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ACCEPT : introduction of the adverse condition and critical event prediction toolbox / / Rodney A. Martin [and three others]
| ACCEPT : introduction of the adverse condition and critical event prediction toolbox / / Rodney A. Martin [and three others] |
| Autore | Martin Rodney A. |
| Pubbl/distr/stampa | Moffett Field, CA : , : National Aeronautics and Space Administration, Ames Research Center, , November 2015 |
| Descrizione fisica | 1 online resource (51 pages) : color illustrations |
| Collana | NASA/TM |
| Soggetto topico |
Mathematical models
Regression analysis Applications programs (computers) Machine learning Monte Carlo method |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | ACCEPT |
| Record Nr. | UNINA-9910704242103321 |
Martin Rodney A.
|
||
| Moffett Field, CA : , : National Aeronautics and Space Administration, Ames Research Center, , November 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Adaptive tests of significance using permutations of residuals with R and SAS [[electronic resource] /] / Thomas W. O'Gorman
| Adaptive tests of significance using permutations of residuals with R and SAS [[electronic resource] /] / Thomas W. O'Gorman |
| Autore | O'Gorman Thomas W |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley, 2012 |
| Descrizione fisica | 1 online resource (365 p.) |
| Disciplina | 519.5/36 |
| Soggetto topico |
Regression analysis
Computer adaptive testing R (Computer program language) |
| ISBN |
1-280-58894-2
1-118-21825-6 9786613618771 1-118-21822-1 |
| Classificazione | MAT029030 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Adaptive Tests of Significance Using Permutations of Residuals with R and SAS®; CONTENTS; Preface; 1 Introduction; 1.1 Why Use Adaptive Tests?; 1.2 A Brief History of Adaptive Tests; 1.2.1 Early Tests and Estimators; 1.2.2 Rank Tests; 1.2.3 The Weighted Least Squares Approach; 1.2.4 Recent Rank-Based Tests; 1.3 The Adaptive Test of Hogg, Fisher, and Randles; 1.3.1 Level of Significance of the HFR Test; 1.3.2 Comparison of Power of the HFR Test to the t Test; 1.4 Limitations of Rank-Based Tests; 1.5 The Adaptive Weighted Least Squares Approach; 1.5.1 Level of Significance
1.5.2 Comparison of Power of the Adaptive WLS Test to the t Test and the HFR Test1.6 Development of the Adaptive WLS Test; 2 Smoothing Methods and Normalizing Transformations; 2.1 Traditional Estimators of the Median and the Interquartile Range; 2.2 Percentile Estimators that Use the Smooth Cumulative Distribution Function; 2.2.1 Smoothing the Cumulative Distribution Function; 2.2.2 Using the Smoothed c.d.f. to Compute Percentiles; 2.2.3 R Code for Smoothing the c.d.f.; 2.2.4 R Code for Finding Percentiles; 2.3 Estimating the Bandwidth 2.3.1 An Estimator of Variability Based on Traditional Percentiles2.3.2 R Code for Finding the Bandwidth; 2.3.3 An Estimator of Variability Based on Percentiles from the Smoothed Distribution Function; 2.4 Normalizing Transformations; 2.4.1 Traditional Normalizing Methods; 2.4.2 Normalizing Data by Weighting; 2.5 The Weighting Algorithm; 2.5.1 An Example of the Weighing Procedure; 2.5.2 R Code for Weighting the Observations; 2.6 Computing the Bandwidth; 2.6.1 Error Distributions; 2.6.2 Measuring Errors in Adaptive Weighting; 2.6.3 Simulation Studies; 2.7 Examples of Transformed Data Exercises3 A Two-Sample Adaptive Test; 3.1 A Two-Sample Model; 3.2 Computing the Adaptive Weights; 3.2.1 R Code for Computing the Weights; 3.3 The Test Statistics for Adaptive Tests; 3.3.1 R Code to Compute the Test Statistic; 3.4 Permutation Methods for Two-Sample Tests; 3.4.1 Permutation of Observations; 3.4.2 Permutation of Residuals; 3.4.3 R Code for Permutations; 3.5 An Example of a Two-Sample Test; 3.6 R Code for the Two-Sample Test; 3.6.1 R Code for Computing the Test Statistics; 3.6.2 R Code to Compute the Traditional F Test Statistic and p-Value 