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1.

図書

図書
Rand Wilcox
出版情報: Amsterdam ; Tokyo : Elsevier/Academic Press, 2012  xxi, 690 p. ; 25 cm
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目次情報: 続きを見る
Preface
Introduction / 1:
A Foundation for Robust Methods / 2:
Estimating Measures of Location and Scale / 3:
Confidence Intervals in the One-Sample Case / 4:
Comparing Two Groups / 5:
Some Multivariate Methods / 6:
One-Way and Higher Designs for Independent Groups / 7:
Comparing Multiple Dependent Groups / 8:
Correlation and Tests of Independence / 9:
Robust Regression / 10:
More Regression Methods / 11:
Preface
Introduction / 1:
A Foundation for Robust Methods / 2:
2.

図書

図書
Andrew P. Sage, James L. Melsa
出版情報: Malabar, Fla. : Robert E. Krieger, 1979  xi, 529 p.; 24 cm
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3.

図書

図書
Ю.В. Линник
出版情報: Москва : Изд-во "Наука" Глав. ред. физико-математической лит-ры, 1966  252 p. ; 21 cm
シリーズ名: Теория вероятностей и математическая статистика
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4.

図書

図書
D. Bosq
出版情報: New York ; Tokyo : Springer, c1998  xvi, 210 p. ; 24 cm
シリーズ名: Lecture notes in statistics ; 110
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5.

図書

図書
Geoffrey J. McLachlan, Thriyambakam Krishnan
出版情報: Hoboken, N.J. : Wiley-Interscience, c2008  xxvii, 359 p. ; 25 cm
シリーズ名: Wiley series in probability and mathematical statistics
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目次情報: 続きを見る
Preface to the Second Edition
Preface to the First Edition
List of Examples
General Introduction. / 1:
Introduction / 1.1:
Maximum Likelihood Estimation / 1.2:
Newton-Type Methods / 1.3:
Introductory Examples / 1.4:
Formulation of the EM Algorithm / 1.5:
EM Algorithm for MAP and MPL Estimation / 1.6:
Brief Summary of the Properties of EM Algorithm / 1.7:
History of the EM Algorithm / 1.8:
Overview of the Book / 1.9:
Notations / 1.10:
Examples of the EM Algorithm. / 2:
Multivariate Data with Missing Values / 2.1:
Least Square with the Missing Data / 2.3:
Example 2.4: Multinomial with Complex Cell Structure / 2.4:
Example 2.5: Analysis of PET and SPECT Data / 2.5:
Example 2.6: Multivariate t-Distribution / Known D.F.2.6:
Finite Normal Mixtures / 2.7:
Example 2.9: Grouped and Truncated Data / 2.8:
Example 2.10: A Hidden Markov AR(1) Model / 2.9:
Basic Theory of the EM Algorithm. / 3:
Monotonicity of a Generalized EM Algorithm / 3.1:
Convergence of an EM Sequence to a Stationary Value / 3.3:
Convergence of an EM Sequence of Iterates / 3.5:
Examples of Nontypical Behavior of an EM (GEM) Sequence / 3.6:
Score Statistic / 3.7:
Missing Information / 3.8:
Rate of Convergence of the EM Algorithm / 3.9:
Standard Errors and Speeding up Convergence. / 4:
Observed Information Matrix / 4.1:
Approximations to Observed Information Matrix: i.i.d. Case / 4.3:
Observed Information Matrix for Grouped Data / 4.4:
Supplemented EM Algorithm / 4.5:
Bookstrap Approach to Standard Error Approximation / 4.6:
BakerÆs, LouisÆ, and OakesÆ Methods for Standard Error Computation / 4.7:
Acceleration of the EM Algorithm via AitkenÆs Method / 4.8:
An Aitken Acceleration-Based Stopping Criterion / 4.9:
conjugate Gradient Acceleration of EM Algorithm / 4.10:
Hybrid Methods for Finding the MLE / 4.11:
A GEM Algorithm Based on One Newton-Raphson Algorithm / 4.12:
EM gradient Algorithm / 4.13:
A Quasi-Newton Acceleration of the EM Algorithm / 4.14:
Ikeda Acceleration / 4.15:
Extension of the EM Algorithm / 5:
ECM Algorithm / 5.1:
Multicycle ECM Algorithm / 5.3:
Example 5.2: Normal Mixtures with Equal Correlations / 5.4:
Example 5.3: Mixture Models for Survival Data / 5.5:
Example 5.4: Contingency Tables with Incomplete Data / 5.6:
ECME Algorithm / 5.7:
Example 5.5: MLE of t-Distribution with the Unknown D.F / 5.8:
Example 5.6: Variance Components / 5.9:
Linear Mixed Models / 5.10:
Example 5.8: Factor Analysis / 5.11:
Efficient Data Augmentation / 5.12:
Alternating ECM Algorithm / 5.13:
Example 5.9: Mixtures of Factor Analyzers / 5.14:
Parameter-Expanded EM (PX-EM) Algorithm / 5.15:
EMS Algorithm / 5.16:
One-Step-Late Algorithm / 5.17:
Variance Estimation for Penalized EM and OSL Algorithms / 5.18:
Incremental EM / 5.19:
Linear Inverse problems / 5.20:
Monte Carlo Versions of the EM Algorithm. / 6:
Monte Carlo Techniques / 6.1:
Monte Carlo EM / 6.3:
Data Augmentation / 6.4:
Bayesian EM / 6.5:
I.I.D. Monte Carlo Algorithm / 6.6:
Markov Chain Monte Carlo Algorithms / 6.7:
Gibbs Sampling / 6.8:
Examples of MCMC Algorithms / 6.9:
Relationship of EM to Gibbs Sampling / 6.10:
Data Augmentation and Gibbs Sampling / 6.11:
Empirical Bayes and EM / 6.12:
Multiple Imputation / 6.13:
Missing-Data Mechanism, Ignorability, and EM Algorithm / 6.14:
Some Generalization of the EM Algorithm. / 7:
Estimating Equations and Estimating Functions / 7.1:
Quasi-Score and the Projection-Solution Algorithm / 7.3:
Expectation-Solution (ES) Algorithm / 7.4:
Other Generalization / 7.5:
Variational Bayesian EM Algorithm / 7.6:
MM Algorithm / 7.7:
Lower Bound Maximization / 7.8:
Interval EM Algorithm / 7.9:
Competing Methods and Some Comparisons with EM / 7.10:
The Delta Algorithm / 7.11:
Image Space Reconstruction Algorithm / 7.12:
Further Applications of the EM Algorithm. / 8:
Hidden Markov Models / 8.1:
AIDS Epidemiology / 8.3:
Neural Networks / 8.4:
Data Mining / 8.5:
Bioinformatics / 8.6:
References
Author Index
Subject Index
Preface to the Second Edition
Preface to the First Edition
List of Examples
6.

