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Cloud-based simulation studies in R - A tutorial on using doRedis with Amazon spot fleets.

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  • 1University of Applied Sciences Bielefeld, Bielefeld, Germany.

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Summary
This summary is machine-generated.

This study introduces parallel computing techniques in R for cloud infrastructure, enabling efficient simulation studies. It demonstrates using doRedis on Amazon Web Services for statistical method assessment.

Keywords:
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Area of Science:

  • Computational Statistics
  • Cloud Computing
  • Statistical Software

Background:

  • Simulation studies are crucial for evaluating new statistical methods.
  • These simulations often involve computationally intensive, parallelizable tasks.
  • Leveraging cloud infrastructure can enhance the efficiency of these simulations.

Purpose of the Study:

  • To present parallelization techniques in R for cloud environments.
  • To provide a practical tutorial on using the doRedis package with Redis on Amazon Web Services (AWS).
  • To demonstrate the application of these techniques for assessing statistical method performance.

Main Methods:

  • Overview of R parallelization strategies.
  • Step-by-step tutorial for setting up and using doRedis on AWS EC2 instances with Redis.
  • Utilization of AWS Spot Fleets for cost-effective, scalable computation.
  • Example application: assessing heteroscedasticity's impact on the t-test.

Main Results:

  • Successful implementation of parallel R simulations on AWS.
  • Demonstrated efficiency gains through cloud-based parallel processing.
  • Practical guidance for researchers on setting up distributed computing environments.

Conclusions:

  • Parallel R computing on AWS via doRedis is feasible and efficient for simulation studies.
  • The described methods facilitate the assessment of statistical methods under various conditions.
  • Researchers can benefit from cloud infrastructure for large-scale computational tasks.