3.6.3 An R Function that Computes the p-Value for the Adaptive Test3.6.4 R Code to Perform the Adaptive Test; 3.7 Level of Significance of the Adaptive Test; 3.8 Power of the Adaptive Test; 3.9 Sample Size Estimation; 3.10 A SAS Macro for the Adaptive Test; 3.11 Modifications for One-Tailed Tests; 3.12 Justification of the Weighting Method; 3.13 Comments on the Adaptive Two-sample Test; Exercises; 4 Permutation Tests with Linear Models; 4.1 Introduction; 4.2 Notation; 4.3 Permutations with Blocking; 4.4 Linear Models in Matrix Form; 4.5 Permutation Methods; 4.5.1 The Permute-Errors Method 4.5.2 The Permute-Residuals Method |
| Record Nr. | UNINA-9910141323703321 |
|
O'Gorman Thomas W
|
||
| Hoboken, N.J., : Wiley, 2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Adaptive tests of significance using permutations of residuals with R and SAS [[electronic resource] /] / Thomas W. O'Gorman
| Adaptive tests of significance using permutations of residuals with R and SAS [[electronic resource] /] / Thomas W. O'Gorman |
| Autore | O'Gorman Thomas W |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley, 2012 |
| Descrizione fisica | 1 online resource (365 p.) |
| Disciplina | 519.5/36 |
| Soggetto topico |
Regression analysis
Computer adaptive testing R (Computer program language) |
| ISBN |
1-280-58894-2
1-118-21825-6 9786613618771 1-118-21822-1 |
| Classificazione | MAT029030 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Adaptive Tests of Significance Using Permutations of Residuals with R and SAS®; CONTENTS; Preface; 1 Introduction; 1.1 Why Use Adaptive Tests?; 1.2 A Brief History of Adaptive Tests; 1.2.1 Early Tests and Estimators; 1.2.2 Rank Tests; 1.2.3 The Weighted Least Squares Approach; 1.2.4 Recent Rank-Based Tests; 1.3 The Adaptive Test of Hogg, Fisher, and Randles; 1.3.1 Level of Significance of the HFR Test; 1.3.2 Comparison of Power of the HFR Test to the t Test; 1.4 Limitations of Rank-Based Tests; 1.5 The Adaptive Weighted Least Squares Approach; 1.5.1 Level of Significance
1.5.2 Comparison of Power of the Adaptive WLS Test to the t Test and the HFR Test1.6 Development of the Adaptive WLS Test; 2 Smoothing Methods and Normalizing Transformations; 2.1 Traditional Estimators of the Median and the Interquartile Range; 2.2 Percentile Estimators that Use the Smooth Cumulative Distribution Function; 2.2.1 Smoothing the Cumulative Distribution Function; 2.2.2 Using the Smoothed c.d.f. to Compute Percentiles; 2.2.3 R Code for Smoothing the c.d.f.; 2.2.4 R Code for Finding Percentiles; 2.3 Estimating the Bandwidth 2.3.1 An Estimator of Variability Based on Traditional Percentiles2.3.2 R Code for Finding the Bandwidth; 2.3.3 An Estimator of Variability Based on Percentiles from the Smoothed Distribution Function; 2.4 Normalizing Transformations; 2.4.1 Traditional Normalizing Methods; 2.4.2 Normalizing Data by Weighting; 2.5 The Weighting Algorithm; 2.5.1 An Example of the Weighing Procedure; 2.5.2 R Code for Weighting the Observations; 2.6 Computing the Bandwidth; 2.6.1 Error Distributions; 2.6.2 Measuring Errors in Adaptive Weighting; 2.6.3 Simulation Studies; 2.7 Examples of Transformed Data Exercises3 A Two-Sample Adaptive Test; 3.1 A Two-Sample Model; 3.2 Computing the Adaptive Weights; 3.2.1 R Code for Computing the Weights; 3.3 The Test Statistics for Adaptive Tests; 3.3.1 R Code to Compute the Test Statistic; 3.4 Permutation Methods for Two-Sample Tests; 3.4.1 Permutation of Observations; 3.4.2 Permutation of Residuals; 3.4.3 R Code for Permutations; 3.5 An Example of a Two-Sample Test; 3.6 R Code for the Two-Sample Test; 3.6.1 R Code for Computing the Test Statistics; 3.6.2 R Code to Compute the Traditional F Test Statistic and p-Value 3.6.3 An R Function that Computes the p-Value for the Adaptive Test3.6.4 R Code to Perform the Adaptive Test; 3.7 Level of Significance of the Adaptive Test; 3.8 Power of the Adaptive Test; 3.9 Sample Size Estimation; 3.10 A SAS Macro for the Adaptive Test; 3.11 Modifications for One-Tailed Tests; 3.12 Justification of the Weighting Method; 3.13 Comments on the Adaptive Two-sample Test; Exercises; 4 Permutation Tests with Linear Models; 4.1 Introduction; 4.2 Notation; 4.3 Permutations with Blocking; 4.4 Linear Models in Matrix Form; 4.5 Permutation Methods; 4.5.1 The Permute-Errors Method 4.5.2 The Permute-Residuals Method |
