Accelerated regression-based summary statistics for discrete stochastic systems via approximate simulators
Abstract
Background Approximate Bayesian Computation (ABC) has become a key tool for calibrating the parameters of discrete stochastic biochemical models. For higher dimensional models and data, its performance is strongly dependent on having a representative set of summary statistics. While regression-based methods have been demonstrated to allow for the automatic construction of effective summary statistics, their reliance on first simulating a large...
Paper Details
Title
Accelerated regression-based summary statistics for discrete stochastic systems via approximate simulators
Published Date
Jun 23, 2021
Journal
Volume
22
Issue
1
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