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Computational actuarial science with R

Autores adicionales: Charpentier, Arthur -- editor

Series: The R series Statics for finance Publicado por : CRC Press Taylor & Francis Group (Boca Ratón (Florida, Estados Unidos)) Detalles físicos: xxxi, 618 páginas ISBN:9781466592599 .

Tema(s): Seguros de vida -- Matemáticas | Matemáticas en seguros de vida | R (Lenguaje de programación para computadores)

Año : 2015

Existencias ( 2 )
Notas de título ( 1 )

Tipo de ítem	Ubicación actual	Colección	Signatura	Copia número	Estado	Fecha de vencimiento	Código de barras	Reserva de ítems
Libro	Claustro 2do piso	Libro	368.01285 C738ca (Navegar estantería)	Ej.1	Disponible		100154237
Libro	Claustro 2do piso	Libro	368.01285 C738ca (Navegar estantería)	Ej.2	Disponible		100154238

Total de reservas: 0

"This book aims to provide a broad introduction to computational aspects of actuarial science, in the R environment. We assume that the reader is either learning, or is familiar with actuarial science. It can be seen as a companion to standard textbooks on actuarial science. This book is intended for various audiences: students, researchers, and actuaries. As explained in cite Kendrick et al. (2006) (discussing the importance of computational economics) \our thesis is that computational economics o ers a way to improve this situation and to bring new life into the teaching of economics in colleges and universities [...] computational economics provides an opportunity for some students to move away from too much use of the lecture-exam paradigm and more use of a laboratorypaper paradigm in teaching under graduate economics. This opens the door for more creative activity on the part of the students by giving them models developed by previous generations and challenging them to modify those models." Based on the assumption that the same holds for computational actuarial science, we decided to publish this book. As claimed by computational scientists, computational actuarial science might simply refer to modern actuarial science methods. Computational methods started probably in the 1950s with Dwyer (1951) and von Neumann (1951). The rst one emphasized the importance of linear computations, and the second one the importance of massive computations, using random number generations (and Monte Carlo methods), while (at that time) access to digital computers was not widespread"--