| Record Nr. | UNINA-9910811410703321 |
|
O'Gorman Thomas W
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||
| Hoboken, N.J., : Wiley, 2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Alternative methods of regression [[electronic resource] /] / David Birkes, Yadolah Dodge
| Alternative methods of regression [[electronic resource] /] / David Birkes, Yadolah Dodge |
| Autore | Birkes David |
| Pubbl/distr/stampa | New York, : John Wiley, 1993 |
| Descrizione fisica | 1 online resource (248 p.) |
| Disciplina |
519.5/36
519.536 |
| Altri autori (Persone) | DodgeYadolah <1944-> |
| Collana | Wiley Series in Probability and Statistics |
| Soggetto topico |
Regression analysis
Multivariate analysis |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-283-29481-8
9786613294814 1-118-15023-6 1-118-15024-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Alternative Methods of Regression; Contents; Preface; Acknowledgments; 1. Linear Regression Analysis; 1.1 Introduction; 1.2 Example; 1.3 The Linear Regression Model; 1.4 Estimating the Regression Coefficients; 1.5 Testing the Significance of the Relationship; 1.6 The Need for Alternative Methods; 1.7 The Origin of the Word ""Regression""; Notes; References; 2. Constructing and Checking the Model; 2.1 Introduction; 2.2 Checking the Model; 2.3 Modifying the Model; 2.4 Examples; Notes; References; 3. Least-Squares Regression; 3.1 Introduction; 3.2 An Example of Simple Regression
3.3 Estimating the Regression Line3.4 Testing β = 0; 3.5 Checking Normality; 3.6 An Example of Multiple Regression; 3.7 Estimating the Regression Coefficients; 3.8 Testing the Regression Coefficients; 3.9 Testing βq + 1 = · · · = βp = 0; 3.10 Testing β3 = 0; 3.11 The Coefficient of Determination; 3.12 Computation; Notes; References; 4. Least-Absolute-Deviations Regression; 4.1 Introduction; 4.2 Estimating the Regression Line; 4.3 Nonuniqueness and Degeneracy; 4.4 Testing β = 0; 4.5 An Example of Multiple Regression; 4.6 Estimating the Regression Coefficients 4.7 Testing βq + 1 = · · · = βp = 04.8 Computation; Notes; References; 5. M-Regression; 5.1 Introduction; 5.2 An Example of Simple Regression; 5.3 Estimating the Regression Line; 5.4 Testing β = 0; 5.5 An Example of Multiple Regression; 5.6 Estimating the Regression Coefficients; 5.7 Testing βq + 1 = · · · = βp = 0; 5.8 Computation; Notes; References; 6. Nonparametric Regression; 6.1 Introduction; 6.2 An Example of Simple Regression; 6.3 Estimating the Regression Line; 6.4 Testing β = 0; 6.5 An Example of Multiple Regression; 6.6 Estimating the Regression Coefficients 6.7 Testing βq + 1 = · · · = βp = 06.8 Computation; Notes; References; 7. Bayesian Regression; 7.1 Introduction; 7.2 The Bayesian Approach; 7.3 An Example of Simple Regression; 7.4 Estimating the Regression Line; 7.5 Testing β = 0; 7.6 An Example of Multiple Regression; 7.7 Estimating the Regression Coefficients; 7.8 Testing βq + 1 = · · · = βp = 0; 7.9 Computation; Notes; References; 8. Ridge Regression; 8.1 Introduction; 8.2 An Example of Simple Regression; 8.3 Estimating the Regression Line; 8.4 An Example of Multiple Regression; 8.5 Standardization 8.6 Estimating the Regression Coefficients8.7 Collinearity; Notes; References; 9. Comparisons; 9.1 Introduction; 9.2 Comparison of Properties; 9.3 Comparisons on Three Data Sets; Notes; References; 10. Other Methods; 10.1 Introduction; 10.2 Other Methods of Linear Regression; 10.3 More General Methods of Regression; References; Appendix; Student's t-Distribution; F-Distribution; Chi-squared Distribution; Index |
