An introduction to regression graphics [[electronic resource] /] / R. Dennis Cook, Sanford Weisberg |
Autore | Cook R. Dennis |
Pubbl/distr/stampa | New York, : Wiley, c1994 |
Descrizione fisica | 1 online resource (282 p.) |
Disciplina |
519.536028566
519.536078 |
Altri autori (Persone) | WeisbergSanford <1947-> |
Collana | Wiley series in probability and mathematical statistics |
Soggetto topico |
Multivariate analysis
Regression analysis - Graphic methods - Data processing |
ISBN |
1-282-30784-3
9786612307843 0-470-31686-1 0-470-31770-1 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
An Introduction to Regression Graphics; Contents; Preface; 1 Getting Started; 1.1 Doing the examples; 1.2 A Very Brief Introduction to Xlisp-Stat; 1.2.1 Entering Data; 1.2.2 Working with Lists; 1.2.3 Calculating the Slope and Intercept; 1.2.4 Drawing a Histogram; 1.2.5 Drawing a Scatterplot; 1.2.6 Saving and Printing Text; 1.2.7 Saving and Printing a Graph; 1.2.8 Quitting Xlisp-Stat; 1.3 An Introduction to the R-code; 1.4 Using Your Own Data; 1.5 Getting Help; 1.6 Complements; Exercises; 2 Simple Regression Plots; 2.1 Thinking about Scatterplots; 2.2 Simple Linear Regression
2.3 Assessing Linearity2.3.1 Superimposing the Fitted Line; 2.3.2 Residual Plots; 2.3.3 Average Smoothing; 2.3.4 Regression Smoothing; 2.4 Complements; Exercises; 3 Two-Dimensional Plots; 3.1 Aspect Ratio and Focusing; 3.2 Power Transformations; 3.3 Thinking about Power Transformations; 3.4 Showing Labels and Coordinates; 3.5 Linking Plots; 3.6 Marking and Coloring Points; 3.7 Brushing; 3.8 Name Lists; 3.9 complements; Exercises; 4 Scatterplot Matrices; 4.1 Using a Scatterplot Matrix; 4.2 Identifying Points; 4.3 Transforming Predictors to Linearity; 4.4 Partial Response Plots; 4.5 Complements Exercises5 Three-Dimensional Plots; 5.1 Viewing a Three-Dimensional Plot; 5.1.1 Rotation Control; 5.1.2 Recalling Views; 5.1.3 Rocking; 5.1.4 Show Axes; 5.1.5 Depth Cuing; 5.2 Scaling and Centering; 5.3 Two-Dimensional Plots fromThree-Dimensional Plots; 5.3.1 Saving h; 5.3.2 Rotation in Two Dimensions; 5.3.3 Extracting a Two-Dimensional Plot; 5.3.4 Summary; 5.4 Removing a Linear Trend in Three-Dimensional Plots; 5.5 Using Uncorrelated Predictors; 5.6 Complements; Exercises; 6 Visualizing Linear Regression with Two Predictors; 6.1 Linear Regression; 6.1.1 The Ideal Summary Plot 6.1.2 Viewing an Ideal Summary Plot When o2 = 06.2 Fitting by Eye; 6.2.1 Fitting by Eye When o2 = 0; 6.2.2 Fitting by Eye When o2 > 0; 6.2.3 Fitting by ols; 6.2.4 Checking a Candidate Summary Plot; 6.3 Correlated Predictors; 6.4 Distribution of the Predictors; 6.4.1 Nonlinear Predictors; 6.4.2 Linear Relationships Between Predictors; 6.4.3 Partial Variance Functions; 6.4.4 Scatterplot Matrices; 6.4.5 Multiple Regression; 6.5 Linear Predictors; 6.6 Complements; Exercises; 7 Visualizing Regression without Linearity; 7.1 General Three-Dimensional Response Plots; 7.1.1 Zero-Dimensional Structure 7.1.2 One-Dimensional Structure7.1.3 Two-Dimensional Structure; 7.2 Example: Australian Athletes Data; 7.3 Example: Ethanol Data; 7.4 Many Predictors; 7.4.1 The One-Dimensional Estimation Result; 7.4.2 An Example with a Nonlinear Response; 7.5 Example: Berkeley Guidance Study for Girls; 7.6 Example: Australian Athletes Again; 7.7 Complements; 7.7.1 Linearity; 7.7.2 ols Summary Plots; 7.7.3 References; Exercises; 8 Finding Dimension; 8.1 Finding Dimension Graphically; 8.1.1 The Inverse Regression Curve; 8.1.2 Inverse Partial Response Plots; 8.2 Sliced Inverse Regression 8.3 Example: Ethanol Data Revisited |
Record Nr. | UNINA-9910144693403321 |
Cook R. Dennis | ||
New York, : Wiley, c1994 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
