Fitting Time-Series Input Processes for Simulation
نویسندگان
چکیده
منابع مشابه
Fitting Time-Series Input Processes for Simulation
Providing accurate and automated input modeling support is one of the challenging problems in the application of computer simulation. The models incorporated in current input-modeling software packages often fall short because they assume independent and identically distributed processes, even though dependent time-series processes occur naturally in many real-life systems. This paper introduce...
متن کاملEvaluation of the ARTAFIT Method for Fitting Time-Series Input Processes for Simulation
T input processes occur naturally in the stochastic simulation of many service, communications, and manufacturing systems, and there are a variety of time-series input models available to match a given collection of properties, typically a marginal distribution and an autocorrelation structure specified via the use of one or more time lags. The focus of this paper is the situation in which the ...
متن کاملAutoregressive to anything: Time-series input processes for simulation
We develop a model for representing stationary time series with arbitrary marginal distributions and autocorrelation structures and describe how to generate data based upon our model for use in a simulation.
متن کاملProbabilistic Input Processes for Simulation
Techniques are presented for modeling and generating the univariate and multivariate probabilistic input processes that drive many simulation experiments. Among univariate input models, emphasis is given to the generalized beta distribution family, the Johnson translation system of distributions, and the Bézier distribution family. Among bivariate and higher-dimensional input models, emphasis i...
متن کاملFitting Time Series Models for Prediction Fitting Time Series Models for Prediction
This research was supported by the Army, Navy, Air Force and NASA under a contract. administered by the Office of Naval Research, with Yale University; by the National Science Foundation under Grant GU-2059 and the Air Force Office of Scientific Research under Contract AFOSR-68-l4l5 with the University of North Carolina at Chapel Hill. ** The major portion of the research for this paper was don...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Operations Research
سال: 2005
ISSN: 0030-364X,1526-5463
DOI: 10.1287/opre.1040.0190