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Berry-Esseen bounds of weighted kernel estimator for a nonparametric regression model based on linear process errors under a LNQD sequence

Overview of attention for article published in Journal of Inequalities & Applications, January 2018
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About this Attention Score

  • Among the highest-scoring outputs from this source (#40 of 126)

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Citations

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Title
Berry-Esseen bounds of weighted kernel estimator for a nonparametric regression model based on linear process errors under a LNQD sequence
Published in
Journal of Inequalities & Applications, January 2018
DOI 10.1186/s13660-017-1604-8
Pubmed ID
Authors

Liwang Ding, Ping Chen, Yongming Li

Abstract

In this paper, the authors investigate the Berry-Esseen bounds of weighted kernel estimator for a nonparametric regression model based on linear process errors under a LNQD random variable sequence. The rate of the normal approximation is shown as [Formula: see text] under some appropriate conditions. The results obtained in the article generalize or improve the corresponding ones for mixing dependent sequences in some sense.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 100%
Readers by discipline Count As %
Business, Management and Accounting 1 100%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 March 2018.
All research outputs
#9,709,724
of 12,651,470 outputs
Outputs from Journal of Inequalities & Applications
#40
of 126 outputs
Outputs of similar age
#189,455
of 274,082 outputs
Outputs of similar age from Journal of Inequalities & Applications
#1
of 1 outputs
Altmetric has tracked 12,651,470 research outputs across all sources so far. This one is in the 20th percentile – i.e., 20% of other outputs scored the same or lower than it.
So far Altmetric has tracked 126 research outputs from this source. They receive a mean Attention Score of 1.0. This one has gotten more attention than average, scoring higher than 66% of its peers.
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We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them