current record value, the statistical problem of prediction of the next record based on past records has also been an important area of record research. Probabilistic and statistical models to describe behavior and make predictions from record-breaking data have been developed only within the last fifty or so years, with a relatively large amount of literature appearing on the subject in the last couple of decades. This book, written from a statistician's perspective, is not a compilation of 'records,' rather, it deals with the statistical issues of inference from a type of incomplete data, record-breaking data, observed as successive record values (maxima or minima) arising from a phenomenon or situation under study. Prediction is just one aspect of statistical inference based on observed record values. Seller Inventory # 9780387001388
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