R Programming for Actuarial Science
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 intermediatelevel 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.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
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 intermediatelevel 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.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.