PDF plots of GIED.

<div><p>This article explores the estimation of Shannon entropy and Rényi entropy based on the generalized inverse exponential distribution under the condition of stepwise Type II truncated samples. Firstly, we analyze the maximum likelihood estimation and interval estimation of Shannon...

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Main Author: Qin Gong (118801) (author)
Other Authors: Bin Yin (120095) (author)
Published: 2024
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author Qin Gong (118801)
author2 Bin Yin (120095)
author2_role author
author_facet Qin Gong (118801)
Bin Yin (120095)
author_role author
dc.creator.none.fl_str_mv Qin Gong (118801)
Bin Yin (120095)
dc.date.none.fl_str_mv 2024-09-30T17:35:50Z
dc.identifier.none.fl_str_mv 10.1371/journal.pone.0311129.g001
dc.relation.none.fl_str_mv https://figshare.com/articles/figure/PDF_plots_of_GIED_/27137445
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Genetics
Neuroscience
Biotechnology
Cancer
Plant Biology
Environmental Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
research results show
r &# 233
practical applications using
lindley approximation algorithm
degroot loss function
construct confidence intervals
entropy loss function
maximum likelihood estimation
nyi entropy based
nyi entropy
shannon entropy
entropy functions
xlink ">
statistical inference
relatively high
progressive type
prior distribution
interval estimation
gied model
gamma distribution
estimation method
estimation accuracy
demonstrate effectiveness
bootstrap method
article explores
dc.title.none.fl_str_mv PDF plots of GIED.
dc.type.none.fl_str_mv Image
Figure
info:eu-repo/semantics/publishedVersion
image
description <div><p>This article explores the estimation of Shannon entropy and Rényi entropy based on the generalized inverse exponential distribution under the condition of stepwise Type II truncated samples. Firstly, we analyze the maximum likelihood estimation and interval estimation of Shannon entropy and Rényi entropy for the generalized inverse exponential distribution. In this process, we use the bootstrap method to construct confidence intervals for Shannon entropy and Rényi entropy. Next, we select the gamma distribution as the prior distribution and apply the Lindley approximation algorithm to calculate `estimates of Shannon entropy and Rényi entropy under different loss functions including Linex loss function, entropy loss function, and DeGroot loss function respectively. Afterwards, simulation is used to calculate estimates and corresponding mean square errors of Shannon entropy and Rényi entropy in GIED model. The research results show that under DeGroot loss function, estimation accuracy of Shannon entropy and Rényi entropy for generalized inverse exponential distribution is relatively high, overall Bayesian estimation performs better than maximum likelihood estimation. Finally, we demonstrate effectiveness of our estimation method in practical applications using a set of real data.</p></div>
eu_rights_str_mv openAccess
id Manara_640aefcfd076d1dfd768f8e6ab9d1c70
identifier_str_mv 10.1371/journal.pone.0311129.g001
network_acronym_str Manara
network_name_str ManaraRepo
oai_identifier_str oai:figshare.com:article/27137445
publishDate 2024
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
rights_invalid_str_mv CC BY 4.0
spelling PDF plots of GIED.Qin Gong (118801)Bin Yin (120095)GeneticsNeuroscienceBiotechnologyCancerPlant BiologyEnvironmental Sciences not elsewhere classifiedMathematical Sciences not elsewhere classifiedresearch results showr &# 233practical applications usinglindley approximation algorithmdegroot loss functionconstruct confidence intervalsentropy loss functionmaximum likelihood estimationnyi entropy basednyi entropyshannon entropyentropy functionsxlink ">statistical inferencerelatively highprogressive typeprior distributioninterval estimationgied modelgamma distributionestimation methodestimation accuracydemonstrate effectivenessbootstrap methodarticle explores<div><p>This article explores the estimation of Shannon entropy and Rényi entropy based on the generalized inverse exponential distribution under the condition of stepwise Type II truncated samples. Firstly, we analyze the maximum likelihood estimation and interval estimation of Shannon entropy and Rényi entropy for the generalized inverse exponential distribution. In this process, we use the bootstrap method to construct confidence intervals for Shannon entropy and Rényi entropy. Next, we select the gamma distribution as the prior distribution and apply the Lindley approximation algorithm to calculate `estimates of Shannon entropy and Rényi entropy under different loss functions including Linex loss function, entropy loss function, and DeGroot loss function respectively. Afterwards, simulation is used to calculate estimates and corresponding mean square errors of Shannon entropy and Rényi entropy in GIED model. The research results show that under DeGroot loss function, estimation accuracy of Shannon entropy and Rényi entropy for generalized inverse exponential distribution is relatively high, overall Bayesian estimation performs better than maximum likelihood estimation. Finally, we demonstrate effectiveness of our estimation method in practical applications using a set of real data.</p></div>2024-09-30T17:35:50ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pone.0311129.g001https://figshare.com/articles/figure/PDF_plots_of_GIED_/27137445CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/271374452024-09-30T17:35:50Z
spellingShingle PDF plots of GIED.
Qin Gong (118801)
Genetics
Neuroscience
Biotechnology
Cancer
Plant Biology
Environmental Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
research results show
r &# 233
practical applications using
lindley approximation algorithm
degroot loss function
construct confidence intervals
entropy loss function
maximum likelihood estimation
nyi entropy based
nyi entropy
shannon entropy
entropy functions
xlink ">
statistical inference
relatively high
progressive type
prior distribution
interval estimation
gied model
gamma distribution
estimation method
estimation accuracy
demonstrate effectiveness
bootstrap method
article explores
status_str publishedVersion
title PDF plots of GIED.
title_full PDF plots of GIED.
title_fullStr PDF plots of GIED.
title_full_unstemmed PDF plots of GIED.
title_short PDF plots of GIED.
title_sort PDF plots of GIED.
topic Genetics
Neuroscience
Biotechnology
Cancer
Plant Biology
Environmental Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
research results show
r &# 233
practical applications using
lindley approximation algorithm
degroot loss function
construct confidence intervals
entropy loss function
maximum likelihood estimation
nyi entropy based
nyi entropy
shannon entropy
entropy functions
xlink ">
statistical inference
relatively high
progressive type
prior distribution
interval estimation
gied model
gamma distribution
estimation method
estimation accuracy
demonstrate effectiveness
bootstrap method
article explores