2000, ISBN: 9780387950174

This book is about using graphs to understand the relationship between a regression model and the data to which it is fitted. Because of the way in which models are fitted, for example, by least squares, we can lose infor mation about the effect of individual observations on inferences about the form and parameters of the model. The methods developed in this book reveal how the fitted regression model depends on individual observations and on groups of observations. Robust procedures can sometimes reveal this structure, but downweight or discard some observations. The novelty in our book is to combine robustness and a forward' ' search through the data with regression diagnostics and computer graphics. We provide easily understood plots that use information from the whole sample to display the effect of each observation on a wide variety of aspects of the fitted model. This bald statement of the contents of our book masks the excitement we feel about the methods we have developed based on the forward search. We are continuously amazed, each time we analyze a new set of data, by the amount of information the plots generate and the insights they provide. We believe our book uses comparatively elementary methods to move regression in a completely new and useful direction. We have written the book to be accessible to students and users of statistical methods, as well as for professional statisticians. Buch (fremdspr.) Anthony Atkinson#Marco Riani gebundene Ausgabe, Springer US, 11.08.2000, Springer US, 2000

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2000, ISBN: 9780387950174

This book is about using graphs to understand the relationship between a regression model and the data to which it is fitted. Because of the way in which models are fitted, for example, by least squares, we can lose infor mation about the effect of individual observations on inferences about the form and parameters of the model. The methods developed in this book reveal how the fitted regression model depends on individual observations and on groups of observations. Robust procedures can sometimes reveal this structure, but downweight or discard some observations. The novelty in our book is to combine robustness and a forward' ' search through the data with regression diagnostics and computer graphics. We provide easily understood plots that use information from the whole sample to display the effect of each observation on a wide variety of aspects of the fitted model. This bald statement of the contents of our book masks the excitement we feel about the methods we have developed based on the forward search. We are continuously amazed, each time we analyze a new set of data, by the amount of information the plots generate and the insights they provide. We believe our book uses comparatively elementary methods to move regression in a completely new and useful direction. We have written the book to be accessible to students and users of statistical methods, as well as for professional statisticians. Buch (fremdspr.) Anthony Atkinson#Marco Riani gebundene Ausgabe, Springer Us, 11.08.2000, Springer Us, 2000

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ISBN: 9780387950174

This book is about using graphs to understand the relationship between a regression model and the data to which it is fitted. Because of the way in which models are fitted, for example, by least squares, we can lose inforÂ mation about the effect of individual observations on inferences about the form and parameters of the model. The methods developed in this book reveal how the fitted regression model depends on individual observations and on groups of observations. Robust procedures can sometimes reveal this structure, but downweight or discard some observations. The novelty in our book is to combine robustness and a forward" " search through the data with regression diagnostics and computer graphics. We provide easily understood plots that use information from the whole sample to display the effect of each observation on a wide variety of aspects of the fitted model. This bald statement of the contents of our book masks the excitement we feel about the methods we have developed based on the forward search. We are continuously amazed, each time we analyze a new set of data, by the amount of information the plots generate and the insights they provide. We believe our book uses comparatively elementary methods to move regression in a completely new and useful direction. We have written the book to be accessible to students and users of statistical methods, as well as for professional statisticians. Books > Mathematics Hard cover, Springer Shop

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2000, ISBN: 9780387950174

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2000, ISBN: 9780387950174

This book is about using graphs to understand the relationship between a regression model and the data to which it is fitted. Because of the way in which models are fitted, for example, b… More...

2000, ISBN: 9780387950174

This book is about using graphs to understand the relationship between a regression model and the data to which it is fitted. Because of the way in which models are fitted, for example, b… More...

## ISBN: 9780387950174

This book is about using graphs to understand the relationship between a regression model and the data to which it is fitted. Because of the way in which models are fitted, for example, b… More...

2000, ISBN: 9780387950174

Buch, Hardcover, [PU: Springer-Verlag New York Inc.], Springer-Verlag New York Inc., 2000

2000, ISBN: 9780387950174

Hardcover, Buch, [PU: Springer-Verlag New York Inc.]

Author: | |

Title: | |

ISBN: |

** Details of the book - Robust Diagnostic Regression Analysis**

EAN (ISBN-13): 9780387950174

ISBN (ISBN-10): 0387950176

Hardcover

Publishing year: 2000

Publisher: Springer-Verlag New York Inc.

327 Pages

Weight: 0,684 kg

Language: eng/Englisch

Book in our database since 2007-05-12T02:25:29-04:00 (New York)

Detail page last modified on 2021-10-10T06:42:26-04:00 (New York)

ISBN/EAN: 0387950176

ISBN - alternate spelling:

0-387-95017-6, 978-0-387-95017-4

### Information from Publisher

Author: Anthony Atkinson; Marco Riani

Title: Springer Series in Statistics; Robust Diagnostic Regression Analysis

Publisher: Springer; Springer US

328 Pages

Publishing year: 2000-08-11

New York; NY; US

Weight: 1,470 kg

Language: English

128,39 € (DE)

131,99 € (AT)

141,50 CHF (CH)

POD

BB; Book; Hardcover, Softcover / Mathematik/Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik; Wahrscheinlichkeitsrechnung und Statistik; Verstehen; Generalized linear model; Likelihood; Regression Analysis; Robust Statistics; Variance; best fit; data analysis; B; Probability Theory and Stochastic Processes; Statistical Theory and Methods; Probability Theory; Statistical Theory and Methods; Mathematics and Statistics; Stochastik; Wahrscheinlichkeitsrechnung und Statistik; BC; EA

