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Introduction to nonparametric regression [[electronic resource] /] / Kunio Takezawa
| Introduction to nonparametric regression [[electronic resource] /] / Kunio Takezawa |
| Autore | Takezawa Kunio <1959-> |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Interscience, c2006 |
| Descrizione fisica | 1 online resource (566 p.) |
| Disciplina |
519.5/36
519.536 |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Regression analysis
Nonparametric statistics |
| ISBN |
1-280-28698-9
9786610286980 0-470-36261-8 0-471-77145-7 0-471-77144-9 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
INTRODUCTION TO NONPARAMETRIC REGRESSION; CONTENTS; Preface; Acknowledgments; 1 Exordium; 1.1 Introduction; 1.2 Are the moving average and Fourier series sufficiently useful?; 1.3 Is a histogram or normal distribution sufficiently powerful?; 1.4 Is interpolation sufficiently powerful?; 1.5 Should we use a descriptive equation?; 1.6 Parametric regression and nonparametric regression; 2 Smoothing for data with an equispaced predictor; 2.1 Introduction; 2.2 Moving average and binomial filter; 2.3 Hat matrix; 2.4 Local linear regression; 2.5 Smoothing spline
2.6 Analysis on eigenvalue of hat matrix2.7 Examples of S-Plus object; References; Problems; 3 Nonparametric regression for one-dimensional predictor; 3.1 Introduction; 3.2 Trade-off between bias and variance; 3.3 Index to select beneficial regression equations; 3.4 Nadaraya-Watson estimator; 3.5 Local polynomial regression; 3.6 Natural spline and smoothing spline; 3.7 LOESS; 3.8 Supersmoother; 3.9 LOWESS; 3.10 Examples of S-Plus object; References; Problems; 4 Multidimensional smoothing; 4.1 Introduction; 4.2 Local polynomial regression for multidimensional predictor 4.3 Thin plate smoothing splines4.4 LOESS and LOWESS with plural predictors; 4.5 Kriging; 4.6 Additive model; 4.7 ACE; 4.8 Projection pursuit regression; 4.9 Examples of S-Plus object; References; Problems; 5 Nonparametric regression with predictors represented as distributions; 5.1 Introduction; 5.2 Use of distributions as predictors; 5.3 Nonparametric DVR method; 5.4 Form of nonparametric regression with predictors represented as distributions; 5.5 Examples of S-Plus object; References; Problems; 6 Smoothing of histograms and nonparametric probability density functions; 6.1 Introduction 6.2 Histogram6.3 Smoothing a histogram; 6.4 Nonparametnc probability density function; 6.5 Examples of S-Plus object; References; Problems; 7 Pattern recognition; 7.1 Introduction; 7.2 Bayes' decision rule; 7.3 Linear discriminant rule and quadratic discriminant rule; 7.4 Classification using nonparametric probability density function; 7.5 Logistic regression; 7.6 Neural networks; 7.7 Tree-based model; 7.8 k-nearest-neighbor classifier; 7.9 Nonparametric regression based on the least squares; 7.10 Transformation of feature vectors; 7.11 Examples of S-Plus object; References; Problems Appendix A: Creation and applications of B-spline basesA.1 Introduction; A.2 Method to create B-spline basis; A.3 Natural spline created by B-spline; A.4 Application to smoothing spline; A.5 Examples of S-Plus object; References; Appendix B: R objects; B.1 Introduction; B.2 Transformation of S-Plus objects in Chapter 2; B.3 Transformation of S-Plus objects in Chapter 3; B.4 Transformation of S-Plus objects in Chapter 4; B.5 Transformation of S-Plus objects in Chapter 5; B.6 Transformation of S-Plus objects in Chapter 6; B.7 Transformation of S-Plus objects in Chapter 7 B.8 Transformation of S-Plus objects in Appendix A |
| Record Nr. | UNINA-9910829967303321 |
Takezawa Kunio <1959->
|
||
| Hoboken, N.J., : Wiley-Interscience, c2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Introduction to nonparametric regression [[electronic resource] /] / Kunio Takezawa
| Introduction to nonparametric regression [[electronic resource] /] / Kunio Takezawa |
| Autore | Takezawa Kunio <1959-> |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Interscience, c2006 |
| Descrizione fisica | 1 online resource (566 p.) |
| Disciplina |
519.5/36
519.536 |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Regression analysis
Nonparametric statistics |
| ISBN |
1-280-28698-9
9786610286980 0-470-36261-8 0-471-77145-7 0-471-77144-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
INTRODUCTION TO NONPARAMETRIC REGRESSION; CONTENTS; Preface; Acknowledgments; 1 Exordium; 1.1 Introduction; 1.2 Are the moving average and Fourier series sufficiently useful?; 1.3 Is a histogram or normal distribution sufficiently powerful?; 1.4 Is interpolation sufficiently powerful?; 1.5 Should we use a descriptive equation?; 1.6 Parametric regression and nonparametric regression; 2 Smoothing for data with an equispaced predictor; 2.1 Introduction; 2.2 Moving average and binomial filter; 2.3 Hat matrix; 2.4 Local linear regression; 2.5 Smoothing spline