| Record Nr. | UNINA-9910139573103321 |
|
Birkes David
|
||
| New York, : John Wiley, 1993 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Alternative methods of regression [[electronic resource] /] / David Birkes, Yadolah Dodge
| Alternative methods of regression [[electronic resource] /] / David Birkes, Yadolah Dodge |
| Autore | Birkes David |
| Pubbl/distr/stampa | New York, : John Wiley, 1993 |
| Descrizione fisica | 1 online resource (248 p.) |
| Disciplina |
519.5/36
519.536 |
| Altri autori (Persone) | DodgeYadolah <1944-> |
| Collana | Wiley Series in Probability and Statistics |
| Soggetto topico |
Regression analysis
Multivariate analysis |
| ISBN |
1-283-29481-8
9786613294814 1-118-15023-6 1-118-15024-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Alternative Methods of Regression; Contents; Preface; Acknowledgments; 1. Linear Regression Analysis; 1.1 Introduction; 1.2 Example; 1.3 The Linear Regression Model; 1.4 Estimating the Regression Coefficients; 1.5 Testing the Significance of the Relationship; 1.6 The Need for Alternative Methods; 1.7 The Origin of the Word ""Regression""; Notes; References; 2. Constructing and Checking the Model; 2.1 Introduction; 2.2 Checking the Model; 2.3 Modifying the Model; 2.4 Examples; Notes; References; 3. Least-Squares Regression; 3.1 Introduction; 3.2 An Example of Simple Regression
3.3 Estimating the Regression Line3.4 Testing β = 0; 3.5 Checking Normality; 3.6 An Example of Multiple Regression; 3.7 Estimating the Regression Coefficients; 3.8 Testing the Regression Coefficients; 3.9 Testing βq + 1 = · · · = βp = 0; 3.10 Testing β3 = 0; 3.11 The Coefficient of Determination; 3.12 Computation; Notes; References; 4. Least-Absolute-Deviations Regression; 4.1 Introduction; 4.2 Estimating the Regression Line; 4.3 Nonuniqueness and Degeneracy; 4.4 Testing β = 0; 4.5 An Example of Multiple Regression; 4.6 Estimating the Regression Coefficients 4.7 Testing βq + 1 = · · · = βp = 04.8 Computation; Notes; References; 5. M-Regression; 5.1 Introduction; 5.2 An Example of Simple Regression; 5.3 Estimating the Regression Line; 5.4 Testing β = 0; 5.5 An Example of Multiple Regression; 5.6 Estimating the Regression Coefficients; 5.7 Testing βq + 1 = · · · = βp = 0; 5.8 Computation; Notes; References; 6. Nonparametric Regression; 6.1 Introduction; 6.2 An Example of Simple Regression; 6.3 Estimating the Regression Line; 6.4 Testing β = 0; 6.5 An Example of Multiple Regression; 6.6 Estimating the Regression Coefficients 6.7 Testing βq + 1 = · · · = βp = 06.8 Computation; Notes; References; 7. Bayesian Regression; 7.1 Introduction; 7.2 The Bayesian Approach; 7.3 An Example of Simple Regression; 7.4 Estimating the Regression Line; 7.5 Testing β = 0; 7.6 An Example of Multiple Regression; 7.7 Estimating the Regression Coefficients; 7.8 Testing βq + 1 = · · · = βp = 0; 7.9 Computation; Notes; References; 8. Ridge Regression; 8.1 Introduction; 8.2 An Example of Simple Regression; 8.3 Estimating the Regression Line; 8.4 An Example of Multiple Regression; 8.5 Standardization 8.6 Estimating the Regression Coefficients8.7 Collinearity; Notes; References; 9. Comparisons; 9.1 Introduction; 9.2 Comparison of Properties; 9.3 Comparisons on Three Data Sets; Notes; References; 10. Other Methods; 10.1 Introduction; 10.2 Other Methods of Linear Regression; 10.3 More General Methods of Regression; References; Appendix; Student's t-Distribution; F-Distribution; Chi-squared Distribution; Index |
| Record Nr. | UNISA-996218078503316 |
|
Birkes David
|
||
| New York, : John Wiley, 1993 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Alternative methods of regression [[electronic resource] /] / David Birkes, Yadolah Dodge
| Alternative methods of regression [[electronic resource] /] / David Birkes, Yadolah Dodge |
| Autore | Birkes David |
