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Regression graphics [[electronic resource] ] : ideas for studying regressions through graphics / / R. Dennis Cook
Regression graphics [[electronic resource] ] : ideas for studying regressions through graphics / / R. Dennis Cook
Autore Cook R. Dennis
Pubbl/distr/stampa New York, : Wiley, c1998
Descrizione fisica 1 online resource (378 p.)
Disciplina 519.536
519.536028
Collana Wiley series in probability and statistics Probability and statistics section
Soggetto topico Multivariate analysis
Regression analysis - Graphic methods
ISBN 1-282-30757-6
9786612307577
0-470-31693-4
0-470-31777-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Regression Graphics Ideas for Studying Regressions through Graphics; Contents; Preface; 1. Introduction; 1.1. C.C & I,1; 1.1.1. Construction; 1.1.3. Inference; 1.1.2. Characterization; 1.2. Illustrations; 1.2.1. Residuals versus fitted values; 1.2.2. Residuals versus the predictors; 1.2.3. Residuals versus the response; 1.3. On things to come; 1.4. Notational conventions; Problems; 2. Introduction to 2D Scatterplots; 2.1. Response plots in simple regression; 2.2. New Zealand horse mussels; 2.3. Transforming y via inverse response plots; 2.3.1 Response transformations
2.3.2 Response transformations: Mussel data2.4. Danish twins; 2.5. Scatterplot matrices; 2.5.1 Consrruction; 2.5.2 Example; 2.6. Regression graphics in the 1920s; 2.6.1. Ezekiel's successive approximations; 2.6.2. Bean's graphic method; 2.7. Discussion; Problems; 3. Constructing 3D Scatterplots; 3.1. Getting an impression of 3D; 3.2. Depth cuing; 3.3. Scaling; 3.4. Orthogonalization; Problems; 4. Interpreting 3D Scatterplots; 4.1. Haystacks; 4.2. Structural dimensionality; 4.2.1. One predictor; 4.2.2. Two predictors; 4.2.3 Many predictors; 4.3. One-dimensional structure
4.4. Two-dimensional structure4.4.1. Removing linear trends; 4.4.2. Identifying semiparametric regression functions; 4.5. Assessing structural dimensionality; 4.5.1. A visual metaphor for structural dimension; 4.5.2. A first method for deciding d = 1 or 2; 4.5.3. Natural rubber; 4.6. Assessment methods; 4.6.1. Using independence; 4.6.2. Using uncorrelated 2D views; 4.6.3. Uncorrelated 2D views: Haystack data; 4.6.4. Intraslice residuals; 4.6.5. Intraslice orthogonalization; 4.6.6. Mussels again; 4.6.7. Discussion; Problems; 5. Binary Response Variables; 5.1. One predictor; 5.2. Two predictors
7.5.2 Conditions for S ylx1=S(n1)
Record Nr. UNINA-9910144684803321
Cook R. Dennis  
New York, : Wiley, c1998
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Regression graphics [[electronic resource] ] : ideas for studying regressions through graphics / / R. Dennis Cook
Regression graphics [[electronic resource] ] : ideas for studying regressions through graphics / / R. Dennis Cook
Autore Cook R. Dennis
Pubbl/distr/stampa New York, : Wiley, c1998
Descrizione fisica 1 online resource (378 p.)