2.6 Analysis on eigenvalue of hat matrix2.7 Examples of S-Plus object; References; Problems; 3 Nonparametric regression for one-dimensional predictor; 3.1 Introduction; 3.2 Trade-off between bias and variance; 3.3 Index to select beneficial regression equations; 3.4 Nadaraya-Watson estimator; 3.5 Local polynomial regression; 3.6 Natural spline and smoothing spline; 3.7 LOESS; 3.8 Supersmoother; 3.9 LOWESS; 3.10 Examples of S-Plus object; References; Problems; 4 Multidimensional smoothing; 4.1 Introduction; 4.2 Local polynomial regression for multidimensional predictor 4.3 Thin plate smoothing splines4.4 LOESS and LOWESS with plural predictors; 4.5 Kriging; 4.6 Additive model; 4.7 ACE; 4.8 Projection pursuit regression; 4.9 Examples of S-Plus object; References; Problems; 5 Nonparametric regression with predictors represented as distributions; 5.1 Introduction; 5.2 Use of distributions as predictors; 5.3 Nonparametric DVR method; 5.4 Form of nonparametric regression with predictors represented as distributions; 5.5 Examples of S-Plus object; References; Problems; 6 Smoothing of histograms and nonparametric probability density functions; 6.1 Introduction 6.2 Histogram6.3 Smoothing a histogram; 6.4 Nonparametnc probability density function; 6.5 Examples of S-Plus object; References; Problems; 7 Pattern recognition; 7.1 Introduction; 7.2 Bayes' decision rule; 7.3 Linear discriminant rule and quadratic discriminant rule; 7.4 Classification using nonparametric probability density function; 7.5 Logistic regression; 7.6 Neural networks; 7.7 Tree-based model; 7.8 k-nearest-neighbor classifier; 7.9 Nonparametric regression based on the least squares; 7.10 Transformation of feature vectors; 7.11 Examples of S-Plus object; References; Problems Appendix A: Creation and applications of B-spline basesA.1 Introduction; A.2 Method to create B-spline basis; A.3 Natural spline created by B-spline; A.4 Application to smoothing spline; A.5 Examples of S-Plus object; References; Appendix B: R objects; B.1 Introduction; B.2 Transformation of S-Plus objects in Chapter 2; B.3 Transformation of S-Plus objects in Chapter 3; B.4 Transformation of S-Plus objects in Chapter 4; B.5 Transformation of S-Plus objects in Chapter 5; B.6 Transformation of S-Plus objects in Chapter 6; B.7 Transformation of S-Plus objects in Chapter 7 B.8 Transformation of S-Plus objects in Appendix A |
| Record Nr. | UNINA-9910841700203321 |
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Takezawa Kunio <1959->
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||
| Hoboken, N.J., : Wiley-Interscience, c2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Introduction to statistical mediation analysis / David P. MacKinnon
| Introduction to statistical mediation analysis / David P. MacKinnon |
| Autore | MACKINNON, David Peter |
| Pubbl/distr/stampa | New York : Lawrence Erlbaum Associates, c2008 |
| Descrizione fisica | x, 477 p. : ill. ; 24 cm. + Cd Rom |
| Disciplina | 519.536(Analisi della regressione) |
| Collana | Multivariate applications series |
| Soggetto topico | Analisi della regressione |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-990005556080203316 |
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MACKINNON, David Peter
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| New York : Lawrence Erlbaum Associates, c2008 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Introduction to Statistical Mediation Analysis [[electronic resource]]
| Introduction to Statistical Mediation Analysis [[electronic resource]] |
| Autore | MacKinnon David |
| Pubbl/distr/stampa | Hoboken, : Lawrence Erlbaum Associates, 2008 |
| Descrizione fisica | 1 online resource (490 p.) |
| Disciplina | 519.536 |
| Collana | Multivariate Applications Series 0 |
| Soggetto topico |
Mediation (Statistics)
Mathematics |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-281-37226-9
9786611372262 1-4106-1861-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front cover; Contents; Preface; Chapter 1. Introduction; Chapter 2. Applications of the Mediation Model; Chapter 3. Single Mediator Model; Chapter 4. Single Mediator Model Details; Chapter 5. Multiple Mediator Model; Chapter 6. Path Analysis Mediation Models; Chapter 7. Latent Variable Mediation Models; Chapter 8. Longitudinal Mediation Models; Chapter 9. Multilevel Mediation Models; Chapter 10. Mediation and Moderation; Chapter 11. Mediation in Cateegorical Data Analysis; Chapter 12. Computer Intensive Methods for Mediation Analysis; Chapter 13. Causal Inference for Mediation Models
