• Corpus ID: 244270316

A Note on Simulation-Based Inference by Matching Random Features

@inproceedings{Shalizi2021ANO,
  title={A Note on Simulation-Based Inference by Matching Random Features},
  author={Cosma Rohilla Shalizi},
  year={2021}
}
  • C. Shalizi
  • Published 17 November 2021
  • Computer Science
We can, and should, do statistical inference on simulation models by adjusting the parameters in the simulation so that the values of randomly chosen functions of the simulation output match the values of those some functions calculated on the data. Results from the “state-space reconstruction” or “geometry from a time series” literature in nonlinear dynamics indicate that just 2d + 1 such functions will typically suffice to identify a model with a d-dimensional parameter space. Results from… 
1 Citations
Matching random features
TLDR
Some of the key results are sketched, numerical evidence about the new method’s properties are presented, and an agenda for research is laid out.

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