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Geologic map of the Beta Regio quadrangle (V-17), Venus / / by Alexander Basilevsky ; prepared for the National Aeronautics and Space Administration
| Geologic map of the Beta Regio quadrangle (V-17), Venus / / by Alexander Basilevsky ; prepared for the National Aeronautics and Space Administration |
| Autore | Basilevsky Alexander |
| Edizione | [Version 1.0.] |
| Pubbl/distr/stampa | [Reston, Va.] : , : U.S. Department of the Interior, U.S. Geological Survey, , 2008 |
| Descrizione fisica | 1 online resource (1 map) : color + + 1 pamphlet (33 pages) |
| Collana | Scientific investigations map |
| Soggetto topico | Geology |
| Soggetto genere / forma |
Maps.
Remote-sensing maps. |
| Formato | Materiale cartografico a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Geologic map of the Beta Regio quadrangle |
| Record Nr. | UNINA-9910703995703321 |
Basilevsky Alexander
|
||
| [Reston, Va.] : , : U.S. Department of the Interior, U.S. Geological Survey, , 2008 | ||
| Materiale cartografico a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Statistical factor analysis and related methods [[electronic resource] ] : theory and applications / / Alexander Basilevsky
| Statistical factor analysis and related methods [[electronic resource] ] : theory and applications / / Alexander Basilevsky |
| Autore | Basilevsky Alexander |
| Pubbl/distr/stampa | New York, : Wiley, c1994 |
| Descrizione fisica | 1 online resource (770 p.) |
| Disciplina |
519.5
519.5354 |
| Collana | Wiley series in probability and mathematical statistics. Probability and mathematical statistics |
| Soggetto topico |
Factor analysis
Multivariate analysis |
| ISBN |
1-282-30742-8
9786612307423 0-470-31689-6 0-470-31773-6 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Statistical Factor Analysis and Related Methods; Contents; 1. Preliminaries; 1.1. Introduction; 1.2. Rules for Univariate Distributions; 1.2.1. The Chi-Squared Distribution; 1.2.2. The F Distribution; 1.2.3. The t Distribution; 1.3. Estimation; 1.3.1. Point Estimation: Maximum Likelihood; 1.3.2. The Likelihood Ratio Criterion; 1.4. Notions of Multivariate Distributions; 1.5. Statistics and the Theory of Measurement; 1.5.1. The Algebraic Theory of Measurement; 1.5.2. Admissiblc Transformations and the Classification of Scales; 1.5.3. Scale Classification and Meaningful Statistics
1.5.4. Units of Measurc and Dimensional Analysis for Ratio Scales1.6. Statistical Entropy; 1.7. Complex Random Variables; Exercises; 2. Matrixes, Vector Spaces; 2.1. Introduction; 2.2. Linear, Quadratic Forms; 2.3. Multivariate Differentiation; 2.3.1. Derivative Vectors; 2.3.2. Derivative Matrices; 2.4. Grammian Association Matrices; 2.4.1. The inner Product Matrix; 2.4.2. The Cosine Matrix; 2.4.3. The Covariance Matrix; 2.4.4. The Correlation Matrix; 2.5. Transformation of Coordinates; 2.5.1. Orthogonal Rotations; 2.5.2. Oblique Rotations; 2.6. Latent Roots and Vectors of Grammian Matrices 2.7. Rotation of Quadratic Forms2.8. Elements of Multivariate Normal Theory; 2.8.1. The Multivariate Normal Distribution; 2.8.2. Sampling from the Multivariatc Normal; 2.9. Thc Kronecker Product; 2.10. Simultaneous Decomposition of Two Grammian Matrices; 2.11. The Complex Muitivariate Normal Distribution; 2.11.1. Complex Matrices, Hermitian Forms; 2.11.2. The Complex Multivariate Normat; Exercises; 3. The Ordinary Principal Components Model; 3.1. Introduction; 3.2. Principal Components in the Population; 3.3. Isotropic Variation; 3.4. Principal Components in the Sample; 3.4.1. Introduction 3.4.2. The General Model3.4.3. The Effect of Mean and Variances on PCs; 3.5. Principal Components and Projections; 3.6. Principal Components by Least Squares; 3.7. Nonlinearity in the Variables; 3.8. Alternative Scaling Criteria; 3.8.1. Introduction; 3.8.2. Standardized Regression Loadings; 3.8.3. Ratio Index Loadings; 3.8.4. Probability Index Loadings; Exercises; 4. Statistical Testing of the Ordinary Principal Components Model; 4.1. Introduction; 4.2. Testing Covariance and Correlation Matrices; 4.2.1. Testing for CompIete Independence; 4.2.2. Testing Sphericity 4.2.3. Other lests for Covariance Matrices4.3. Testing Principal Components by Maximum Likelihood; 4.3.1. Testing Equality of all Latent Roots; 4.3.2. Testing Subsets of Principal Components; 4.3.3. Testing Residuals; 4.3.4. Testing Individual Principal Components; 4.3.5. Information Criteria of Maximum Likelihood Estimation of the Number of Components; 4.4. Other Methods of Choosing Principal Components; 4.4.1. Estirnatcs Bascd on Resampling; 4.4.2. Residual Correlations Test; 4.4.3. Informal Rules of Thumb; 4.5. Discarding Redundant Variables; 4.6. Assessing Normality 4.6.1. Assessing for Univariate Normality |
