This is the only book actuaries need to understand generalized
linear models (GLMs) for insurance applications. GLMs are used in
the insurance industry to support critical decisions. Until now, no
text has introduced GLMs in this context or addressed the problems
specific to insurance data. Using insurance data sets, this
practical, rigorous book treats GLMs, covers all standard
exponential family distributions, extends the methodology to
correlated data structures, and discusses recent developments which
go beyond the GLM. The issues in the book are specific to insurance
data, such as model selection in the presence of large data sets
and the handling of varying exposure times. Exercises and
data-based practicals help readers to consolidate their skills,
with solutions and data sets given on the companion website.
Although the book is package-independent, SAS code and output
examples feature in an appendix and on the website. In addition, R
code and output for all the examples are provided on the website.
General
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