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200210 ||| eng |
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|a 9780470316481
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| 050 |
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4 |
|a QA276
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| 100 |
1 |
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|a Robert J. Serfling
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| 245 |
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|a Approximation Theorems of Mathematical Statistics
|h Elektronische Ressource
|c Serfling, Robert J.
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| 250 |
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|a 1st edition
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| 260 |
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|a Hoboken
|b John Wiley & Sons
|c 1980, ©1980
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| 300 |
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|a xiv, 371 pages
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| 653 |
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|a Statistische methoden
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| 653 |
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|a Probability & Statistics
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| 653 |
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|a Statistik
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| 653 |
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|a 740Limiettheorema's
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| 653 |
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|a Probabilidade (estatistica)
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| 653 |
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|a Estatistica
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| 653 |
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|a Limit theorems (Probability theory)
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| 653 |
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|a Mathematical statistics
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| 653 |
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|a Mathematics
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| 653 |
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|a Statistique mathématique
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| 653 |
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|a Théorèmes limites (Théorie des probabilités)
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| 653 |
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|a Statistiek
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b WILOB
|a Wiley Online Books
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| 490 |
0 |
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|a Wiley Series in Probability and Statistics
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| 028 |
5 |
0 |
|a 10.1002/9780470316481
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| 776 |
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|z 0-471-21927-4
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| 776 |
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|z 9780471024033
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| 856 |
4 |
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|u https://onlinelibrary.wiley.com/book/10.1002/9780470316481
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| 082 |
0 |
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|a 519.5
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| 520 |
3 |
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|a This convenient paperback edition makes a seminal text in statistics accessible to a new generation of students and practitioners. Approximation Theorems of Mathematical Statistics covers a broad range of limit theorems useful in mathematical statistics, along with methods of proof and techniques of application. The manipulation of "probability" theorems to obtain "statistical" theorems is emphasized. Besides a knowledge of these basic statistical theorems, this lucid introduction to the subject imparts an appreciation of the instrumental role of probability theory. -- The book makes accessible to students and practicing professionals in statistics, general mathematics, operations research, and engineering the essentials of: -- * The tools and foundations that are basic to asymptotic theory in statistics -- * The asymptotics of statistics computed from a sample, including transformations of vectors of more basic statistics, with emphasis on asymptotic distribution theory and strong convergence -- * Important special classes of statistics, such as maximum likelihood estimates and other asymptotic efficient procedures; W. Hoeffding's U-statistics and R. von Mises's "differentiable statistical functions" -- * Statistics obtained as solutions of equations ("M-estimates"), linear functions of order statistics ("L-statistics"), and rank statistics ("R-statistics") -- * Use of influence curves -- * Approaches toward asymptotic relative efficiency of statistical test procedures
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