Kei Takeuchi

Contributions on Theory of Mathematical Statistics (eBook, PDF)

• Format: PDF

Produktbeschreibung

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 random and conditional approaches, and of randomized and non-randomized designs, with random sampling from finite populations considered as a special case of randomized designs and with some separate independent papers included. Theory of asymptotically optimal and higher-order optimal estimators are not included, since most of them already have been published in the Joint Collected Papers of M. Akahira and K. Takeuchi. There are some topics that are not necessarily new, do not seem to have attracted many theoretical statisticians, and do not appear to have been systematically dealt with in textbooks or expository monographs. One purpose of this volume is to give a comprehensive view of such problems as well.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Springer-Verlag GmbH
• Seitenzahl: 435
• Erscheinungstermin: 21. Januar 2020
• Englisch
• ISBN-13: 9784431552390
• Artikelnr.: 58560895

Autorenporträt

Professor Emeritus, The University of Tokyo

Inhaltsangabe

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).- 14 On Sum of 0-1 Random Variables (II. Multivariate Case).- 15 Algebraic Properties and Validity of Univariate and Multivariate Cornish-Fisher Expansion.