Statistical Theory and Applications - encadernada, livro de bolso

EAN (ISBN-13): 9780387945910
ISBN (ISBN-10): 0387945911
Livro de capa dura
Ano de publicação: 1995
Editor/Editora: Springer New York Core >2 >T
334 Páginas
Peso: 0,695 kg
Língua: eng/Englisch

Livro na base de dados desde 2007-05-15T06:14:01-03:00 (Sao Paulo)
Página de detalhes modificada pela última vez em 2024-04-06T14:58:02-03:00 (Sao Paulo)
Número ISBN/EAN: 9780387945910

Número ISBN - Ortografia alternativa:
0-387-94591-1, 978-0-387-94591-0
Ortografia alternativa e termos de pesquisa relacionados:
Autor do livro: hans fuchs, morrison, nagaraja, herbert klein, sen pranab
Título do livro: theory, uralic and altaic

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Dados da editora

Autor: H.N. Nagaraja; Pranab K. Sen; Donald F. Morrison
Título: Statistical Theory and Applications - Papers in Honor of Herbert A. David
Editora: Springer; Springer US
334 Páginas
Ano de publicação: 1995-11-09
New York; NY; US
Peso: 1,490 kg
Língua: Inglês
106,99 € (DE)
109,99 € (AT)
118,00 CHF (CH)
POD
XVIII, 334 p.

BB; Probability Theory and Stochastic Processes; Hardcover, Softcover / Mathematik/Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik; Wahrscheinlichkeitsrechnung und Statistik; Verstehen; ANOVA; Estimator; Likelihood; Normal distribution; Random variable; Variance; analysis of variance; Probability Theory; Stochastik; BC; EA