An introduction to regression graphics [[electronic resource] /] / R. Dennis Cook, Sanford Weisberg |
Autore | Cook R. Dennis |
Pubbl/distr/stampa | New York, : Wiley, c1994 |
Descrizione fisica | 1 online resource (282 p.) |
Disciplina |
519.536028566
519.536078 |
Altri autori (Persone) | WeisbergSanford <1947-> |
Collana | Wiley series in probability and mathematical statistics |
Soggetto topico |
Multivariate analysis
Regression analysis - Graphic methods - Data processing |
ISBN |
1-282-30784-3
9786612307843 0-470-31686-1 0-470-31770-1 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
An Introduction to Regression Graphics; Contents; Preface; 1 Getting Started; 1.1 Doing the examples; 1.2 A Very Brief Introduction to Xlisp-Stat; 1.2.1 Entering Data; 1.2.2 Working with Lists; 1.2.3 Calculating the Slope and Intercept; 1.2.4 Drawing a Histogram; 1.2.5 Drawing a Scatterplot; 1.2.6 Saving and Printing Text; 1.2.7 Saving and Printing a Graph; 1.2.8 Quitting Xlisp-Stat; 1.3 An Introduction to the R-code; 1.4 Using Your Own Data; 1.5 Getting Help; 1.6 Complements; Exercises; 2 Simple Regression Plots; 2.1 Thinking about Scatterplots; 2.2 Simple Linear Regression
2.3 Assessing Linearity2.3.1 Superimposing the Fitted Line; 2.3.2 Residual Plots; 2.3.3 Average Smoothing; 2.3.4 Regression Smoothing; 2.4 Complements; Exercises; 3 Two-Dimensional Plots; 3.1 Aspect Ratio and Focusing; 3.2 Power Transformations; 3.3 Thinking about Power Transformations; 3.4 Showing Labels and Coordinates; 3.5 Linking Plots; 3.6 Marking and Coloring Points; 3.7 Brushing; 3.8 Name Lists; 3.9 complements; Exercises; 4 Scatterplot Matrices; 4.1 Using a Scatterplot Matrix; 4.2 Identifying Points; 4.3 Transforming Predictors to Linearity; 4.4 Partial Response Plots; 4.5 Complements Exercises5 Three-Dimensional Plots; 5.1 Viewing a Three-Dimensional Plot; 5.1.1 Rotation Control; 5.1.2 Recalling Views; 5.1.3 Rocking; 5.1.4 Show Axes; 5.1.5 Depth Cuing; 5.2 Scaling and Centering; 5.3 Two-Dimensional Plots fromThree-Dimensional Plots; 5.3.1 Saving h; 5.3.2 Rotation in Two Dimensions; 5.3.3 Extracting a Two-Dimensional Plot; 5.3.4 Summary; 5.4 Removing a Linear Trend in Three-Dimensional Plots; 5.5 Using Uncorrelated Predictors; 5.6 Complements; Exercises; 6 Visualizing Linear Regression with Two Predictors; 6.1 Linear Regression; 6.1.1 The Ideal Summary Plot 6.1.2 Viewing an Ideal Summary Plot When o2 = 06.2 Fitting by Eye; 6.2.1 Fitting by Eye When o2 = 0; 6.2.2 Fitting by Eye When o2 > 0; 6.2.3 Fitting by ols; 6.2.4 Checking a Candidate Summary Plot; 6.3 Correlated Predictors; 6.4 Distribution of the Predictors; 6.4.1 Nonlinear Predictors; 6.4.2 Linear Relationships Between Predictors; 6.4.3 Partial Variance Functions; 6.4.4 Scatterplot Matrices; 6.4.5 Multiple Regression; 6.5 Linear Predictors; 6.6 Complements; Exercises; 7 Visualizing Regression without Linearity; 7.1 General Three-Dimensional Response Plots; 7.1.1 Zero-Dimensional Structure 7.1.2 One-Dimensional Structure7.1.3 Two-Dimensional Structure; 7.2 Example: Australian Athletes Data; 7.3 Example: Ethanol Data; 7.4 Many Predictors; 7.4.1 The One-Dimensional Estimation Result; 7.4.2 An Example with a Nonlinear Response; 7.5 Example: Berkeley Guidance Study for Girls; 7.6 Example: Australian Athletes Again; 7.7 Complements; 7.7.1 Linearity; 7.7.2 ols Summary Plots; 7.7.3 References; Exercises; 8 Finding Dimension; 8.1 Finding Dimension Graphically; 8.1.1 The Inverse Regression Curve; 8.1.2 Inverse Partial Response Plots; 8.2 Sliced Inverse Regression 8.3 Example: Ethanol Data Revisited |
Record Nr. | UNINA-9910830316203321 |
Cook R. Dennis | ||
New York, : Wiley, c1994 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
