Uniform random number generators: a review
Proceedings of the 29th conference on Winter simulation
Time Series Analysis, Forecasting and Control
Time Series Analysis, Forecasting and Control
ANSS '07 Proceedings of the 40th Annual Simulation Symposium
Common defects in initialization of pseudorandom number generators
ACM Transactions on Modeling and Computer Simulation (TOMACS)
The Black Swan: The Impact of the Highly Improbable
The Black Swan: The Impact of the Highly Improbable
Harnessing hibernate
A Grid-Inspired Mechanism for Coarse-Grained Experiment Execution
DS-RT '08 Proceedings of the 2008 12th IEEE/ACM International Symposium on Distributed Simulation and Real-Time Applications
A flexible and scalable experimentation layer
Proceedings of the 40th Conference on Winter Simulation
A plug-in-based architecture for random number generation in simulation systems
Proceedings of the 40th Conference on Winter Simulation
Parallel discrete-event simulation of population dynamics
Proceedings of the 40th Conference on Winter Simulation
Towards a generalized subpopulation support for stochastic population projections
Proceedings of the Winter Simulation Conference
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Predicting future populations and their structure is a central theme in demography. It is related to public health issues, political decision-making, or urban planning. Since these predictions are concerned with the evolution of a complex system, they exhibit a considerable uncertainty. Accounting for this inherent uncertainty is crucial for subsequent decision processes, as it reveals the range of possible outcomes and their likelihood. Consequently, probabilistic prediction approaches emerged over the past decades. This paper describes the probabilistic population projection model (PPPM), a recently developed method that allows detailed projections, but has a complex structure and requires much input data. We discuss the development of P3J, a tool that helps users in managing and executing projections and is built on top of the simulation system JAMES II. We outline how even specific tools like P3J profit from general-purpose simulation frameworks like JAMES II, and illustrate its usage by a simple example.