Overview
- Authors:
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Håkan Andersson
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Group Financial Risk Control, SwedBank, Stockholm, Sweden
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Tom Britton
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Department of Mathematics, Uppsala University, Uppsala, Sweden
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Table of contents (12 chapters)
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Stochastic Modelling
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- Håkan Andersson, Tom Britton
Pages 3-9
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- Håkan Andersson, Tom Britton
Pages 11-18
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- Håkan Andersson, Tom Britton
Pages 19-26
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- Håkan Andersson, Tom Britton
Pages 27-37
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- Håkan Andersson, Tom Britton
Pages 39-49
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- Håkan Andersson, Tom Britton
Pages 51-61
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- Håkan Andersson, Tom Britton
Pages 63-72
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- Håkan Andersson, Tom Britton
Pages 73-83
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Estimation
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- Håkan Andersson, Tom Britton
Pages 87-97
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- Håkan Andersson, Tom Britton
Pages 99-106
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- Håkan Andersson, Tom Britton
Pages 107-115
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- Håkan Andersson, Tom Britton
Pages 117-125
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Back Matter
Pages 127-140
About this book
The present lecture notes describe stochastic epidemic models and methods for their statistical analysis. Our aim is to present ideas for such models, and methods for their analysis; along the way we make practical use of several probabilistic and statistical techniques. This will be done without focusing on any specific disease, and instead rigorously analyzing rather simple models. The reader of these lecture notes could thus have a two-fold purpose in mind: to learn about epidemic models and their statistical analysis, and/or to learn and apply techniques in probability and statistics. The lecture notes require an early graduate level knowledge of probability and They introduce several techniques which might be new to students, but our statistics. intention is to present these keeping the technical level at a minlmum. Techniques that are explained and applied in the lecture notes are, for example: coupling, diffusion approximation, random graphs, likelihood theory for counting processes, martingales, the EM-algorithm and MCMC methods. The aim is to introduce and apply these techniques, thus hopefully motivating their further theoretical treatment. A few sections, mainly in Chapter 5, assume some knowledge of weak convergence; we hope that readers not familiar with this theory can understand the these parts at a heuristic level. The text is divided into two distinct but related parts: modelling and estimation.
Authors and Affiliations
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Group Financial Risk Control, SwedBank, Stockholm, Sweden
Håkan Andersson
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Department of Mathematics, Uppsala University, Uppsala, Sweden
Tom Britton