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1.

図書

図書
J.K. Wani
出版情報: New York : Appleton-Century-Crofts, 1971  xiv, 315 p. ; 24 cm
シリーズ名: The Appleton-Century statistics series
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2.

図書

図書
delivered by J. Neyman, at the Graduate School of the United States Department of Agriculture, in April 1937 ; rev. and supplemented by the author with the editorial assistance of W. Edwards Deming
出版情報: [S.l.] : [s.n.], [1938]  160 p. ; 22 cm
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3.

図書

図書
James R. Schott
出版情報: Hoboken, N.J. : John Wiley, c2005  xiii, 456 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
A Review of Elementary Matrix Algebra / 1:
Vector Spaces / 2:
Eigenvalues and Eigenvectors / 3:
Matrix Factorizations and Martrix Norms / 4:
Generalized Inverses / 5:
Systems of Linear Equations / 6:
Partitioned Matrices / 7:
Special Matrices and Matrix Operations / 8:
Matrix Derivatives and Related Topics / 9:
Some Special Topics Related to Quadratic Forms / 10:
References
Index
Preface
A Review of Elementary Matrix Algebra / 1:
Vector Spaces / 2:
4.

図書

図書
Christian P. Robert, George Casella
出版情報: New York : Springer, c2004  xxx, 645 p. ; 24 cm
シリーズ名: Springer texts in statistics
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5.

図書

図書
Richard J. Larsen, Morris L. Marx
出版情報: Boston ; Tokyo : Prentice Hall, c2012  x, 757 p. ; 26 cm
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6.

図書

図書
par Y.-V. Linnik ; traduit par L. Gruel
出版情報: Paris : Gauthier-Villars, 1962  vi, 293 p. ; 24 cm
シリーズ名: Monographies internationales de mathématiques modernes ; 3
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7.

図書

図書
Jay L. Devore, Nicholas R. Farnum
出版情報: Pacific Grove, Calif. : Duxbury Press, c1999  xiv, 577 p. ; 24 cm.
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8.

図書

図書
В.В. Налимов и Н.А. Чернова
出版情報: Москва : "Наука" Глав. ред. физико-математической лит-ры, 1965  340 p. ; 23 cm
シリーズ名: Физико-математическая библиотека инженера
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9.

