Professional resource providing an introduction to R coding for actuarial and financial mathematics applications, with real-life examples

R Programming for Actuarial Science provides a grounding in R programming applied to the mathematical and statistical methods that are of relevance for actuarial work.

In R Programming for Actuarial Science, readers will find:

• Basic theory for each chapter to complement other actuarial textbooks which provide foundational theory in depth.
• Topics covered include compound interest, statistical inference, asset-liability matching, time series, loss distributions, contingencies, mortality models, and option pricing plus many more typically covered in university courses.
• More than 400 coding examples and exercises, most with solutions, to enable students to gain a better understanding of underlying mathematical and statistical principles.
• An overall basic to intermediate level of coverage in respect of numerous actuarial applications, and real-life examples included with every topic.

Providing a highly useful combination of practical discussion and basic theory, R Programming for Actuarial Science is an essential reference for BSc/MSc students in actuarial science, trainee actuaries studying privately, and qualified actuaries with little programming experience, along with undergraduate students studying finance, business, and economics.