Disciplina 519.536
519.536028
Collana Wiley series in probability and statistics Probability and statistics section
Soggetto topico Multivariate analysis
Regression analysis - Graphic methods
ISBN 1-282-30757-6
9786612307577
0-470-31693-4
0-470-31777-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Regression Graphics Ideas for Studying Regressions through Graphics; Contents; Preface; 1. Introduction; 1.1. C.C & I,1; 1.1.1. Construction; 1.1.3. Inference; 1.1.2. Characterization; 1.2. Illustrations; 1.2.1. Residuals versus fitted values; 1.2.2. Residuals versus the predictors; 1.2.3. Residuals versus the response; 1.3. On things to come; 1.4. Notational conventions; Problems; 2. Introduction to 2D Scatterplots; 2.1. Response plots in simple regression; 2.2. New Zealand horse mussels; 2.3. Transforming y via inverse response plots; 2.3.1 Response transformations
2.3.2 Response transformations: Mussel data2.4. Danish twins; 2.5. Scatterplot matrices; 2.5.1 Consrruction; 2.5.2 Example; 2.6. Regression graphics in the 1920s; 2.6.1. Ezekiel's successive approximations; 2.6.2. Bean's graphic method; 2.7. Discussion; Problems; 3. Constructing 3D Scatterplots; 3.1. Getting an impression of 3D; 3.2. Depth cuing; 3.3. Scaling; 3.4. Orthogonalization; Problems; 4. Interpreting 3D Scatterplots; 4.1. Haystacks; 4.2. Structural dimensionality; 4.2.1. One predictor; 4.2.2. Two predictors; 4.2.3 Many predictors; 4.3. One-dimensional structure
4.4. Two-dimensional structure4.4.1. Removing linear trends; 4.4.2. Identifying semiparametric regression functions; 4.5. Assessing structural dimensionality; 4.5.1. A visual metaphor for structural dimension; 4.5.2. A first method for deciding d = 1 or 2; 4.5.3. Natural rubber; 4.6. Assessment methods; 4.6.1. Using independence; 4.6.2. Using uncorrelated 2D views; 4.6.3. Uncorrelated 2D views: Haystack data; 4.6.4. Intraslice residuals; 4.6.5. Intraslice orthogonalization; 4.6.6. Mussels again; 4.6.7. Discussion; Problems; 5. Binary Response Variables; 5.1. One predictor; 5.2. Two predictors
7.5.2 Conditions for S ylx1=S(n1)
Record Nr. UNINA-9910829913403321
Cook R. Dennis  
New York, : Wiley, c1998
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Regression graphics : ideas for studying regressions through graphics / / R. Dennis Cook
Regression graphics : ideas for studying regressions through graphics / / R. Dennis Cook
Autore Cook R. Dennis
Pubbl/distr/stampa New York, : Wiley, c1998
Descrizione fisica 1 online resource (378 p.)
Disciplina 519.5/36
Collana Wiley series in probability and statistics Probability and statistics section
Soggetto topico Multivariate analysis
Regression analysis - Graphic methods
ISBN 1-282-30757-6
9786612307577
0-470-31693-4
0-470-31777-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Regression Graphics Ideas for Studying Regressions through Graphics; Contents; Preface; 1. Introduction; 1.1. C.C & I,1; 1.1.1. Construction; 1.1.3. Inference; 1.1.2. Characterization; 1.2. Illustrations; 1.2.1. Residuals versus fitted values; 1.2.2. Residuals versus the predictors; 1.2.3. Residuals versus the response; 1.3. On things to come; 1.4. Notational conventions; Problems; 2. Introduction to 2D Scatterplots; 2.1. Response plots in simple regression; 2.2. New Zealand horse mussels; 2.3. Transforming y via inverse response plots; 2.3.1 Response transformations
2.3.2 Response transformations: Mussel data2.4. Danish twins; 2.5. Scatterplot matrices; 2.5.1 Consrruction; 2.5.2 Example; 2.6. Regression graphics in the 1920s; 2.6.1. Ezekiel's successive approximations; 2.6.2. Bean's graphic method; 2.7. Discussion; Problems; 3. Constructing 3D Scatterplots; 3.1. Getting an impression of 3D; 3.2. Depth cuing; 3.3. Scaling; 3.4. Orthogonalization; Problems; 4. Interpreting 3D Scatterplots; 4.1. Haystacks; 4.2. Structural dimensionality; 4.2.1. One predictor; 4.2.2. Two predictors; 4.2.3 Many predictors; 4.3. One-dimensional structure
4.4. Two-dimensional structure4.4.1. Removing linear trends; 4.4.2. Identifying semiparametric regression functions; 4.5. Assessing structural dimensionality; 4.5.1. A visual metaphor for structural dimension; 4.5.2. A first method for deciding d = 1 or 2; 4.5.3. Natural rubber; 4.6. Assessment methods; 4.6.1. Using independence; 4.6.2. Using uncorrelated 2D views; 4.6.3. Uncorrelated 2D views: Haystack data; 4.6.4. Intraslice residuals; 4.6.5. Intraslice orthogonalization; 4.6.6. Mussels again; 4.6.7. Discussion; Problems; 5. Binary Response Variables; 5.1. One predictor; 5.2. Two predictors
7.5.2 Conditions for S ylx1=S(n1)
Record Nr. UNINA-9910876779303321
Cook R. Dennis  
New York, : Wiley, c1998
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui