Comparar métodos

	Simulación de Sistemas de Eventos Discretos	Simulación Bootstrap
Campo	Simulación	Simulación
Familia	Process / pipeline	Process / pipeline
Año de origen	1960s (formalised in literature through the 1980s–2000s)	1979
Autor original	Kelton, Law & Sadowski (formalised methodology); SIMSCRIPT (Markowitz et al., 1963) and GPSS (Gordon, 1961) were pioneering tools	Bradley Efron
Tipo	Stochastic process simulation	Simulation-based nonparametric inference
Fuente seminal	Kelton, W.D., Sadowski, R.P. & Zupick, N.B. (2014). Simulation with Arena (6th ed.). McGraw-Hill. ISBN: 978-0073401317	Efron, B. & Tibshirani, R.J. (1993). An Introduction to the Bootstrap. Chapman & Hall/CRC.
Alias	DES, discrete event simulation, Kesikli Sistem Simülasyonu (Arena / AnyLogic tarzı)	bootstrap resampling, empirical resampling, nonparametric bootstrap, Önyükleme Simülasyonu (Bootstrap Resampling)
Relacionados	4	5
Resumen	Discrete-event system simulation (DES) is a computational modelling technique in which the state of a system changes only at discrete points in time — called events — such as a customer arriving, a machine starting, or a job completing. Formalised through foundational texts by Kelton, Sadowski, and Zupick (2014) and Law (2015), DES represents processes as networks of resources, queues, and activities, allowing analysts to test capacity and policy changes on a virtual model before touching the real system.	Bootstrap simulation, introduced by Bradley Efron in 1979, is a simulation-based inference method that derives the sampling distribution of virtually any statistic by repeatedly resampling with replacement from the observed data. Because it requires no parametric distributional assumptions, it provides a robust, general-purpose alternative to analytical confidence intervals and parametric hypothesis tests across continuous, ordinal, binary, and count data.