Simulation / Sheldon M. Ross
Tipo de material: TextoDetalles de publicación: Amsterdam : Academic Press, 2013. Edición: 5th ed.Descripción: xii, 310 p.: ill. ; 24 cmISBN: 9780124158252 (hardback)Tema(s): Métodos de simulación | Variables aleatorias | Simulación por ordenador | ProbabilidadesTipo de ítem | Biblioteca de origen | Signatura | URL | Estado | Fecha de vencimiento | Código de barras | Reserva de ítems |
---|---|---|---|---|---|---|---|
Monografías | 02. BIBLIOTECA CAMPUS PUERTO REAL | 519.876.5/ROS/sim (Navegar estantería(Abre debajo)) | Texto completo | Disponible Ubicación en estantería | Bibliomaps® | 3742091619 |
"In formulating a stochastic model to describe a real phenomenon, it used to be that one compromised between choosing a model that is a realistic replica of the actual situation and choosing one whose mathematical analysis is tractable. That is, there did not seem to be any payoff in choosing a model that faithfully conformed to the phenomenon under study if it were not possible to mathematically analyze that model. Similar considerations have led to the concentration on asymptotic or steady-state results as opposed to the more useful ones on transient time. However, the relatively recent advent of fast and inexpensive computational power has opened up another approach--namely, to try to model the phenomenon as faithfully as possible and then to rely on a simulation study to analyze it"-- Provided by publisher.
Includes bibliographical references and index.
Machine generated contents note: Preface; Introduction; Elements of Probability; Random Numbers; Generating Discrete Random Variables; Generating Continuous Random Variables; The Discrete Event Simulation Approach; Statistical Analysis of Simulated Data; Variance Reduction Techniques; Statistical Validation Techniques; Markov Chain Monte Carlo Methods; Some Additional Topics; Exercises; References; Index.
No hay comentarios en este titulo.