This IMA Volume in Mathematics and its Applications DIRECTIONS IN ROBUST STATISTICS AND DIAGNOSTICS is based on the proceedings of the first four weeks of the six week IMA 1989 summer program "Robustness, Diagnostics, Computing and Graphics in Statistics". An important objective of the organizers was to draw a broad set of statisticians working in robustness or diagnostics into collaboration on the challenging problems in these areas, particularly on the interface between them. We thank the organizers of the robustness and diagnostics program Noel Cressie, Thomas P. Hettmansperger, Peter J. Huber, R. Douglas Martin, and especially Werner Stahel and Sanford Weisberg who edited the proceedings. A vner Friedman Willard Miller, Jr. PREFACE Central themes of all statistics are estimation, prediction, and making decisions under uncertainty. A standard approach to these goals is through parametric mod elling. Parametric models can give a problem sufficient structure to allow standard, well understood paradigms to be applied to make the required inferences. If, how ever, the parametric model is not completely correct, then the standard inferential methods may not give reasonable answers. In the last quarter century, particularly with the advent of readily available computing, more attention has been paid to the problem of inference when the parametric model used is not correctly specified.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Directions in Robust Statistics and Diagnositcs: Part I.- Survey of robust procedures for survival data.- Simulated annealing for the detection of multiple outliers using least squares and least median of squares fitting.- Goodness of fit tests and long-range dependence.- A functional approach to robust nonparametric regression.- Added variable plots in linear regression.- Efficiency of reweighted least squares iterates.- An overview of small sample asymptotics.- Diagnostics, divergences and perturbation analysis.- Some mixed questions and comments on robustness.- Some research directions in rank-based inference.- Between robustness and diagnostics.- Dependence among observations: Consequences and methods to deal with it.- Local and deletion influence.- Outliers in time series analysis: Some comments on their impact and their detection.- Breakdown point and asymptotic properties of multivariate S-estimators and r-estimators: A Summary.- Algorithms and programs for robust linear regression.- Robust M-type testing procedures for linear models.- Recent results on bias-robust regression estimates.- Bias robust estimation of autoregression parameters.- Author index.
Book by None
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
Da: Brook Bookstore On Demand, Napoli, NA, Italia
Condizione: new. Questo è un articolo print on demand. Codice articolo R4BWW8ML13
Quantità: Più di 20 disponibili
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This IMA Volume in Mathematics and its Applications DIRECTIONS IN ROBUST STATISTICS AND DIAGNOSTICS is based on the proceedings of the first four weeks of the six week IMA 1989 summer program 'Robustness, Diagnostics, Computing and Graphics in Statistics'. An important objective of the organizers was to draw a broad set of statisticians working in robustness or diagnostics into collaboration on the challenging problems in these areas, particularly on the interface between them. We thank the organizers of the robustness and diagnostics program Noel Cressie, Thomas P. Hettmansperger, Peter J. Huber, R. Douglas Martin, and especially Werner Stahel and Sanford Weisberg who edited the proceedings. A vner Friedman Willard Miller, Jr. PREFACE Central themes of all statistics are estimation, prediction, and making decisions under uncertainty. A standard approach to these goals is through parametric mod elling. Parametric models can give a problem sufficient structure to allow standard, well understood paradigms to be applied to make the required inferences. If, how ever, the parametric model is not completely correct, then the standard inferential methods may not give reasonable answers. In the last quarter century, particularly with the advent of readily available computing, more attention has been paid to the problem of inference when the parametric model used is not correctly specified. 276 pp. Englisch. Codice articolo 9781461568636
Quantità: 2 disponibili
Da: Ria Christie Collections, Uxbridge, Regno Unito
Condizione: New. In. Codice articolo ria9781461568636_new
Quantità: Più di 20 disponibili
Da: moluna, Greven, Germania
Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This IMA Volume in Mathematics and its Applications DIRECTIONS IN ROBUST STATISTICS AND DIAGNOSTICS is based on the proceedings of the first four weeks of the six week IMA 1989 summer program Robustness, Diagnostics, Computing and Graphics in Statistics . . Codice articolo 4200174
Quantità: Più di 20 disponibili
Da: Revaluation Books, Exeter, Regno Unito
Paperback. Condizione: Brand New. reprint edition. 270 pages. 9.25x6.10x0.63 inches. In Stock. Codice articolo x-1461568633
Quantità: 2 disponibili
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This IMA Volume in Mathematics and its Applications DIRECTIONS IN ROBUST STATISTICS AND DIAGNOSTICS is based on the proceedings of the first four weeks of the six week IMA 1989 summer program 'Robustness, Diagnostics, Computing and Graphics in Statistics'. An important objective of the organizers was to draw a broad set of statisticians working in robustness or diagnostics into collaboration on the challenging problems in these areas, particularly on the interface between them. We thank the organizers of the robustness and diagnostics program Noel Cressie, Thomas P. Hettmansperger, Peter J. Huber, R. Douglas Martin, and especially Werner Stahel and Sanford Weisberg who edited the proceedings. A vner Friedman Willard Miller, Jr. PREFACE Central themes of all statistics are estimation, prediction, and making decisions under uncertainty. A standard approach to these goals is through parametric mod elling. Parametric models can give a problem sufficient structure to allow standard, well understood paradigms to be applied to make the required inferences. If, how ever, the parametric model is not completely correct, then the standard inferential methods may not give reasonable answers. In the last quarter century, particularly with the advent of readily available computing, more attention has been paid to the problem of inference when the parametric model used is not correctly specified.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 276 pp. Englisch. Codice articolo 9781461568636
Quantità: 1 disponibili
Da: AHA-BUCH GmbH, Einbeck, Germania
Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This IMA Volume in Mathematics and its Applications DIRECTIONS IN ROBUST STATISTICS AND DIAGNOSTICS is based on the proceedings of the first four weeks of the six week IMA 1989 summer program 'Robustness, Diagnostics, Computing and Graphics in Statistics'. An important objective of the organizers was to draw a broad set of statisticians working in robustness or diagnostics into collaboration on the challenging problems in these areas, particularly on the interface between them. We thank the organizers of the robustness and diagnostics program Noel Cressie, Thomas P. Hettmansperger, Peter J. Huber, R. Douglas Martin, and especially Werner Stahel and Sanford Weisberg who edited the proceedings. A vner Friedman Willard Miller, Jr. PREFACE Central themes of all statistics are estimation, prediction, and making decisions under uncertainty. A standard approach to these goals is through parametric mod elling. Parametric models can give a problem sufficient structure to allow standard, well understood paradigms to be applied to make the required inferences. If, how ever, the parametric model is not completely correct, then the standard inferential methods may not give reasonable answers. In the last quarter century, particularly with the advent of readily available computing, more attention has been paid to the problem of inference when the parametric model used is not correctly specified. Codice articolo 9781461568636
Quantità: 1 disponibili