Statistical and Probabilistic Methods in Actuarial Science covers
many of the diverse methods in applied probability and statistics
for students aspiring to careers in insurance, actuarial science,
and finance. The book builds on students' existing knowledge of
probability and statistics by establishing a solid and thorough
understanding of these methods. It also emphasizes the wide variety
of practical situations in insurance and actuarial science where
these techniques may be used.
Although some chapters are linked, several can be studied
independently from the others. The first chapter introduces claims
reserving via the deterministic chain ladder technique. The next
few chapters survey loss distributions, risk models in a fixed
period of time, and surplus processes, followed by an examination
of credibility theory in which collateral and sample information
are brought together to provide reasonable methods of estimation.
In the subsequent chapter, experience rating via no claim discount
schemes for motor insurance provides an interesting application of
Markov chain methods. The final chapters discuss generalized linear
models and decision and game theory.
Developed by an author with many years of teaching experience,
this text presents an accessible, sound foundation in both the
theory and applications of actuarial science. It encourages
students to use the statistical software package R to check
examples and solve problems.
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