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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
Opac: Controlla la disponibilità qui
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
Opac: Controlla la disponibilità qui
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
Opac: Controlla la disponibilità qui
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 9786612307423
9781282307421
1282307428
9780470316894
0470316896
9780470317730
0470317736
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-9911020098103321
Basilevsky Alexander  
New York, : Wiley, c1994
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui