Articoli correlati a Parametric and Nonparametric Inference from Record-Breaking...
Sinossi
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.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Recensione
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
Contenuti
1. Introduction.- 2. Preliminaries and Early Work.- 3. Parametric Inference.- 4. Nonparametric Inference—Genesis.- 5. Smooth Function Estimation.- 6. Bayesian Models.- 7. Record Models with Trend.- References.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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Parametric and Nonparametric Inference from Record-Breaking Data
Da: Buchpark, Trebbin, Germania
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Condizione: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher. Codice articolo 1160303/202
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Parametric and Nonparametric Inference from Record-Breaking Data.
Editore:
New York, Springer., 2003
ISBN 10: 0387001387
ISBN 13: 9780387001388
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Da: Universitätsbuchhandlung Herta Hold GmbH, Berlin, Germania
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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. Codice articolo 36898HB
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Parametric and Nonparametric Inference from Record-breaking Data.
Editore:
New York, NY, U.S.A. Springer-Verlag New York, Incorporated, 2003
ISBN 10: 0387001387
ISBN 13: 9780387001388
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Softcover
Da: CSG Onlinebuch GMBH, Darmstadt, Germania
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Softcover. Condizione: Gut. Gebraucht - Gut Zustand: Gut, Mängelexemplar, VIII, 113 p. 1 illus. About this book: This book provides a comprehensive look at statistical inference from record-breaking data in both parametric and nonparametric settings, including Bayesian inference. A unique feature is that it treats the area of nonparametric function estimation from such data in detail, gathering results on this topic to date in one accessible volume. Previous books on records have focused mainly on the probabilistic behavior of records, prediction of future records, and characterizations of the distributions of record values, addressing some inference methods only briefly. The main purpose of this book is to fill this void on general inference from record values. Statisticians, mathematicians, and engineers will find the book useful as a research reference and in learning about making inferences from record-breaking data. The book can also serve as part of a graduatelevel statistics or mathematics course, complementing material on the probabilistic aspects of record values. For a basic understanding of the statistical concepts, a one-year graduate course in mathematical statistics provides sufficient background. For a detailed understanding of the convergence theory of the nonparametric function estimators, a course in measure theory or probability theory at the graduate level is useful. Sneh Gulati is Associate Professor of Statistics at Florida International University in Miami. She is currently an associate editor of the Journal of Statistical Computation and Simulation and has published several articles in statistics. Currently she serves as the president of the South Florida Chapter of the American Statistical Association and is also the chair of the Florida Commission of Hurricane Loss Projection Methodology. William J. Padgett is Professor of Statistics and was the founding Chair of the Department of Statistics at the University of South Written for researchers None. Codice articolo 14032
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Parametric and Nonparametric Inference from Record-Breaking Data (Lecture Notes in Statistics)
Da: Orca Knowledge Systems, Inc., Novato, CA, U.S.A.
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Paperback. Condizione: Good. Volume 172 in series. No DJ. Ex University of California, Berkeley Math/Stat Library book with usual library markings. Binding is tight, text clean. No other marks in book. Appears unread. Softcover overbound with clear plastic hardcover. Codice articolo mon0000017869
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Parametric and Nonparametric Inference from Record-Breaking Data (Lecture Notes in Statistics)
Da: Orca Knowledge Systems, Inc., Novato, CA, U.S.A.
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Paperback. Condizione: Fine. Unread. A comprehensive look at statistical inference from record-breaking data in both parametric and nonparametric settings, including Bayesian inference. Chapters (7): Introduction; Preliminaries & Early Work; Parametric Inference; Nonparametric Inference-Genesis; Smooth Function Estimation; Bayesian Models; Record Models with Trend. Codice articolo 004072
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Parametric and Nonparametric Inference from Record-Breaking Data
Editore:
Springer New York, 2003
ISBN 10: 0387001387
ISBN 13: 9780387001388
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Da: moluna, Greven, Germania
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Kartoniert / Broschiert. Condizione: 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. Codice articolo 5908814
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Parametric and Nonparametric Inference from Record-Breaking Data
Editore:
Springer New York Jan 2003, 2003
ISBN 10: 0387001387
ISBN 13: 9780387001388
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Taschenbuch
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Taschenbuch. Condizione: 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. Codice articolo 9780387001388
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Parametric and Nonparametric Inference from Record-Breaking Data
Editore:
Springer New York, Springer New York Jan 2003, 2003
ISBN 10: 0387001387
ISBN 13: 9780387001388
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Taschenbuch
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Taschenbuch. Condizione: Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 128 pp. Englisch. Codice articolo 9780387001388
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Parametric and Nonparametric Inference from Record-Breaking Data (Lecture Notes in Statistics, 172)
Da: Ria Christie Collections, Uxbridge, Regno Unito
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Condizione: New. In. Codice articolo ria9780387001388_new
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Parametric and Nonparametric Inference from Record-Breaking Data
Da: GreatBookPrices, Columbia, MD, U.S.A.
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Condizione: New. Codice articolo 1823419-n
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