Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Online Quantification of Input Model Uncertainty by Two-Layer Importance
  Sampling   Stochastic simulation has been widely used to analyze the performance of
complex stochastic systems and facilitate decision making in those systems.
Stochastic simulation is driven by the input model, which is a collection of
probability distributions that model the stochasticity in the system. The input
model is usually estimated using a finite amount of data, which introduces the
so-called input model uncertainty to the simulation output. How to quantify
input uncertainty has been studied extensively, and many methods have been
proposed for the batch data setting, i.e., when all the data are available at
once. However, methods for "streaming data" arriving sequentially in time are
still in demand, despite that streaming data have become increasingly prevalent
in modern applications. To fill this gap, we propose a two-layer importance
sampling framework that incorporates streaming data for online input
uncertainty quantification. Under this framework, we develop two algorithms
that suit different application scenarios: the first scenario is when data come
at a fast speed and there is no time for any new simulation in between updates;
the second is when data come at a moderate speed and a few but limited
simulations are allowed at each time stage. We prove the consistency and
asymptotic convergence rate results, which theoretically show the efficiency of
our proposed approach. We further demonstrate the proposed algorithms on a
numerical example of the news vendor problem.

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The categories of this paper are: nucl-th
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The categories of this paper are: q-bio
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The categories of this paper are: chao-dyn
26
The categories of this paper are: bayes-an
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The categories of this paper are: plasm-ph
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The categories of this paper are: math-ph
36
The categories of this paper are: cmp-lg
3
The categories of this paper are: physics
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The categories of this paper are: econ
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The categories of this paper are: eess
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The categories of this paper are: atom-ph
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The categories of this paper are: chem-ph
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The categories of this paper are: comp-gas
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The categories of this paper are: funct-an
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The categories of this paper are: quant-ph
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The categories of this paper are: supr-con