Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Asymptotically efficient estimation of linear functionals in inverse
  regression models   In this paper we will discuss a procedure to improve the usual estimator of a
linear functional of the unknown regression function in inverse nonparametric
regression models. In Klaassen, Lee, and Ruymgaart (2001) it has been proved
that this traditional estimator is not asymptotically efficient (in the sense
of the H\'{a}jek - Le Cam convolution theorem) except, possibly, when the error
distribution is normal. Since this estimator, however, is still root-n
consistent a procedure in Bickel, Klaassen, Ritov, and Wellner (1993) applies
to construct a modification which is asymptotically efficient. A self-contained
proof of the asymptotic efficiency is included.

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The categories of this paper are: cmp-lg
14
The categories of this paper are: math-ph
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The categories of this paper are: mtrl-th
1
The categories of this paper are: cs
5
The categories of this paper are: gr-qc
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The categories of this paper are: acc-phys
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The categories of this paper are: q-fin
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The categories of this paper are: supr-con
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The categories of this paper are: bayes-an
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The categories of this paper are: eess
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The categories of this paper are: nlin
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The categories of this paper are: chem-ph
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The categories of this paper are: quant-ph
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The categories of this paper are: nucl-ex
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The categories of this paper are: plasm-ph
6
The categories of this paper are: astro-ph