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  • 1
    Online Resource
    Online Resource
    New York, NY :Springer New York :
    UID:
    almahu_9947362853202882
    Format: XIII, 287 p. , online resource.
    Edition: Second Edition.
    ISBN: 9781461211662
    Series Statement: Springer Series in Statistics,
    Content: by Sara van de Geer. Also, we did not include material due to David Donoho, lain Johnstone, and their school. We found our­ selves unprepared to write a distillate of the material. We did touch briefly on "nonparametrics," but not on "semiparamet­ rics." This is because we feel that the semiparametric situation has not yet been properly structured. We hope that the reader will find this book interesting and challenging, in spite of its shortcomings. The material was typed in LaTeX form by the authors them­ selves, borrowing liberally from the 1990 script by Chris Bush. It was reviewed anonymously by distinguished colleagues. We thank them for their kind encouragement. Very special thanks are due to Professor David Pollard who took time out of a busy schedule to give us a long list of suggestions. We did not follow them all, but we at least made attempts. We wish also to thank the staff of Springer-Verlag for their help, in particular editor John Kimmel, who tried to make us work with all deliberate speed. Thanks are due to Paul Smith, Te-Ching Chen and Ju-Yi-Yen, who helped with the last-minute editorial corrections.
    Note: 1 Introduction -- 2 Experiments, Deficiencies, Distances v -- 2.1 Comparing Risk Functions -- 2.2 Deficiency and Distance between Experiments -- 2.3 Likelihood Ratios and Blackwell's Representation -- 2.4 Further Remarks on the Convergence of Distri butions of Likelihood Ratios -- 2.5 Historical Remarks -- 3 Contiguity — Hellinger Transforms -- 3.1 Contiguity -- 3.2 Hellinger Distances, Hellinger Transforms -- 3.3 Historical Remarks -- 4 Gaussian Shift and Poisson Experiments -- 4.1 Introduction -- 4.2 Gaussian Experiments -- 4.3 Poisson Experiments -- 4.4 Historical Remarks -- 5 Limit Laws for Likelihood Ratios -- 5.1 Introduction -- 5.2 Auxiliary Results -- 5.3 Limits for Binary Experiments -- 5.4 Gaussian Limits -- 5.5 Historical Remarks -- 6 Local Asymptotic Normality -- 6.1 Introduction -- 6.2 Locally Asymptotically Quadratic Families -- 6.3 A Method of Construction of Estimates -- 6.4 Some Local Bayes Properties -- 6.5 Invariance and Regularity -- 6.6 The LAMN and LAN Conditions -- 6.7 Additional Remarks on the LAN Conditions -- 6.8 Wald's Tests and Confidence Ellipsoids -- 6.9 Possible Extensions -- 6.10 Historical Remarks -- 7 Independent, Identically Distributed Observations -- 7.1 Introduction -- 7.2 The Standard i.i.d. Case: Differentiability in Quadratic Mean -- 7.3 Some Examples -- 7.4 Some Nonparametric Considerations -- 7.5 Bounds on the Risk of Estimates -- 7.6 Some Cases Where the Number of Observations Is Random -- 7.7 Historical Remarks -- 8 On Bayes Procedures -- 8.1 Introduction -- 8.2 Bayes Procedures Behave Nicely -- 8.3 The Bernstein—von Mises Phenomenon -- 8.4 A Bernstein—von Mises Result for the i.i.d. Case -- 8.5 Bayes Procedures Behave Miserably -- 8.6 Historical Remarks -- Author Index.
    In: Springer eBooks
    Additional Edition: Printed edition: ISBN 9781461270300
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Online Resource
    Online Resource
    New York, NY : Springer New York
    UID:
    b3kat_BV042419773
    Format: 1 Online-Ressource (XIII, 287 p)
    Edition: Second Edition
    ISBN: 9781461211662 , 9781461270300
    Series Statement: Springer Series in Statistics
    Note: by Sara van de Geer. Also, we did not include material due to David Donoho, lain Johnstone, and their school. We found our­ selves unprepared to write a distillate of the material. We did touch briefly on "nonparametrics," but not on "semiparamet­ rics." This is because we feel that the semiparametric situation has not yet been properly structured. We hope that the reader will find this book interesting and challenging, in spite of its shortcomings. The material was typed in LaTeX form by the authors them­ selves, borrowing liberally from the 1990 script by Chris Bush. It was reviewed anonymously by distinguished colleagues. We thank them for their kind encouragement. Very special thanks are due to Professor David Pollard who took time out of a busy schedule to give us a long list of suggestions. We did not follow them all, but we at least made attempts. We wish also to thank the staff of Springer-Verlag for their help, in particular editor John Kimmel, who tried to make us work with all deliberate speed. Thanks are due to Paul Smith, Te-Ching Chen and Ju-Yi-Yen, who helped with the last-minute editorial corrections
    Language: English
    Keywords: Statistik ; Asymptotik ; Asymptotische Statistik
    Library Location Call Number Volume/Issue/Year Availability
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  • 3
    Online Resource
    Online Resource
    New York, NY : Springer
    UID:
    gbv_1655389122
    Format: Online-Ressource (XIII, 287 p, online resource)
    Edition: Second Edition
    ISBN: 9781461211662
    Series Statement: Springer Series in Statistics
    Content: This volume is the second edition of a work that presents a coherent introduction to the subject of asymptotic statistics as it has developed in the past 50 years. The second edition differs from the first in that it has been made more 'reader friendly'. It also includes a new chapter, Chapter 4, on Gaussian and Poisson experiments because of their growing role in the field, especially in nonparametrics and semi-parametrics. Most of the subsequent chapters have been entirely rewritten and the nonparametrics of Chapter 7 have been ampliefied. Much of the material has been taught in a second year graduate course at Berkeley for 30 years. It represents a link between traditional material including maximum likelihood, and Wald's Theory of Statistical Decision Functions together with comparison and distances for experiments. This volume is not intended to replace monographs on specialized subjects, but it will help to place them in a coherent perspective. Lucien Le Cam is Professor of Statistics and Mathematics (Emeritus) at the University of California, Berkeley. He is the author of numerous papers on asymptotics and Asymptotic Methods in Statistical Decision Theory, Springer Verlag (1986). He was co-editor, with J. Neyman and E. Scott of the Berkeley Symposia on Mathematical Statistics and Probability. Grace Lo Yang is Professor, Department of Mathematics, University of Maryland, College Park. She is a long time holder of a Faculty Appointment at the National Institute of Standards and Technology, Gaithersburg, MD. Her research activities include stochastic modeling in physical sciences and theory of incomplete data
    Additional Edition: ISBN 9781461270300
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-146-127-030-0
    Language: English
    URL: Volltext  (lizenzpflichtig)
    URL: Cover
    Author information: Le Cam, Lucien M. 1924-
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