| Record Nr. | UNINA-9910144695503321 |
|
Basilevsky Alexander
|
||
| New York, : Wiley, c1994 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Statistical factor analysis and related methods [[electronic resource] ] : theory and applications / / Alexander Basilevsky
| Statistical factor analysis and related methods [[electronic resource] ] : theory and applications / / Alexander Basilevsky |
| Autore | Basilevsky Alexander |
| Pubbl/distr/stampa | New York, : Wiley, c1994 |
| Descrizione fisica | 1 online resource (770 p.) |
| Disciplina |
519.5
519.5354 |
| Collana | Wiley series in probability and mathematical statistics. Probability and mathematical statistics |
| Soggetto topico |
Factor analysis
Multivariate analysis |
| ISBN |
1-282-30742-8
9786612307423 0-470-31689-6 0-470-31773-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Statistical Factor Analysis and Related Methods; Contents; 1. Preliminaries; 1.1. Introduction; 1.2. Rules for Univariate Distributions; 1.2.1. The Chi-Squared Distribution; 1.2.2. The F Distribution; 1.2.3. The t Distribution; 1.3. Estimation; 1.3.1. Point Estimation: Maximum Likelihood; 1.3.2. The Likelihood Ratio Criterion; 1.4. Notions of Multivariate Distributions; 1.5. Statistics and the Theory of Measurement; 1.5.1. The Algebraic Theory of Measurement; 1.5.2. Admissiblc Transformations and the Classification of Scales; 1.5.3. Scale Classification and Meaningful Statistics
1.5.4. Units of Measurc and Dimensional Analysis for Ratio Scales1.6. Statistical Entropy; 1.7. Complex Random Variables; Exercises; 2. Matrixes, Vector Spaces; 2.1. Introduction; 2.2. Linear, Quadratic Forms; 2.3. Multivariate Differentiation; 2.3.1. Derivative Vectors; 2.3.2. Derivative Matrices; 2.4. Grammian Association Matrices; 2.4.1. The inner Product Matrix; 2.4.2. The Cosine Matrix; 2.4.3. The Covariance Matrix; 2.4.4. The Correlation Matrix; 2.5. Transformation of Coordinates; 2.5.1. Orthogonal Rotations; 2.5.2. Oblique Rotations; 2.6. Latent Roots and Vectors of Grammian Matrices 2.7. Rotation of Quadratic Forms2.8. Elements of Multivariate Normal Theory; 2.8.1. The Multivariate Normal Distribution; 2.8.2. Sampling from the Multivariatc Normal; 2.9. Thc Kronecker Product; 2.10. Simultaneous Decomposition of Two Grammian Matrices; 2.11. The Complex Muitivariate Normal Distribution; 2.11.1. Complex Matrices, Hermitian Forms; 2.11.2. The Complex Multivariate Normat; Exercises; 3. The Ordinary Principal Components Model; 3.1. Introduction; 3.2. Principal Components in the Population; 3.3. Isotropic Variation; 3.4. Principal Components in the Sample; 3.4.1. Introduction 3.4.2. The General Model3.4.3. The Effect of Mean and Variances on PCs; 3.5. Principal Components and Projections; 3.6. Principal Components by Least Squares; 3.7. Nonlinearity in the Variables; 3.8. Alternative Scaling Criteria; 3.8.1. Introduction; 3.8.2. Standardized Regression Loadings; 3.8.3. Ratio Index Loadings; 3.8.4. Probability Index Loadings; Exercises; 4. Statistical Testing of the Ordinary Principal Components Model; 4.1. Introduction; 4.2. Testing Covariance and Correlation Matrices; 4.2.1. Testing for CompIete Independence; 4.2.2. Testing Sphericity 4.2.3. Other lests for Covariance Matrices4.3. Testing Principal Components by Maximum Likelihood; 4.3.1. Testing Equality of all Latent Roots; 4.3.2. Testing Subsets of Principal Components; 4.3.3. Testing Residuals; 4.3.4. Testing Individual Principal Components; 4.3.5. Information Criteria of Maximum Likelihood Estimation of the Number of Components; 4.4. Other Methods of Choosing Principal Components; 4.4.1. Estirnatcs Bascd on Resampling; 4.4.2. Residual Correlations Test; 4.4.3. Informal Rules of Thumb; 4.5. Discarding Redundant Variables; 4.6. Assessing Normality 4.6.1. Assessing for Univariate Normality |
