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Spatial Microsimulation: A Reference Guide for Users

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Cover of 'Spatial Microsimulation: A Reference Guide for Users'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction to Spatial Microsimulation: History, Methods and Applications
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    Chapter 2 Building a Static Spatial Microsimulation Model: Data Preparation
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    Chapter 3 An Evaluation of Two Synthetic Small-Area Microdata Simulation Methodologies: Synthetic Reconstruction and Combinatorial Optimisation
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    Chapter 4 Estimating Small-Area Income Deprivation: An Iterative Proportional Fitting Approach
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    Chapter 5 SimObesity: Combinatorial Optimisation (Deterministic) Model
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    Chapter 6 Spatial Microsimulation Using a Generalised Regression Model
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    Chapter 7 Creating a Spatial Microsimulation Model of the Irish Local Economy
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    Chapter 8 Linking Static Spatial Microsimulation Modelling to Meso-scale Models: The Relationship Between Access to GP Services and Long-Term Illness
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    Chapter 9 Projections Using a Static Spatial Microsimulation Model
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    Chapter 10 Limits of Static Spatial Microsimulation Models
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    Chapter 11 Moses: A Dynamic Spatial Microsimulation Model for Demographic Planning
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    Chapter 12 Design Principles for Micro Models
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    Chapter 13 SimEducation: A Dynamic Spatial Microsimulation Model for Understanding Educational Inequalities
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    Chapter 14 Challenges for Spatial Dynamic Microsimulation Modelling
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    Chapter 15 Validation of Spatial Microsimulation Models
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    Chapter 16 Conclusions and Future Research Directions
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Citations

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Title
Spatial Microsimulation: A Reference Guide for Users
Published by
Springer Netherlands, November 2012
DOI 10.1007/978-94-007-4623-7
ISBNs
978-9-40-074622-0, 978-9-40-074623-7
Editors

Tanton, Robert, Edwards, Kimberley

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Australia 2 3%
Iceland 1 2%
United States 1 2%
Unknown 56 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 27%
Researcher 10 17%
Student > Doctoral Student 6 10%
Professor > Associate Professor 4 7%
Student > Master 4 7%
Other 8 13%
Unknown 12 20%
Readers by discipline Count As %
Economics, Econometrics and Finance 13 22%
Social Sciences 9 15%
Environmental Science 5 8%
Engineering 5 8%
Computer Science 3 5%
Other 11 18%
Unknown 14 23%