- Automatically and accurately determines the best probability distribution for your data set in seconds
- Distribution-selection algorithm is based on 33 years of research and on experimentation with 35,000 data sets.
- Provides an absolute evaluation of the “best” distribution – this is a critical capability!
- Standard mode contains features sufficient for 95 percent of all analyses and focuses the user on those features that are really important.
- Advanced mode contains numerous additional features for the sophisticated user.
- Allows you to switch from one mode to another during an analysis
- Sample sizes up to 100,000
- Gives you access to 40 probability distributions (click here for a list)
- Chosen distribution is put into the proper format for direct input to 14 simulation-software products (click here for a list).
- Technically correct chi-square, Kolmogorov-Smirnov, and Anderson-Darling
goodness-of-fit tests - Provides more than 30 high-quality plots of your data (click here for examples)
- Allows you to plot any number of distributions on the same graph, making comparisons easy
- Histograms can be interactively updated.
- Generation of random values from any distribution
- Distribution viewer allows you to interactively see characteristics of a distribution without entering data (click here for an illustration).
- Batch-mode capability allows the user to analyze a large number of data sets with only a few keystrokes (see Versions for availability).
- Local area network (LAN) versions
- Module for determining if a data set is a random sample, a requirement for many statistical techniques
- Module for determining whether “similar” data sets are homogeneous and, thus, can be merged
- Helps you pick a distribution in the absence of data, including models for task times and for random equipment breakdowns
- Comprehensive context-sensitive help for all menus and results screens
- Tutorials on topics such as available probability distributions and goodness-of-fit tests
- User’s Guide with 8 complete examples
Discrete-Event Simulation Versions | Simulation Products Supported |
---|---|
Professional (has batch mode) | AnyLogic, Arena, Crystal Ball, ExtendSim, FlexSim, MedModel, ProcessModel, ProModel, @Risk, Simio, SIMUL8, WITNESS |
University | Same as Professional, but without batch mode |
ExtendSim | ExtendSim |
SIMUL8 | SIMUL8 |
Each product is a registered trademark of its respective company.
Korea
ATWORTH
11-24, Hangang-daero
102-gil, Yongsan-gu
Seoul, Korea
82-318-2320
Contact: Y.S. Park (yspark@atworth.co.kr)
www.atworth.co.kr
Dr. Averill M. Law, President of Averill M. Law & Associates, is one of the world’s foremost experts on simulation modeling and distribution fitting. He is the author of the textbook Simulation Modeling and Analysis (Fifth Edition), which has more than 175,000 copies in print and 22,100 citations. This book contains the most comprehensive and practical discussion of fitting probability distributions to data that is available.
He has been a simulation consultant to numerous organizations including Accenture, Boeing, Booz Allen & Hamilton, ConocoPhillips, Defense Modeling and Simulation Office, Hewlett-Packard, ITT, Kimberly-Clark, M&M/Mars, Monsanto, Oak Ridge National Lab, SAIC, Sandia National Labs, 3M, Tropicana, U.S. Air Force, U.S. Army, U.S. Marine Corps, U.S. Navy, and Xerox.
Dr. Law has presented more than 580 simulation and statistics short courses in 20 countries. He has been the keynote speaker at simulation conferences around the world. Dr. Law is the author of numerous technical papers on simulation, statistics, operations research, manufacturing, and communications. He wrote a regular column on simulation for Industrial Engineering magazine. He was awarded the 2009 INFORMS Simulation Society Lifetime Professional Achievement Award. (https://www.youtube.com/watch?v=ipvWgQp97Qo)
Dr. Law has been a tenured faculty member at the University of Wisconsin, Madison and the University of Arizona. He has a Ph.D. in industrial engineering and operations research from the University of California, Berkeley.