| Record Nr. | UNINA-9910831051403321 |
|
Basilevsky Alexander
|
||
| New York, : Wiley, c1994 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Statistical factor analysis and related methods : theory and applications / / Alexander Basilevsky
| Statistical factor analysis and related methods : theory and applications / / Alexander Basilevsky |
| Autore | Basilevsky Alexander |
| Pubbl/distr/stampa | New York, : Wiley, c1994 |
| Descrizione fisica | 1 online resource (770 p.) |
| Disciplina |
519.5
519.5354 |
| Collana | Wiley series in probability and mathematical statistics. Probability and mathematical statistics |
| Soggetto topico |
Factor analysis
Multivariate analysis |
| ISBN |
1-282-30742-8
9786612307423 0-470-31689-6 0-470-31773-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Statistical Factor Analysis and Related Methods; Contents; 1. Preliminaries; 1.1. Introduction; 1.2. Rules for Univariate Distributions; 1.2.1. The Chi-Squared Distribution; 1.2.2. The F Distribution; 1.2.3. The t Distribution; 1.3. Estimation; 1.3.1. Point Estimation: Maximum Likelihood; 1.3.2. The Likelihood Ratio Criterion; 1.4. Notions of Multivariate Distributions; 1.5. Statistics and the Theory of Measurement; 1.5.1. The Algebraic Theory of Measurement; 1.5.2. Admissiblc Transformations and the Classification of Scales; 1.5.3. Scale Classification and Meaningful Statistics
1.5.4. Units of Measurc and Dimensional Analysis for Ratio Scales1.6. Statistical Entropy; 1.7. Complex Random Variables; Exercises; 2. Matrixes, Vector Spaces; 2.1. Introduction; 2.2. Linear, Quadratic Forms; 2.3. Multivariate Differentiation; 2.3.1. Derivative Vectors; 2.3.2. Derivative Matrices; 2.4. Grammian Association Matrices; 2.4.1. The inner Product Matrix; 2.4.2. The Cosine Matrix; 2.4.3. The Covariance Matrix; 2.4.4. The Correlation Matrix; 2.5. Transformation of Coordinates; 2.5.1. Orthogonal Rotations; 2.5.2. Oblique Rotations; 2.6. Latent Roots and Vectors of Grammian Matrices 2.7. Rotation of Quadratic Forms2.8. Elements of Multivariate Normal Theory; 2.8.1. The Multivariate Normal Distribution; 2.8.2. Sampling from the Multivariatc Normal; 2.9. Thc Kronecker Product; 2.10. Simultaneous Decomposition of Two Grammian Matrices; 2.11. The Complex Muitivariate Normal Distribution; 2.11.1. Complex Matrices, Hermitian Forms; 2.11.2. The Complex Multivariate Normat; Exercises; 3. The Ordinary Principal Components Model; 3.1. Introduction; 3.2. Principal Components in the Population; 3.3. Isotropic Variation; 3.4. Principal Components in the Sample; 3.4.1. Introduction 3.4.2. The General Model3.4.3. The Effect of Mean and Variances on PCs; 3.5. Principal Components and Projections; 3.6. Principal Components by Least Squares; 3.7. Nonlinearity in the Variables; 3.8. Alternative Scaling Criteria; 3.8.1. Introduction; 3.8.2. Standardized Regression Loadings; 3.8.3. Ratio Index Loadings; 3.8.4. Probability Index Loadings; Exercises; 4. Statistical Testing of the Ordinary Principal Components Model; 4.1. Introduction; 4.2. Testing Covariance and Correlation Matrices; 4.2.1. Testing for CompIete Independence; 4.2.2. Testing Sphericity 4.2.3. Other lests for Covariance Matrices4.3. Testing Principal Components by Maximum Likelihood; 4.3.1. Testing Equality of all Latent Roots; 4.3.2. Testing Subsets of Principal Components; 4.3.3. Testing Residuals; 4.3.4. Testing Individual Principal Components; 4.3.5. Information Criteria of Maximum Likelihood Estimation of the Number of Components; 4.4. Other Methods of Choosing Principal Components; 4.4.1. Estirnatcs Bascd on Resampling; 4.4.2. Residual Correlations Test; 4.4.3. Informal Rules of Thumb; 4.5. Discarding Redundant Variables; 4.6. Assessing Normality 4.6.1. Assessing for Univariate Normality |
| Record Nr. | UNINA-9910877826103321 |
|
Basilevsky Alexander
|
||
| New York, : Wiley, c1994 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||