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Produktbild: Simplicity, Complexity and Modelling

Simplicity, Complexity and Modelling

Aus der Reihe Statistics in Practice

132,99 €

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Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

07.11.2011

Herausgeber

Mike Christie + weitere

Verlag

John Wiley & Sons

Seitenzahl

220

Maße (L/B/H)

23,4/15,5/1,5 cm

Gewicht

458 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-0-470-74002-6

Beschreibung

Rezension

"In short, this book offers plenty. While reading it cannot entirely replace first-hand experience of actually working with statistical modelling, I think it can be highly useful, either for a course on Ph.D. level, or for a statistician setting out on her own to improve her competence in applying statistical techniques and modelling in non-trivial situations.
( International Statistical Review , 1 December 2012)

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

07.11.2011

Herausgeber

Verlag

John Wiley & Sons

Seitenzahl

220

Maße (L/B/H)

23,4/15,5/1,5 cm

Gewicht

458 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-0-470-74002-6

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

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  • Produktbild: Simplicity, Complexity and Modelling
  • Preface ix
     
    Acknowledgements xi
     
    Contributing authors xiii
     
    1 Introduction 1
    Mike Christie, Andrew Cliffe, Philip Dawid and Stephen Senn
     
    1.1 The origins of the SCAM project 1
     
    1.2 The scope of modelling in the modern world 2
     
    1.3 The different professions and traditions engaged in modelling 3
     
    1.4 Different types of models 3
     
    1.5 Different purposes for modelling 5
     
    1.6 The purpose of the book 6
     
    1.7 Overview of the chapters 6
     
    References 8
     
    2 Statistical model selection 11
    Philip Dawid and Stephen Senn
     
    2.1 Introduction 11
     
    2.2 Explanation or prediction? 12
     
    2.3 Levels of uncertainty 12
     
    2.4 Bias-variance trade-off 13
     
    2.5 Statistical models 15
     
    2.5.1 Within-model inference 16
     
    2.6 Model comparison 18
     
    2.7 Bayesian model comparison 18
     
    2.7.1 Model uncertainty 19
     
    2.7.2 Laplace approximation 20
     
    2.8 Penalized likelihood 20
     
    2.8.1 Bayesian information criterion 21
     
    2.9 The Akaike information criterion 21
     
    2.9.1 Inconsistency of AIC 23
     
    2.10 Significance testing 23
     
    2.11 Many variables 27
     
    2.12 Data-driven approaches 28
     
    2.12.1 Cross-validation 29
     
    2.12.2 Prequential analysis 29
     
    2.13 Model selection or model averaging? 30
     
    References 31
     
    3 Modelling in drug development 35
    Stephen Senn
     
    3.1 Introduction 35
     
    3.2 The nature of drug development and scope for statistical modelling 36
     
    3.3 Simplicity versus complexity in phase III trials 36
     
    3.3.1 The nature of phase III trials 36
     
    3.3.2 The case for simplicity in analysing phase III trials 37
     
    3.3.3 The case for complexity in modelling clinical trials 38
     
    3.4 Some technical issues 39
     
    3.4.1 The effect of covariate adjustment in linear models 40
     
    3.4.2 The effect of covariate adjustment in non-linear models 42
     
    3.4.3 Random effects in multi-centre trials 44
     
    3.4.4 Subgroups and interactions 45
     
    3.4.5 Bayesian approaches 46
     
    3.5 Conclusion 46
     
    3.6 Appendix: The effect of covariate adjustment on the variance multiplier in least squares 47
     
    References 48
     
    4 Modelling with deterministic computer models 51
    Jeremy E. Oakley
     
    4.1 Introduction 51
     
    4.2 Metamodels and emulators for computationally expensive simulators 52
     
    4.2.1 Gaussian processes emulators 53
     
    4.2.2 Multivariate outputs 56
     
    4.3 Uncertainty analysis 57
     
    4.4 Sensitivity analysis 58
     
    4.4.1 Variance-based sensitivity analysis 58
     
    4.4.2 Value of information 61
     
    4.5 Calibration and discrepancy 63
     
    4.6 Discussion 64
     
    References 65
     
    5 Modelling future climates 69
    Peter Challenor and Robin Tokmakian
     
    5.1 Introduction 69
     
    5.2 What is the risk from climate change? 70
     
    5.3 Climate models 70
     
    5.4 An anatomy of uncertainty 72
     
    5.4.1 Aleatoric uncertainty 72
     
    5.4.2 Epistemic uncertainty 73
     
    5.5 Simplicity and complexity 75
     
    5.6 An example: The collapse of the thermohaline circulation 77
     
    5.7 Conclusions 79
     
    References 79
     
    6 Modelling climate change impacts for adaptation assessments 83
    Suraje Dessai and Jeroen van der Sluijs
     
    6.1 Introduction 83
     
    6.1.1 Climate impact assessment 84
     
    6.2 Modelling climate change impacts: From world development paths to localized impacts 87
     
    6.2.1 Greenhouse gas emissions 87