Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Generating Random Samples from Non-Identical Truncated Order Statistics   We provide an efficient algorithm to generate random samples from the bounded
kth order statistic in a sample of independent, but not necessarily identically
distributed, random variables. The bounds can be upper or lower bounds and need
only hold on the kth order statistic. Furthermore, we require access to the
inverse CDF for each statistic in the ordered sample. The algorithm is slightly
slower than rejection sampling when the density of the bounded statistic is
large, however, it is significantly faster when the bounded density becomes
sparse. We provide a practical example and a simulation that shows the
superiority of this method for sparse regions arising from tight boundary
conditions and/or over regions of low probability density.

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The categories of this paper are: hep-th
18
The categories of this paper are: econ
10
The categories of this paper are: q-bio
12
The categories of this paper are: nucl-th
3
The categories of this paper are: physics
19
The categories of this paper are: eess
25
The categories of this paper are: patt-sol
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The categories of this paper are: q-fin
29
The categories of this paper are: funct-an
15
The categories of this paper are: nucl-ex
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The categories of this paper are: cs
37
The categories of this paper are: supr-con
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The categories of this paper are: solv-int
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The categories of this paper are: alg-geom
34
The categories of this paper are: chem-ph
36
The categories of this paper are: cmp-lg