| Pubbl/distr/stampa | New York, : John Wiley, 1993 |
| Descrizione fisica | 1 online resource (248 p.) |
| Disciplina |
519.5/36
519.536 |
| Altri autori (Persone) | DodgeYadolah <1944-> |
| Collana | Wiley Series in Probability and Statistics |
| Soggetto topico |
Regression analysis
Multivariate analysis |
| ISBN |
1-283-29481-8
9786613294814 1-118-15023-6 1-118-15024-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Alternative Methods of Regression; Contents; Preface; Acknowledgments; 1. Linear Regression Analysis; 1.1 Introduction; 1.2 Example; 1.3 The Linear Regression Model; 1.4 Estimating the Regression Coefficients; 1.5 Testing the Significance of the Relationship; 1.6 The Need for Alternative Methods; 1.7 The Origin of the Word ""Regression""; Notes; References; 2. Constructing and Checking the Model; 2.1 Introduction; 2.2 Checking the Model; 2.3 Modifying the Model; 2.4 Examples; Notes; References; 3. Least-Squares Regression; 3.1 Introduction; 3.2 An Example of Simple Regression
3.3 Estimating the Regression Line3.4 Testing β = 0; 3.5 Checking Normality; 3.6 An Example of Multiple Regression; 3.7 Estimating the Regression Coefficients; 3.8 Testing the Regression Coefficients; 3.9 Testing βq + 1 = · · · = βp = 0; 3.10 Testing β3 = 0; 3.11 The Coefficient of Determination; 3.12 Computation; Notes; References; 4. Least-Absolute-Deviations Regression; 4.1 Introduction; 4.2 Estimating the Regression Line; 4.3 Nonuniqueness and Degeneracy; 4.4 Testing β = 0; 4.5 An Example of Multiple Regression; 4.6 Estimating the Regression Coefficients 4.7 Testing βq + 1 = · · · = βp = 04.8 Computation; Notes; References; 5. M-Regression; 5.1 Introduction; 5.2 An Example of Simple Regression; 5.3 Estimating the Regression Line; 5.4 Testing β = 0; 5.5 An Example of Multiple Regression; 5.6 Estimating the Regression Coefficients; 5.7 Testing βq + 1 = · · · = βp = 0; 5.8 Computation; Notes; References; 6. Nonparametric Regression; 6.1 Introduction; 6.2 An Example of Simple Regression; 6.3 Estimating the Regression Line; 6.4 Testing β = 0; 6.5 An Example of Multiple Regression; 6.6 Estimating the Regression Coefficients 6.7 Testing βq + 1 = · · · = βp = 06.8 Computation; Notes; References; 7. Bayesian Regression; 7.1 Introduction; 7.2 The Bayesian Approach; 7.3 An Example of Simple Regression; 7.4 Estimating the Regression Line; 7.5 Testing β = 0; 7.6 An Example of Multiple Regression; 7.7 Estimating the Regression Coefficients; 7.8 Testing βq + 1 = · · · = βp = 0; 7.9 Computation; Notes; References; 8. Ridge Regression; 8.1 Introduction; 8.2 An Example of Simple Regression; 8.3 Estimating the Regression Line; 8.4 An Example of Multiple Regression; 8.5 Standardization 8.6 Estimating the Regression Coefficients8.7 Collinearity; Notes; References; 9. Comparisons; 9.1 Introduction; 9.2 Comparison of Properties; 9.3 Comparisons on Three Data Sets; Notes; References; 10. Other Methods; 10.1 Introduction; 10.2 Other Methods of Linear Regression; 10.3 More General Methods of Regression; References; Appendix; Student's t-Distribution; F-Distribution; Chi-squared Distribution; Index |
| Record Nr. | UNINA-9910831025803321 |
|
Birkes David
|
||
| New York, : John Wiley, 1993 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Alternative methods of regression [[electronic resource] /] / David Birkes, Yadolah Dodge
| Alternative methods of regression [[electronic resource] /] / David Birkes, Yadolah Dodge |
| Autore | Birkes David |
| Pubbl/distr/stampa | New York, : John Wiley, 1993 |
| Descrizione fisica | 1 online resource (248 p.) |
| Disciplina |
519.5/36
519.536 |
| Altri autori (Persone) | DodgeYadolah <1944-> |
| Collana | Wiley Series in Probability and Statistics |
| Soggetto topico |
Regression analysis
Multivariate analysis |
| ISBN |
1-283-29481-8
