Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Note on information bias and efficiency of composite likelihood   Does the asymptotic variance of the maximum composite likelihood estimator of
a parameter of interest always decrease when the nuisance parameters are known?
Will a composite likelihood necessarily become more efficient by incorporating
addi- tional independent component likelihoods, or by using component
likelihoods with higher dimension? In this note we show through illustrative
examples that the an- swer to both questions is no, and indeed the opposite
direction might be observed. The role of information bias is highlighted to
understand the occurrence of these paradoxical phenomenon.

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The categories of this paper are: nlin
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The categories of this paper are: quant-ph
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The categories of this paper are: q-alg
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The categories of this paper are: astro-ph
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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: ao-sci
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The categories of this paper are: math-ph
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The categories of this paper are: patt-sol
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The categories of this paper are: mtrl-th
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The categories of this paper are: q-fin
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The categories of this paper are: bayes-an
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The categories of this paper are: alg-geom
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The categories of this paper are: cs
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The categories of this paper are: supr-con
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The categories of this paper are: solv-int