Evidence map›Paper›PMID 38248187›Full record

ArticleEntropy (Basel, Switzerland)2024

Linear Bayesian Estimation of Misrecorded Poisson Distribution.

Huiqing Gao, Zhanshou Chen, Fuxiao Li

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Huiqing GaoSchool of Mathematics and Statistic, Qinghai Normal University, Xining 810008, China.
Zhanshou ChenSchool of Mathematics and Statistic, Qinghai Normal University, Xining 810008, China.ORCID 0000-0003-3326-8663
Fuxiao LiFaculty of Science, Xi'an University of Technology, Xi'an 710048, China.

Funding

Natural Science Foundation of China No.12161072Natural Science Foundation of Qinghai Province 2019-ZJ-920
6 · The paper itself

Abstract

Parameter estimation is an important component of statistical inference, and how to improve the accuracy of parameter estimation is a key issue in research. This paper proposes a linear Bayesian estimation for estimating parameters in a misrecorded Poisson distribution. The linear Bayesian estimation method not only adopts prior information but also avoids the cumbersome calculation of posterior expectations. On the premise of ensuring the accuracy and stability of computational results, we derived the explicit solution of the linear Bayesian estimation. Its superiority was verified through numerical simulations and illustrative examples.

Indexed as

bootstraplinear Bayesian estimationmisrecorded Poisson distribution

Identifiers

PMID38248187
PMCPMC10813946

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.