9786613294814 1-118-15023-6 1-118-15024-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Alternative Methods of Regression; Contents; Preface; Acknowledgments; 1. Linear Regression Analysis; 1.1 Introduction; 1.2 Example; 1.3 The Linear Regression Model; 1.4 Estimating the Regression Coefficients; 1.5 Testing the Significance of the Relationship; 1.6 The Need for Alternative Methods; 1.7 The Origin of the Word ""Regression""; Notes; References; 2. Constructing and Checking the Model; 2.1 Introduction; 2.2 Checking the Model; 2.3 Modifying the Model; 2.4 Examples; Notes; References; 3. Least-Squares Regression; 3.1 Introduction; 3.2 An Example of Simple Regression
3.3 Estimating the Regression Line3.4 Testing β = 0; 3.5 Checking Normality; 3.6 An Example of Multiple Regression; 3.7 Estimating the Regression Coefficients; 3.8 Testing the Regression Coefficients; 3.9 Testing βq + 1 = · · · = βp = 0; 3.10 Testing β3 = 0; 3.11 The Coefficient of Determination; 3.12 Computation; Notes; References; 4. Least-Absolute-Deviations Regression; 4.1 Introduction; 4.2 Estimating the Regression Line; 4.3 Nonuniqueness and Degeneracy; 4.4 Testing β = 0; 4.5 An Example of Multiple Regression; 4.6 Estimating the Regression Coefficients 4.7 Testing βq + 1 = · · · = βp = 04.8 Computation; Notes; References; 5. M-Regression; 5.1 Introduction; 5.2 An Example of Simple Regression; 5.3 Estimating the Regression Line; 5.4 Testing β = 0; 5.5 An Example of Multiple Regression; 5.6 Estimating the Regression Coefficients; 5.7 Testing βq + 1 = · · · = βp = 0; 5.8 Computation; Notes; References; 6. Nonparametric Regression; 6.1 Introduction; 6.2 An Example of Simple Regression; 6.3 Estimating the Regression Line; 6.4 Testing β = 0; 6.5 An Example of Multiple Regression; 6.6 Estimating the Regression Coefficients 6.7 Testing βq + 1 = · · · = βp = 06.8 Computation; Notes; References; 7. Bayesian Regression; 7.1 Introduction; 7.2 The Bayesian Approach; 7.3 An Example of Simple Regression; 7.4 Estimating the Regression Line; 7.5 Testing β = 0; 7.6 An Example of Multiple Regression; 7.7 Estimating the Regression Coefficients; 7.8 Testing βq + 1 = · · · = βp = 0; 7.9 Computation; Notes; References; 8. Ridge Regression; 8.1 Introduction; 8.2 An Example of Simple Regression; 8.3 Estimating the Regression Line; 8.4 An Example of Multiple Regression; 8.5 Standardization 8.6 Estimating the Regression Coefficients8.7 Collinearity; Notes; References; 9. Comparisons; 9.1 Introduction; 9.2 Comparison of Properties; 9.3 Comparisons on Three Data Sets; Notes; References; 10. Other Methods; 10.1 Introduction; 10.2 Other Methods of Linear Regression; 10.3 More General Methods of Regression; References; Appendix; Student's t-Distribution; F-Distribution; Chi-squared Distribution; Index |
| Record Nr. | UNINA-9910841134903321 |
|
Birkes David
|
||
| New York, : John Wiley, 1993 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
The analysis of covariance and alternatives [[electronic resource] ] : statistical methods for experiments, quasi-experiments, and single-case studies / / Bradley Huitema
| The analysis of covariance and alternatives [[electronic resource] ] : statistical methods for experiments, quasi-experiments, and single-case studies / / Bradley Huitema |
| Autore | Huitema Bradley E. <1938-> |
| Edizione | [2nd ed.] |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley, c2011 |
| Descrizione fisica | 1 online resource (690 p.) |
| Disciplina |
519.5/38
519.535 |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Analysis of covariance
Regression analysis |
| ISBN |
1-283-33209-4
9786613332097 1-118-06747-9 1-118-06746-0 1-118-06745-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
The Analysis of Covariance and Alternatives; Contents; Preface; PART I BASIC EXPERIMENTAL DESIGN AND ANALYSIS; 1 Review of Basic Statistical Methods; 1.1 Introduction; 1.2 Elementary Statistical Inference; 1.3 Elementary Statistical Decision Theory; 1.4 Effect Size; 1.5 Measures of Association; 1.6 A Practical Alternative to Effect Sizes and Measures of Association That Is Relevant to the Individual: p(YTx > YControl); 1.7 Generalization of Results; 1.8 Control of Nuisance Variation; 1.9 Software; 1.10 Summary; 2 Review of Simple Correlated Samples Designs and Associated Analyses