1 Some Regression Examples.- 1.1 Influence and Outliers.- 1.2 Three Examples.- 1.2.1 Forbes’ Data.- 1.2.2 Multiple Regression Data.- 1.2.3 Wool Data.- 1.3 Checking and Building Models.- 2 Regression and the Forward Search.- 2.1 Least Squares.- 2.1.1 Parameter Estimates.- 2.1.2 Residuals and Leverage.- 2.1.3 Formal Tests.- 2.2 Added Variables.- 2.3 Deletion Diagnostics.- 2.3.1 The Algebra of Deletion.- 2.3.2 Deletion Residuals.- 2.3.3 Cook’s Distance.- 2.4 The Mean Shift Outlier Model.- 2.5 Simulation Envelopes.- 2.6 The Forward Search.- 2.6.1 General Principles.- 2.6.2 Step 1: Choice of the Initial Subset.- 2.6.3 Step 2: Adding Observations During the Forward Search.- 2.6.4 Step 3: Monitoring the Search.- 2.6.5 Forward Deletion Formulae.- 2.7 Further Reading.- 2.8 Exercises.- 2.9 Solutions.- 3 Regression.- 3.1 Hawkins’ Data.- 3.2 Stack Loss Data.- 3.3 Salinity Data.- 3.4 Ozone Data.- 3.5 Exercises.- 3.6 Solutions.- 4 Transformations to Normality.- 4.1 Background.- 4.2 Transformations in Regression.- 4.2.1 Transformation of the Response.- 4.2.2 Graphics for Transformations.- 4.2.3 Transformation of an Explanatory Variable.- 4.3 Wool Data.- 4.4 Poison Data.- 4.5 Modified Poison Data.- 4.6 Doubly Modified Poison Data: An Example of Masking.- 4.7 Multiply Modified Poison Data—More Masking.- 4.7.1 A Diagnostic Analysis.- 4.7.2 A Forward Analysis.- 4.7.3 Other Graphics for Transformations.- 4.8 Ozone Data.- 4.9 Stack Loss Data.- 4.10 Mussels’ Muscles: Transformation of the Response.- 4.11 Transforming Both Sides of a Model.- 4.12 Shortleaf Pine.- 4.13 Other Transformations and Further Reading.- 4.14 Exercises.- 4.15 Solutions.- 5 Nonlinear Least Squares.- 5.1 Background.- 5.1.1 Nonlinear Models.- 5.1.2 Curvature.- 5.2 The Forward Search.- 5.2.1 Parameter Estimation.- 5.2.2 Monitoring the Forward Search.- 5.3 Radioactivity and Molar Concentration of Nifedipene.- 5.4 Enzyme Kinetics.- 5.5 Calcium Uptake.- 5.6 Nitrogen in Lakes.- 5.7 Isomerization ofn-Pentane.- 5.8 Related Literature.- 5.9 Exercises.- 5.10 Solutions.- 6 Generalized Linear Models.- 6.1 Background.- 6.1.1 British Train Accidents.- 6.1.2 Bliss’s Beetle Data.- 6.1.3 The Link Function.- 6.2 The Exponential Family.- 6.3 Mean, Variance, and Likelihood.- 6.3.1 One Observation.- 6.3.2 The Variance Function.- 6.3.3 Canonical Parameterization.- 6.3.4 The Likelihood.- 6.4 Maximum Likelihood Estimation.- 6.4.1 Least Squares.- 6.4.2 Weighted Least Squares.- 6.4.3 Newton’s Method for Solving Equations.- 6.4.4 Fisher Scoring.- 6.4.5 The Algorithm.- 6.5 Inference.- 6.5.1 The Deviance.- 6.5.2 Estimation of the Dispersion Parameter.- 6.5.3 Inference About Parameters.- 6.6 Checking Generalized Linear Models.- 6.6.1 The Hat Matrix.- 6.6.2 Residuals.- 6.6.3 Cook’s Distance.- 6.6.4 A Goodness of Link Test.- 6.6.5 Monitoring the Forward Search.- 6.7 Gamma Models.- 6.8 Car Insurance Data.- 6.9 Dielectric Breakdown Strength.- 6.10 Poisson Models.- 6.11 British Train Accidents.- 6.12 Cellular Differentiation Data.- 6.13 Binomial Models.- 6.14 Bliss’s Beetle Data.- 6.15 Mice with Convulsions.- 6.16 Toxoplasmosis and Rainfall.- 6.16.1 A Forward Analysis.- 6.16.2 Comparison with Backwards Methods.- 6.17 Binary Data.- 6.17.1 Introduction: Vasoconstriction Data.- 6.17.2 The Deviance.- 6.17.3 The Forward Search for Binary Data.- 6.17.4 Perfect Fit.- 6.18 Theory: The Effect of Perfect Fit and the Arcsine Link.- 6.19 Vasoconstriction Data and Perfect Fit.- 6.20 Chapman Data.- 6.21 Developments and Further Reading.- 6.22 Exercises.- 6.23 Solutions.- A Data.- Author Index.This book is about using graphs to understand the relationship between a regression model and the data to which it is fitted. The book is accessible to students and users of statistical methods, as well as for professional statisticians.

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