An introduction to regression graphics [[electronic resource] /] / R. Dennis Cook, Sanford Weisberg |
Autore | Cook R. Dennis |
Pubbl/distr/stampa | New York, : Wiley, c1994 |
Descrizione fisica | 1 online resource (282 p.) |
Disciplina |
519.536028566
519.536078 |
Altri autori (Persone) | WeisbergSanford <1947-> |
Collana | Wiley series in probability and mathematical statistics |
Soggetto topico |
Multivariate analysis
Regression analysis - Graphic methods - Data processing |
ISBN |
1-282-30784-3
9786612307843 0-470-31686-1 0-470-31770-1 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
An Introduction to Regression Graphics; Contents; Preface; 1 Getting Started; 1.1 Doing the examples; 1.2 A Very Brief Introduction to Xlisp-Stat; 1.2.1 Entering Data; 1.2.2 Working with Lists; 1.2.3 Calculating the Slope and Intercept; 1.2.4 Drawing a Histogram; 1.2.5 Drawing a Scatterplot; 1.2.6 Saving and Printing Text; 1.2.7 Saving and Printing a Graph; 1.2.8 Quitting Xlisp-Stat; 1.3 An Introduction to the R-code; 1.4 Using Your Own Data; 1.5 Getting Help; 1.6 Complements; Exercises; 2 Simple Regression Plots; 2.1 Thinking about Scatterplots; 2.2 Simple Linear Regression
2.3 Assessing Linearity2.3.1 Superimposing the Fitted Line; 2.3.2 Residual Plots; 2.3.3 Average Smoothing; 2.3.4 Regression Smoothing; 2.4 Complements; Exercises; 3 Two-Dimensional Plots; 3.1 Aspect Ratio and Focusing; 3.2 Power Transformations; 3.3 Thinking about Power Transformations; 3.4 Showing Labels and Coordinates; 3.5 Linking Plots; 3.6 Marking and Coloring Points; 3.7 Brushing; 3.8 Name Lists; 3.9 complements; Exercises; 4 Scatterplot Matrices; 4.1 Using a Scatterplot Matrix; 4.2 Identifying Points; 4.3 Transforming Predictors to Linearity; 4.4 Partial Response Plots; 4.5 Complements Exercises5 Three-Dimensional Plots; 5.1 Viewing a Three-Dimensional Plot; 5.1.1 Rotation Control; 5.1.2 Recalling Views; 5.1.3 Rocking; 5.1.4 Show Axes; 5.1.5 Depth Cuing; 5.2 Scaling and Centering; 5.3 Two-Dimensional Plots fromThree-Dimensional Plots; 5.3.1 Saving h; 5.3.2 Rotation in Two Dimensions; 5.3.3 Extracting a Two-Dimensional Plot; 5.3.4 Summary; 5.4 Removing a Linear Trend in Three-Dimensional Plots; 5.5 Using Uncorrelated Predictors; 5.6 Complements; Exercises; 6 Visualizing Linear Regression with Two Predictors; 6.1 Linear Regression; 6.1.1 The Ideal Summary Plot 6.1.2 Viewing an Ideal Summary Plot When o2 = 06.2 Fitting by Eye; 6.2.1 Fitting by Eye When o2 = 0; 6.2.2 Fitting by Eye When o2 > 0; 6.2.3 Fitting by ols; 6.2.4 Checking a Candidate Summary Plot; 6.3 Correlated Predictors; 6.4 Distribution of the Predictors; 6.4.1 Nonlinear Predictors; 6.4.2 Linear Relationships Between Predictors; 6.4.3 Partial Variance Functions; 6.4.4 Scatterplot Matrices; 6.4.5 Multiple Regression; 6.5 Linear Predictors; 6.6 Complements; Exercises; 7 Visualizing Regression without Linearity; 7.1 General Three-Dimensional Response Plots; 7.1.1 Zero-Dimensional Structure 7.1.2 One-Dimensional Structure7.1.3 Two-Dimensional Structure; 7.2 Example: Australian Athletes Data; 7.3 Example: Ethanol Data; 7.4 Many Predictors; 7.4.1 The One-Dimensional Estimation Result; 7.4.2 An Example with a Nonlinear Response; 7.5 Example: Berkeley Guidance Study for Girls; 7.6 Example: Australian Athletes Again; 7.7 Complements; 7.7.1 Linearity; 7.7.2 ols Summary Plots; 7.7.3 References; Exercises; 8 Finding Dimension; 8.1 Finding Dimension Graphically; 8.1.1 The Inverse Regression Curve; 8.1.2 Inverse Partial Response Plots; 8.2 Sliced Inverse Regression 8.3 Example: Ethanol Data Revisited |
Record Nr. | UNINA-9910877092303321 |
Cook R. Dennis | ||
New York, : Wiley, c1994 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|