2.1 Introduction 2.2 Two-Level Correlated Samples Designs; 2.3 Software; 2.4 Summary; 3 ANOVA Basics for One-Factor Randomized Group, Randomized Block, and Repeated Measurement Designs; 3.1 Introduction; 3.2 One-Factor Randomized Group Design and Analysis; 3.3 One-Factor Randomized Block Design and Analysis; 3.4 One-Factor Repeated Measurement Design and Analysis; 3.5 Summary; PART II ESSENTIALS OF REGRESSION ANALYSIS; 4 Simple Linear Regression; 4.1 Introduction; 4.2 Comparison of Simple Regression and ANOVA; 4.3 Regression Estimation, Inference, and Interpretation 4.4 Diagnostic Methods: Is the Model Apt?4.5 Summary; 5 Essentials of Multiple Linear Regression; 5.1 Introduction; 5.2 Multiple Regression: Two-Predictor Case; 5.3 General Multiple Linear Regression: m Predictors; 5.4 Alternatives to OLS Regression; 5.5 Summary; PART III ESSENTIALS OF SIMPLE AND MULTIPLE ANCOVA; 6 One-Factor Analysis of Covariance; 6.1 Introduction; 6.2 Analysis of Covariance Model; 6.3 Computation and Rationale; 6.4 Adjusted Means; 6.5 ANCOVA Example 1: Training Effects; 6.6 Testing Homogeneity of Regression Slopes; 6.7 ANCOVA Example 2: Sexual Activity Reduces Lifespan 6.8 Software 6.9 Summary; 7 Analysis of Covariance Through Linear Regression; 7.1 Introduction; 7.2 Simple Analysis of Variance Through Linear Regression; 7.3 Analysis of Covariance Through Linear Regression; 7.4 Computation of Adjusted Means; 7.5 Similarity of ANCOVA to Part and Partial Correlation Methods; 7.6 Homogeneity of Regression Test Through General Linear Regression; 7.7 Summary; 8 Assumptions and Design Considerations; 8.1 Introduction; 8.2 Statistical Assumptions; 8.3 Design and Data Issues Related to the Interpretation of ANCOVA; 8.4 Summary 9 Multiple Comparison Tests and Confidence Intervals 9.1 Introduction; 9.2 Overview of Four Multiple Comparison Procedures; 9.3 Tests on All Pairwise Comparisons: Fisher-Hayter; 9.4 All Pairwise Simultaneous Confidence Intervals and Tests: Tukey-Kramer; 9.5 Planned Pairwise and Complex Comparisons: Bonferroni; 9.7 Ignore Multiple Comparison Procedures?; 9.8 Summary; 10 Multiple Covariance Analysis; 10.1 Introduction; 10.2 Multiple ANCOVA Through Multiple Regression; 10.3 Testing Homogeneity of Regression Planes; 10.4 Computation of Adjusted Means 10.5 Multiple Comparison Procedures for Multiple ANCOVA |
| Record Nr. | UNINA-9910139563203321 |
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Huitema Bradley E. <1938->
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| Hoboken, N.J., : Wiley, c2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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The analysis of covariance and alternatives [[electronic resource] ] : statistical methods for experiments, quasi-experiments, and single-case studies / / Bradley Huitema
| The analysis of covariance and alternatives [[electronic resource] ] : statistical methods for experiments, quasi-experiments, and single-case studies / / Bradley Huitema |
| Autore | Huitema Bradley E. <1938-> |
| Edizione | [2nd ed.] |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley, c2011 |
| Descrizione fisica | 1 online resource (690 p.) |
| Disciplina |
519.5/38
519.535 |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Analysis of covariance
Regression analysis |
| ISBN |
1-283-33209-4
9786613332097 1-118-06747-9 1-118-06746-0 1-118-06745-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