I General Distribution Theory and Inference.- 1 PIC: Power Divergence Information Criterion.- 1.1 Introduction.- 1.2 The Power Divergence Measures.- 1.3 Power-divergence Information Criterion (PIC).- 1.4 Count Data from the Framingham Study.- 1.5 Conclusions.- 1.6 References.- 2 Multivariate Student’s t and Its Applications.- 2.1 Introduction.- 2.2 A Multivariate Student t Distribution.- 2.2.1 Definition and Probability Integral.- 2.2.2 Computing the Probability Integral for p > 2.- 2.2.3 An Approximation for the Unequal pij Case.- 2.3 Applications of Multivariate t.- 2.3.1 Two-stage Indifference Zone Selection.- 2.3.2 Subset Selection.- 2.3.3 Treatments Versus Control Multiple Comparisons.- 2.3.4 Testing Multiple Contrasts.- 2.3.5 Multiple Comparisons with the “Best”.- 2.3.6 Additional Applications.- 2.4 References.- 3 Two Sets of Multivariate Bonferroni-type Inequalities.- 3.1 Introduction.- 3.2 The Results.- 3.3 Proofs.- 3.4 References.- 4 On the Proportion above Sample Mean for Symmetric Stable Laws.- 4.1 Introduction.- 4.2 The Result.- 4.3 A Partial Converse.- 4.4 Remarks and Extensions.- 4.5 References.- 5 The Relative Efficiency of Several Statistics Measuring Skewness.- 5.1 Introduction.- 5.2 Skewness Functional for X with Finite Support.- 5.3 Relative Efficiency of Skewness Estimators when X has Finite Support.- 5.4 Relative Efficiency of Skewness Estimators when X has Infinite Support.- 5.5 Summary.- 5.6 References.- 6 On a Class of Symmetric Nonnormal Distributions with a Kurtosis of Three.- 6.1 Introduction.- 6.2 Symmetric Mixtures with ?2 = 3.- 6.3 Examples.- 6.4 Limiting Distributions of the Extremes.- 6.5 Comments.- 6.6 References.- II Order Statistics — Distribution Theory.- 7 Moments of the Selection Differential from Exponential and Uniform Parents.- 7.1 Introduction.- 7.2 Moments of D from an Exponential Parent.- 7.3 Moments of D from a Uniform Parent.- 7.4 Asymptotes for the Moments of D.- 7.5 Convergence of the Moments: Exponential Parent.- 7.6 Convergence of the Moments: Uniform Parent.- 7.7 Tabular Analysis.- 7.7.1 Mean.- 7.7.2 Variance.- 7.7.3 Skewness.- 7.7.4 Kurtosis.- 7.8 Practical Implications.- 7.9 References.- 8 The Tallest Man in the World.- 8.1 Introduction.- 8.2 Some Useful Results on Branching Processes.- 8.3 The Tallest Man in the World.- 8.4 The Tallest Man in History.- 8.5 What Kind of Limit Laws can be Encountered?.- 8.6 References.- 9 Characterizing Distributions by Properties of Order Statistics — A Partial Review.- 9.1 Introduction.- 9.2 Independence of Linear Functions.- 9.3 Identical Distributions of Functions of Order Statistics.- 9.4 Moment Properties.- 9.5 Statistical Properties.- 9.6 Asymptotic Properties.- 9.7 References.- 10 Stochastic Ordering of the Number of Records.- 10.1 Introduction.- 10.2 The Results.- 10.2.1 Stochastic Ordering.- 10.2.2 Expectation of the Number of k-th Records.- 10.2.3 Integrated Likelihood Ratio Ordering.- 10.3 Proofs and an Example.- 10.4 References.- 11 Moments of Cauchy Order Statistics via Riemann Zeta Functions.- 11.1 Introduction.- 11.2 An Expression for the Mean.- 11.3 Expressions for Product Moments.- 11.4 References.- 12 Order Statistics of Bivariate Exponential Random Variables.- 12.1 Introduction.- 12.2 Freund, Marshall-Olkin, ?nd Raftery’s BVE Distributions.- 12.3 Joint Distributions.- 12.4 Marginal Distributions.- 12.4.1 Properties of T1.- 12.4.2 Properties of T2.- 12.5 Copula Functions.- 12.6 References.- III Order Statistics in Inference and Applications.- 13 Maximum Likelihood Estimation of the Laplace Parameters Based on Type-II Censored Samples.- 13.1 Introduction.- 13.2 Maximum Likelihood Estimators.- 13.3 Efficiency Relative to BLUE’s.- 13.4 References.- 14 The Impact of Order Statistics on Signal Processing.- 14.1 Introduction.- 14.2 Order Statistic Filters.- 14.2.1 Median and Rank-Order Filters.- 14.2.2 RO Filters.- 14.2.3 OS Filters.- 14.3 Generalizations.- 14.3.1 ? and Ll Filters.- 14.3.2 Permutation Filters.- 14.3.3 WMMR Filters.- 14.3.4 Stack Filters.- 14.3.5 Morphological Filters.- 14.4 Related Applications of Order Statistics.- 14.4.1 Edge Detection.- 14.4.2 Signal Enhancement and Restoration.- 14.5 Conclusions.- 14.6 References.- 15 A Nonlinear Ordered Rank Test to Detect Stochastic Ordering Between Two Distributions.- 15.1 Introduction.- 15.2 The Proposed Test.- 15.3 Simulation Study.- 15.4 Discussion.- 15.5 Asymptotic Properties.- 15.6 References.- 16 Estimation of Location and Scale Parameters of a Logistic Distribution Using a Ranked Set Sample.- 16.1 Introduction.- 16.2 Estimation of the Location Parameter.- 16.2.1 Best Linear Unbiased Estimator.- 16.2.2 Which Order Statistic?.- 16.3 Estimation of the Scale Parameter.- 16.4 Estimation of Quantiles.- 16.5 Proofs.- 16.6 References.- 17 Probability Models for an Employment Problem.- 17.1 Introduction.- 17.2 Definition of the Problem.- 17.2.1 Hiring Criteria.- 17.2.2 Notation.- 17.3 The Case of Couples and Single Applicants.- 17.3.1 Small Sample Results.- 17.3.2 Asymptotic Results.- 17.4 A Strategy for Couples.- 17.5 Conclusions.- 17.6 References.- IV Analysis of Variance and Experimental Design.- 18 On the Robustness of Bayes Estimators of the Variance Ratio in Balanced One-Way ANOVA Models with Covariates.- 18.1 Introduction.- 18.2 The Bayes Estimator and its Asymptotic Properties.- 18.3 Jackknifed Estimator of the Asymptotic Variance and Asymptotic Confidence Intervals.- 18.4 Simulation Results.- 18.5 References.- 19 Interchange Algorithms for Constructing Designs with Complex Blocking Structures.- 19.1 Historical Perspective.- 19.2 Optimality Criteria.- 19.3 Interchange Algorithms.- 19.4 Objective Functions.- 19.5 Discussion.- 19.6 References.- 20 Paired Comparisons for Multiple Characteristics: An ANOCOVA Approach.- 20.1 Introduction.- 20.2 ANOCOVAPC for Paired Characteristics.- 20.3 Probability Laws for Multiple Dichotomous Attributes.- 20.4 MANOCOVAPC Paired Comparisons Models and Analyses.- 20.5 Concluding Remarks.- 20.6 References.- V Biometry and Applications.- 21 On Assessing Multiple Equivalences with Reference to Bioequivalence.- 21.1 Introduction.- 21.2 Many-to-One Comparisons.- 21.3 Assessing Equivalence of k Formulations.- 21.4 Multiple Partial Equivalences.- 21.5 Example.- 21.6 References.- 22 Competing Risks.- 22.1 Introduction.- 22.2 Some Independent Competing Risk Results (After 1978).- 22.3 Non-identifiability Issues.- 22.4 Methods Assuming Informative Censoring (Dependent Competing Risks).- 22.5 Inference Using Estimable Quantities.- 22.6 Summary.- 22.7 References.- 23 Statistical Aspects of the Detection of Activation Effects in Cerebral Blood Flow and Metabolism by Positron Emission Tomography.- 23.1 Introduction: The Analysis of PET Data.- 23.2 The Activation Experiment and the Data.- 23.3 Activation Effects and a Simple Whole Brain Adjustment.- 23.4 Adjustment by the Analysis of Covariance.- 23.5 References.- 24 On Optimality of Q—Charts for Outliers in Statistical Process Control.- 24.1 Introduction.- 24.2 The Normal Mean Q-Chart.- 24.3 The Binomial Q-Chart.- 24.4 The Poisson Q-Chart.- 24.5 References.- VI Postscript.- 25 Herbert A. David.- 26 Conference Abstracts, Anecdotes, and Appreciation.