Mathematical Statistics Mathematical Statistics
Springer Series in Statistics

Mathematical Statistics

Essays on History and Methodology

    • ‏139٫99 US$
    • ‏139٫99 US$

وصف الناشر

This book presents a detailed description of the development of statistical theory. In the mid twentieth century, the development of mathematical statistics underwent an enduring change, due to the advent of more refined mathematical tools. New concepts like sufficiency, superefficiency, adaptivity etc. motivated scholars to reflect upon the interpretation of mathematical concepts in terms of their real-world relevance. Questions concerning the optimality of estimators, for instance, had remained unanswered for decades, because a meaningful concept of optimality (based on the regularity of the estimators, the representation of their limit distribution and assertions about their concentration by means of Anderson’s Theorem) was not yet available. The rapidly developing asymptotic theory provided approximate answers to questions for which non-asymptotic theory had found no satisfying solutions. In four engaging essays, this book presents a detailed description of how the use of mathematical methods stimulated the development of a statistical theory. Primarily focused on methodology, questionable proofs and neglected questions of priority, the book offers an intriguing resource for researchers in theoretical statistics, and can also serve as a textbook for advanced courses in statistics.

النوع
علم وطبيعة
تاريخ النشر
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٢٣ أكتوبر
اللغة
EN
الإنجليزية
عدد الصفحات
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الناشر
Springer Berlin Heidelberg
البائع
Springer Nature B.V.
الحجم
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‫م.ب.‬
Mathematical Statistics and Limit Theorems Mathematical Statistics and Limit Theorems
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Robustness Theory and Application Robustness Theory and Application
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Selected Works of Debabrata Basu Selected Works of Debabrata Basu
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Contemporary Developments in Statistical Theory Contemporary Developments in Statistical Theory
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Non-Asymptotic Analysis of Approximations for Multivariate Statistics Non-Asymptotic Analysis of Approximations for Multivariate Statistics
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Statistical Inference, Econometric Analysis and Matrix Algebra Statistical Inference, Econometric Analysis and Matrix Algebra
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The Elements of Statistical Learning The Elements of Statistical Learning
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Regression Modeling Strategies Regression Modeling Strategies
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Forecasting with Exponential Smoothing Forecasting with Exponential Smoothing
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An Introduction to Sequential Monte Carlo An Introduction to Sequential Monte Carlo
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Simulation and Inference for Stochastic Differential Equations Simulation and Inference for Stochastic Differential Equations
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Permutation, Parametric, and Bootstrap Tests of Hypotheses Permutation, Parametric, and Bootstrap Tests of Hypotheses
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