Chapter 14. Additional Approaches to Identifying Mediating VariablesChapter 15. Conclusions and Future Directions; Appendix A: Answers to Odd-Numbered Exercises; Appendix B: Notation; Author Index; Subject Index; Back cover; |
| Record Nr. | UNINA-9910452197003321 |
|
MacKinnon David
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||
| Hoboken, : Lawrence Erlbaum Associates, 2008 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Introduction to Statistical Mediation Analysis [[electronic resource]]
| Introduction to Statistical Mediation Analysis [[electronic resource]] |
| Autore | MacKinnon David |
| Pubbl/distr/stampa | Hoboken, : Lawrence Erlbaum Associates, 2008 |
| Descrizione fisica | 1 online resource (490 p.) |
| Disciplina | 519.536 |
| Collana | Multivariate Applications Series 0 |
| Soggetto topico |
Mediation (Statistics)
Mathematics |
| ISBN |
1-136-67613-9
1-281-37226-9 9786611372262 1-4106-1861-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front cover; Contents; Preface; Chapter 1. Introduction; Chapter 2. Applications of the Mediation Model; Chapter 3. Single Mediator Model; Chapter 4. Single Mediator Model Details; Chapter 5. Multiple Mediator Model; Chapter 6. Path Analysis Mediation Models; Chapter 7. Latent Variable Mediation Models; Chapter 8. Longitudinal Mediation Models; Chapter 9. Multilevel Mediation Models; Chapter 10. Mediation and Moderation; Chapter 11. Mediation in Cateegorical Data Analysis; Chapter 12. Computer Intensive Methods for Mediation Analysis; Chapter 13. Causal Inference for Mediation Models
Chapter 14. Additional Approaches to Identifying Mediating VariablesChapter 15. Conclusions and Future Directions; Appendix A: Answers to Odd-Numbered Exercises; Appendix B: Notation; Author Index; Subject Index; Back cover; |
| Record Nr. | UNINA-9910778336703321 |
|
MacKinnon David
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||
| Hoboken, : Lawrence Erlbaum Associates, 2008 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Introduction to Statistical Mediation Analysis [[electronic resource]]
| Introduction to Statistical Mediation Analysis [[electronic resource]] |
| Autore | MacKinnon David |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Hoboken, : Lawrence Erlbaum Associates, 2008 |
| Descrizione fisica | 1 online resource (490 p.) |
| Disciplina | 519.536 |
| Collana | Multivariate Applications Series 0 |
| Soggetto topico |
Mediation (Statistics)
Mathematics |
| ISBN |
1-136-67613-9
1-281-37226-9 9786611372262 1-4106-1861-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front cover; Contents; Preface; Chapter 1. Introduction; Chapter 2. Applications of the Mediation Model; Chapter 3. Single Mediator Model; Chapter 4. Single Mediator Model Details; Chapter 5. Multiple Mediator Model; Chapter 6. Path Analysis Mediation Models; Chapter 7. Latent Variable Mediation Models; Chapter 8. Longitudinal Mediation Models; Chapter 9. Multilevel Mediation Models; Chapter 10. Mediation and Moderation; Chapter 11. Mediation in Cateegorical Data Analysis; Chapter 12. Computer Intensive Methods for Mediation Analysis; Chapter 13. Causal Inference for Mediation Models
Chapter 14. Additional Approaches to Identifying Mediating VariablesChapter 15. Conclusions and Future Directions; Appendix A: Answers to Odd-Numbered Exercises; Appendix B: Notation; Author Index; Subject Index; Back cover; |
| Record Nr. | UNINA-9910808614203321 |
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MacKinnon David
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| Hoboken, : Lawrence Erlbaum Associates, 2008 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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La régression PLS : théorie et pratique / Michel Tenenhaus
| La régression PLS : théorie et pratique / Michel Tenenhaus |
| Autore | Tenenhaus, Michel |
| Pubbl/distr/stampa | Paris : Technip, 1998 |
| Descrizione fisica | X, 254 p. ; 25 cm. |
| Disciplina | 519.536 |
| Soggetto topico | Regressione - Statistica |
| ISBN | 978-27-10-80735-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | fre |
| Record Nr. | UNICAMPANIA-SUN0107527 |
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Tenenhaus, Michel
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| Paris : Technip, 1998 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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La régression PLS : théorie et pratique / Michel Tenenhaus
