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Mathematical basis of statistics /

Mathematical Basis of Statistics.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Barra, Jean Ren�e, 1934-
Otros Autores: Herbach, Leon H.
Formato: Electrónico eBook
Idioma:Inglés
Francés
Publicado: New York : Academic Press, 1981.
Colección:Probability and mathematical statistics.
Temas:
Acceso en línea:Texto completo
Tabla de Contenidos:
  • 5.P-Minimum Sufficient Subfields and Statistics6. Relationship among Freedom, Completeness, Sufficiency, and StochasticIndependence; 7. Existence of Free Events; Exercises; CHAPTER 3. Statistical Information; 1. Introduction; 2. Information (according to Fisher); Exercises; CHAPTER 4. Statistical Inference; 1. Introduction; 2. Decisions and Strategies; 3. Hypothesis Testing and Statistical Estimation; 4. Choosing a Strategy; 5. Quasi-Ordering Induced by a Loss Function; 6. Nuisance Parameters; Exercises; CHAPTER 5. Testing Statistical Hypotheses; 1. Definitions and Preliminary Remarks
  • 2. Quasi-Ordering on Tests of Hypotheses3. Optimal Tests; 4. The Fundamental Neyman-Pearson Lemma; 5. Determining Optimal Tests; 6. Nonoptimal Methods; Exercises; CHAPTER 6. Statistical Estimation; 1. Unbiased Estimators; 2. Optimal Estimators; 3. Construction of Confidence Regions; 4. Optimal Set Estimators; Exercises; CHAPTER 7. The Multivariate Normal Distribution; 1. Some Useful Distributions; 2. Multivariate Normal Distributions; 3. Quadratic Forms of Normal Vectors; 4. Stochastic Dependence among Normal Vectors; Exercises; CHAPTER 8. Random Matrices; 1. Notation
  • 2. Covariance and Characteristic Function of a Random Matrix3. Some Miscellaneous Results; 4. Fundamental Results; 5. Normal Random Matrix; 6. Generalized Gamma Distributions; 7. Bartlett's Decomposition of a Gamma Distribution; 8. Nonsingular Gamma Distribution; 9. Generalized Beta Distributions; 10. Generalized Noncentral Gamma Distributions; Exercises; CHAPTER 9. Linear-Normal Statistical Spaces; 1. The Cochran Theorem; 2. Linear-Normal Statistical Spaces; 3. Fundamental Theorems; 4. Testing Linear Hypotheses; 5. Estimation of Linear Functions
  • 6. Fundamental Lemmas for Analysis of Variance7. Methodology of Analysis of Variance (Model I) in Experimental Design; 8. Analysis of Variance for Some Standard Experimental Designs; 9. Introduction to Analysis of Variance (Model II); 10. Generalized Linear-Normal Statistical Spaces; Exercises; CHAPTER 10. Exponential Statistical Spaces; 1. Laplace Transform of a Measure; 2. Analytical Properties of Exponential Statistical Spaces; 3. Sufficient Statistics on an Exponential Statistical Space; 4. Incomplete Exponential Statistical Spaces; 5. The Behrens-Fisher Problem; Exercises