図書

図書
edited by Demetrios G. Lainiotis
出版情報: New York : American Elsevier, c1974  174 p. ; 24 cm
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7.

図書

図書
Gerald J. Bierman
出版情報: New York : Academic Press, 1977  xvi, 241 p. ; 24 cm
シリーズ名: Mathematics in science and engineering : a series of monographs and textbooks ; v. 128
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8.

図書

図書
Michael I. Gilʹ
出版情報: New York : Marcel Dekker, c1995  viii, 355 p. ; 24 cm
シリーズ名: Monographs and textbooks in pure and applied mathematics ; 192
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Matrix-valued functions
Functions of compact operators
Functions of nonself-adjoint operators
Perterbations of finite dimensional and compact operators
Perterbations of noncompact operators
Perterbations of operators on a tensor product of Hilbert spaces
Stability and boundedness of ordinary differential systems
Stability of retarded systems
Absolute stability of solutions of Voletta integral equations
Stability of semilinear parabolic systems
Stability of Volterra
Matrix-valued functions
Functions of compact operators
Functions of nonself-adjoint operators
9.

図書

図書
by Donald Lee Snyder
出版情報: Cambridge (Mass.) ; London : M.I.T. Press, 1969  xi,114 p ; 24cm
シリーズ名: Research monograph / Massachusetts Institute of Technology ; no.51
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10.

図書

図書
edited by V.P. Godambe
出版情報: Oxford : Clarendon Press , New York : Oxford University Press, 1991  xii, 344 p. ; 24 cm
シリーズ名: Oxford statistical science series ; 7
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Overview / Part 1:
Estimating functions: an overview / V.P. Godambe ; B.K. Kale
Biostatistics / Part 2:
Applications of estimating function theory to replicates of generalized proportional hazards models / I.-Shou Chang ; Chao A. Hsiung
Estimating equations for mixed Poisson models / C.B. Dean
Estimating equations in generalized linear models with measurement error / Kung-Lee Liang ; Xin-Hua Liu
A unification of inference from capture-recapture studies through martingale estimating functions / C.J. Lloyd ; P. Yip
The role of unbiasedness in estimating equations / T. Yanagimoto ; E. Yamamoto
Use of a quadratic exponential model to generate estimating equations for means, variances, and covariances / L.P. Zhao ; R.L. Prentice
Stochastic Processes / Part 3:
Generalized score tests for composite hypotheses / I.V. Basawa
Quasi-likelihood stochastic processes and optimal estimating functions / A.F. Desmond
On optimal estimating functions for partially specified counting process models / P.E. Greenwood ; W. Wefelmeyer
Approximate confidence zones in an estimating function context / C.C. Heyde ; Y.-X. Lin
Simplified and two-stage quasi-likelihood estimators / J.E. Hutton ; O.T. Ogunyemi ; P.I. Nelson
Tests based on an optimal estimate / A. Thavaneswaran
Survey Sampling / Part 4:
Estimating functions in survey sampling: a review / M. Ghosh
Confidence intervals for quantiles
Making use of a regression model for inferences about a finite population mean / H. Mantel
Estimating functions in survey sampling: estimation of superpopulation regression parameters / K. Vijayan
Theory (Foundations) / Part 5:
Sufficiency, ancillarity, and information in estimating functions / V.P. Bhapkar
Inferential estimation, likelihood, and maximum likelihood linear estimating functions / S.R. Chamberlin ; D.A. Sprott
Geometrical aspects of efficiency criteria for spaces of estimating functions / C.G. Small ; D.L. McLeish
Theory (General Methods) / Part 6:
Estimating equations from modified profile likelihood / H. Ferguson ; N. Reid ; D.R. Cox
Resampling using estimating equations / S. Lele
On using bivariate moment equations in mixed normal problems / B.G. Lindsay ; P. Basak
Estimating funtions in semi-parametric models / Y. Ritov
Overview / Part 1:
Estimating functions: an overview / V.P. Godambe ; B.K. Kale
Biostatistics / Part 2:
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