| La régression PLS : théorie et pratique / Michel Tenenhaus |
| Autore | Tenenhaus, Michel |
| Pubbl/distr/stampa | Paris, : Technip, 1998 |
| Descrizione fisica | X, 254 p. ; 25 cm. |
| Disciplina | 519.536 |
| Soggetto topico | Regressione - Statistica |
| ISBN | 978-27-10-80735-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | fre |
| Record Nr. | UNICAMPANIA-VAN0107527 |
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Tenenhaus, Michel
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| Paris, : Technip, 1998 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Learning regression analysis by simulation / / Kunio Takezawa
| Learning regression analysis by simulation / / Kunio Takezawa |
| Autore | Takezawa Kunio <1959-> |
| Pubbl/distr/stampa | Tokyo : , : Springer, , [2014] |
| Descrizione fisica | 1 online resource (xii, 300 pages) : illustrations |
| Disciplina | 519.536 |
| Soggetto topico |
Regression analysis - Simulation methods
Statistical Theory and Methods Statistics and Computing/Statistics Programs Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences |
| ISBN |
4-431-54321-X
9784431543213 9784431543206 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Preface; Acknowledgments; Contents; Chapter 1: Linear Algebra; 1.1 Starting Up and Executing R; 1.2 Vectors; 1.3 Matrices; 1.4 Addition of Two Matrices; 1.5 Multiplying Two Matrices; 1.6 Identity and Inverse Matrices; 1.7 Simultaneous Equations; 1.8 Diagonalization of a Symmetric Matrix; 1.9 Quadratic Forms; References; Chapter 2: Distributions and Tests; 2.1 Sampling and Random Variables; 2.2 Probability Distribution; 2.3 Normal Distribution and the Central Limit Theorem; 2.4 Interval Estimation by t Distribution; 2.5 t-Test
2.6 Interval Estimation of Population Varianceand the χ2 Distribution2.7 F Distribution and F-Test; 2.8 Wilcoxon Signed-Rank Sum Test; References; Chapter 3: Simple Regression; 3.1 Derivation of Regression Coefficients; 3.2 Exchange Between Predictor Variable and Target Variable; 3.3 Regression to the Mean; 3.4 Confidence Interval of Regression Coefficients in Simple Regression; 3.5 t-Test in Simple Regression; 3.6 F-Test on Simple Regression; 3.7 Selection Between Constant and Nonconstant Regression Equations; 3.8 Prediction Error of Simple Regression; 3.9 Weighted Regression 3.10 Least Squares Method and Prediction ErrorReferences; Chapter 4: Multiple Regression; 4.1 Derivation of Regression Coefficients; 4.2 Test on Multiple Regression; 4.3 Prediction Error on Multiple Regression; 4.4 Notes on Model Selection Using Prediction Error; 4.5 Polynomial Regression; 4.6 Variance of Regression Coefficient and Multicollinearity; 4.7 Detection of Multicollinearity Using Variance Inflation Factors; 4.8 Hessian Matrix of Log-Likelihood; References; Chapter 5: Akaike's Information Criterion (AIC) and the Third Variance; 5.1 Cp and FPE 5.2 AIC of a Multiple Regression Equation with Independent and Identical Normal Distribution5.3 Derivation of AIC for Multiple Regression; 5.4 AIC with Unbiased Estimator for Error Variance; 5.5 Error Variance by Maximizing Expectationof Log-Likelihood in Light of the Datain the Future and the ``Third Variance''; 5.6 Relationship Between AIC (or GCV) and F-Test; 5.7 AIC on Poisson Regression; References; Chapter 6: Linear Mixed Model; 6.1 Random-Effects Model; 6.2 Random Intercept Model; 6.3 Random Intercept and Slope Model; 6.4 Generalized Linear Mixed Model 6.5 Generalized Additive Mixed ModelIndex |
| Record Nr. | UNINA-9910300145603321 |
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Takezawa Kunio <1959->
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| Tokyo : , : Springer, , [2014] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Linear models : least squares and alternatives / C. Radhakrishna Rao, Helge Toutenburg ; with contributions by Andreas Fieger
| Linear models : least squares and alternatives / C. Radhakrishna Rao, Helge Toutenburg ; with contributions by Andreas Fieger |
| Autore | Rao, Calyampudi Radhakrishna <1920- > |
| Edizione | [2. ed] |
| Pubbl/distr/stampa | New York : Springer, ©1999 |
| Descrizione fisica | XV, 427 p. ; 25 cm |
| Disciplina | 519.536 |
| Altri autori (Persone) | Toutenburg, Helge |
| Collana | Springer series in statistics |
| ISBN | 0-387-98848-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-990007382220403321 |
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Rao, Calyampudi Radhakrishna <1920- >
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| New York : Springer, ©1999 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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