図書

図書
Michael E. Tarter
出版情報: Natick, Mass. : A K Peters, c2000  xiii, 386 p. ; 24 cm
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目次情報: 続きを見る
Preface
Introduction / 1:
Background / 1.1:
A fictional example / 1.2:
Curves and statistical history / 1.3:
Model and Distribution Terminology / 2:
Modeling background / 2.1:
Representative number / 2.2:
Curve types / 2.3:
Distribution and data terminology / 2.4:
Parameter validity and property existence / 2.5:
Estimator terminology / 2.6:
Degenerate curves / 2.7:
Variability and Related Curve Properties / 3:
Uncertainty and variability / 3.1:
The absolute deviation curve property / 3.2:
The general AD and the ADM curve properties / 3.3:
Curve property selection / 3.4:
The history of variability appreciation / 3.5:
Simplistic approaches and the history of probability / 3.6:
Moments and Curve Uncertainty / 4:
E and Var Geometry / 4.1:
Higher order moments and the indicator function / 4.2:
Early statistical models / 4.3:
Early statistical models and higher order moments / 4.4:
Curve sub-types and model choice / 4.5:
Goodness of fit / 5:
Neyman's and alternative criteria / 5.1:
Criteria, metrics and estimators / 5.2:
The Kolmogoroff-Smirnoff criteria / 5.3:
Bernoulli variation and the Cauchy density / 5.4:
Comparative goodness of fit / 5.5:
Variates, Variables and Regression / 6:
Variates and variables / 6.1:
Variates and subjects / 6.2:
Expressions, algorithms and life tables / 6.3:
Distinctions between curve types / 6.4:
Curve properties and symbols / 6.5:
Variates, variables, and E[subscript f](Y|x) regression / 6.6:
[mu](x), E[subscript f] (Y|x) and regression alternatives / 6.7:
Mixing Parameters and Data-generation models / 7:
An introduction to data-generation models / 7.1:
Error, regression, and probit, models / 7.2:
Regression and data-generation models / 7.3:
Probability, proportion, and data-generation models / 7.4:
The generation of contagious model and mixture model data / 7.5:
The Association Parameter [rho] / 8:
Response, key, and nuisance, variates / 8.1:
The association parameter [rho] / 8.2:
Conditional, joint and marginal, notation / 8.3:
The sample and the population correlation coefficient / 8.4:
Correlation geometry / 8.5:
Regression and Association Parameters / 9:
The curse of dimensionality / 9.1:
Multiple variable interdependence / 9.2:
Logit and linear models / 9.3:
Dual regression functions / 9.4:
Parameters, Confounding, and Least Squares / 10:
Ideal objects / 10.1:
Linear data-generation models and mixture models / 10.2:
Parameter distinctiveness / 10.3:
Representational uniqueness and model fitting / 10.4:
Model-fitting considerations / 10.5:
The variance curve property and bathtub functions / 10.6:
Regression and least squares / 10.7:
Nonparametric Adjustment / 11:
Age-adjustment and logistic regression / 11.1:
Crude and specific rates / 11.2:
Age-adjustment; marginal, joint, and conditional curves / 11.3:
Age-adjustment and partial correlation / 11.4:
Direct and indirect adjustment / 11.5:
The computation of adjusted rates / 11.6:
Continuous Variate Adjustment / 12:
Observed and expected rates / 12.1:
Trivariate data-generation and additive regression models / 12.2:
Regression and data generation / 12.3:
Correlation, regression, and nuisance variables / 12.4:
Trivariate Normality graphics / 12.5:
Procedural Road Maps / 13:
The organization of statistical data and statistical methods / 13.1:
Log and log(-log) transformations / 13.2:
Methodological alternatives / 13.3:
Conditional and joint density models / 13.4:
Model-based and Generalized Representation / 14:
Multiple properties and parameters / 14.1:
Specification and generalized representation / 14.2:
Identifiability of generalized versus extended model representation / 14.3:
The E(X) curve property's relationship to location and scale / 14.4:
Parameters, Transformations, and Quantiles / 15:
Location and scale parameter representation of continuous variates / 15.1:
[rho]-focused transformations and [sigma]-focused transformations / 15.2:
Quantiles, quartiles, and box-and-whisker plots / 15.3:
Normal ranges and box sizes / 15.4:
Confidence bands and prediction bands / 15.5:
Notches, stems, and leaves / 15.6:
The log transformation and skewness / 15.7:
Noncentrality Parameters and Degress of Freedom / 16:
The (C[subscript 1]|A[subscript 2]) case and variate-variable relationships / 16.1:
Invariance and confounding / 16.2:
ANOVA tables and confounding / 16.3:
Contingency tables and the parameter v / 16.4:
Student-t and Cauchy densities / 16.5:
Parameter-Based Estimation / 17:
Likelihood and BLU estimation / 17.1:
Censoring and incompleteness / 17.2:
Outliers and errors / 17.3:
Ordered variates and subscripts / 17.4:
BLU estimators / 17.5:
BLU estimation and censoring / 17.6:
BLU estimators and alternatives / 17.7:
Inference and Composite Variates / 18:
Curves and composite variates / 18.1:
Specific sampling distributions / 18.2:
The mean's variance formula and mixtures / 18.3:
Inference and a two-valued metric / 18.4:
The one tail z-test / 18.5:
Parameters and Test Statistics / 19:
The parameter [Delta] / 19.1:
Power and efficiency / 19.2:
Power and test considerations / 19.3:
The sample mean and the sample median / 19.4:
Tables and the details of test construction / 19.5:
Power, efficiency and BLU estimators / 19.6:
Curve Truncation and the Curve e(x) / 20:
Expectation as a limit and the effects of truncation / 20.1:
Truncation symmetry / 20.2:
Truncation and bias / 20.3:
Truncation and the curve e(x) / 20.4:
When are curve properties relevant and when are model parameters relevant / 20.5:
Models and Notation / I:
Notation historical background / I.1:
Specific models, the Normal / I.2:
Specific models, lognormals and related curves / I.3:
Model families / I.4:
Mixtures and Bayesian statistics / I.5:
Notational conventions about moments and variates / I.6:
Variate Independence and Curve Identity / II:
Independence and identical distribution / II.1:
Regression notation / II.2:
General Statistical and Mathematical Notation / III:
References
Index
Preface
Introduction / 1:
Background / 1.1:
10.

図書

図書
Emanuel Parzen, Kunio Tanabe, Genshiro Kitagawa, editors
出版情報: New York : Springer, c1998  viii, 434 p. ; 24 cm
シリーズ名: Springer series in statistics
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