Contributions on Theory of Mathematical Statistics. 1st ed. 2020

種類:

電子ブック

責任表示:

by Kei Takeuchi

出版情報:

Tokyo : Springer Japan : Imprint: Springer, 2020

著者名:

• Takeuchi, Kei.
• SpringerLink (Online service)

ISBN:

9784431552390 [4431552391]    

注記:

Part I Statistical Prediction -- 1 Theory of Statistical Prediction -- Part II Unbiased Estimation -- 2 Unbiased Estimation in Case of the Class of Distributions of Finite Rank -- 3 Some Theorems on Invariant Estimators of Location -- Part III Robust Estimation -- 4 Robust Estimation and Robust Parameter -- 5 Robust Estimation of Location in the Case of Measurement of Physical Quantity -- 6 A Uniformly Asymptotically Efficient Estimator of a Location Parameter -- Part IV Randomization -- 7 Theory of Randomized Designs -- 8 Some Remarks on General Theory for Unbiased Estimation of a Real Parameter of a Finite Population -- Part V Tests of Normality -- 9 The Studentized Empirical Characteristic Function and Its Application to Test for the Shape of Distribution -- 10 Tests of Univariate Normality -- 11 The Tests for Multivariate Normality -- Part VI Model Selection -- 12 On the Problem of Model Selection Based on the Data.-Part VII Asymptotic Approximation -- 13 On Sum of 0-1 Random Variables (I. Univariate Case
This volume is a reorganized edition of Kei Takeuchi’s works on various problems in mathematical statistics based on papers and monographs written since the 1960s on several topics in mathematical statistics and published in various journals in English and in Japanese. They are organized into seven parts, each of which is concerned with specific topics and edited to make a consistent thesis. Sometimes expository chapters have been added. The topics included are as follows: theory of statistical prediction from a non-Bayesian viewpoint and analogous to the classical theory of statistical inference; theory of robust estimation, concepts, and procedures, and its implications for practical applications; theory of location and scale covariant/invariant estimations with derivation of explicit forms in various cases; theory of selection and testing of parametric models and a comprehensive approach including the derivation of the Akaike’s Information Criterion (AIC); theory of randomized designs, comparisons of rando

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