The Analysis of Covariance and Alternatives; Contents; Preface; PART I BASIC EXPERIMENTAL DESIGN AND ANALYSIS; 1 Review of Basic Statistical Methods; 1.1 Introduction; 1.2 Elementary Statistical Inference; 1.3 Elementary Statistical Decision Theory; 1.4 Effect Size; 1.5 Measures of Association; 1.6 A Practical Alternative to Effect Sizes and Measures of Association That Is Relevant to the Individual: p(YTx > YControl); 1.7 Generalization of Results; 1.8 Control of Nuisance Variation; 1.9 Software; 1.10 Summary; 2 Review of Simple Correlated Samples Designs and Associated Analyses
2.1 Introduction 2.2 Two-Level Correlated Samples Designs; 2.3 Software; 2.4 Summary; 3 ANOVA Basics for One-Factor Randomized Group, Randomized Block, and Repeated Measurement Designs; 3.1 Introduction; 3.2 One-Factor Randomized Group Design and Analysis; 3.3 One-Factor Randomized Block Design and Analysis; 3.4 One-Factor Repeated Measurement Design and Analysis; 3.5 Summary; PART II ESSENTIALS OF REGRESSION ANALYSIS; 4 Simple Linear Regression; 4.1 Introduction; 4.2 Comparison of Simple Regression and ANOVA; 4.3 Regression Estimation, Inference, and Interpretation 4.4 Diagnostic Methods: Is the Model Apt?4.5 Summary; 5 Essentials of Multiple Linear Regression; 5.1 Introduction; 5.2 Multiple Regression: Two-Predictor Case; 5.3 General Multiple Linear Regression: m Predictors; 5.4 Alternatives to OLS Regression; 5.5 Summary; PART III ESSENTIALS OF SIMPLE AND MULTIPLE ANCOVA; 6 One-Factor Analysis of Covariance; 6.1 Introduction; 6.2 Analysis of Covariance Model; 6.3 Computation and Rationale; 6.4 Adjusted Means; 6.5 ANCOVA Example 1: Training Effects; 6.6 Testing Homogeneity of Regression Slopes; 6.7 ANCOVA Example 2: Sexual Activity Reduces Lifespan 6.8 Software 6.9 Summary; 7 Analysis of Covariance Through Linear Regression; 7.1 Introduction; 7.2 Simple Analysis of Variance Through Linear Regression; 7.3 Analysis of Covariance Through Linear Regression; 7.4 Computation of Adjusted Means; 7.5 Similarity of ANCOVA to Part and Partial Correlation Methods; 7.6 Homogeneity of Regression Test Through General Linear Regression; 7.7 Summary; 8 Assumptions and Design Considerations; 8.1 Introduction; 8.2 Statistical Assumptions; 8.3 Design and Data Issues Related to the Interpretation of ANCOVA; 8.4 Summary 9 Multiple Comparison Tests and Confidence Intervals 9.1 Introduction; 9.2 Overview of Four Multiple Comparison Procedures; 9.3 Tests on All Pairwise Comparisons: Fisher-Hayter; 9.4 All Pairwise Simultaneous Confidence Intervals and Tests: Tukey-Kramer; 9.5 Planned Pairwise and Complex Comparisons: Bonferroni; 9.7 Ignore Multiple Comparison Procedures?; 9.8 Summary; 10 Multiple Covariance Analysis; 10.1 Introduction; 10.2 Multiple ANCOVA Through Multiple Regression; 10.3 Testing Homogeneity of Regression Planes; 10.4 Computation of Adjusted Means 10.5 Multiple Comparison Procedures for Multiple ANCOVA |
| Record Nr. | UNINA-9910817784903321 |
|
Huitema Bradley E. <1938->
|
||
| Hoboken, N.J., : Wiley, c2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Analysis of Three Different Regression Models to Estimate the Ballistic Performance of New and Environmentally Conditioned Body Armor / / Diane Mauchant, Kirk D. Rice, Michael A. Riley, Dennis Leber, Daniel Samarov, and Amanda L. Forster
| Analysis of Three Different Regression Models to Estimate the Ballistic Performance of New and Environmentally Conditioned Body Armor / / Diane Mauchant, Kirk D. Rice, Michael A. Riley, Dennis Leber, Daniel Samarov, and Amanda L. Forster |
| Autore | Mauchant Diane |
| Pubbl/distr/stampa | [Gaithersburg, MD] : , : U.S. Dept. of Commerce, National Institute of Standards and Technology, , [2011] |
| Descrizione fisica | 1 online resource (xvi, 35 pages) : illustrations (some color) |
| Collana | NISTIR |
| Soggetto topico |
Ballistics
Body armor Logistic regression analysis Regression analysis |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910709936503321 |
|
Mauchant Diane
|
||
| [Gaithersburg, MD] : , : U.S. Dept. of Commerce, National Institute of Standards and Technology, , [2011] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
