Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A set of efficient methods to generate high-dimensional binary data with
  specified correlation structures   High dimensional correlated binary data arise in many areas, such as observed
genetic variations in biomedical research. Data simulation can help researchers
evaluate efficiency and explore properties of different computational and
statistical methods. Also, some statistical methods, such as Monte-Carlo
methods, rely on data simulation. Lunn and Davies (1998) proposed linear time
complexity methods to generate correlated binary variables with three common
correlation structures. However, it is infeasible to specify unequal
probabilities in their methods. In this manuscript, we introduce several
computationally efficient algorithms that generate high-dimensional binary data
with specified correlation structures and unequal probabilities. Our algorithms
have linear time complexity with respect to the dimension for three commonly
studied correlation structures, namely exchangeable, decaying-product and
K-dependent correlation structures. In addition, we extend our algorithms to
generate binary data of general non-negative correlation matrices with
quadratic time complexity. We provide an R package, CorBin, to implement our
simulation methods. Compared to the existing packages for binary data
generation, the time cost to generate a 100-dimensional binary vector with the
common correlation structures and general correlation matrices can be reduced
up to $10^5$ folds and $10^3$ folds, respectively, and the efficiency can be
further improved with the increase of dimensions. The R package CorBin is
available on CRAN at https://cran.r-project.org/.

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The categories of this paper are: physics
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The categories of this paper are: math-ph
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The categories of this paper are: astro-ph
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The categories of this paper are: acc-phys
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The categories of this paper are: dg-ga
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The categories of this paper are: chao-dyn
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The categories of this paper are: math
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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: hep-lat
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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: ao-sci
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The categories of this paper are: cond-mat
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The categories of this paper are: cmp-lg
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The categories of this paper are: nucl-ex