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1. Identity statement
Reference TypeJournal Article
Sitemtc-m21c.sid.inpe.br
Holder Codeisadg {BR SPINPE} ibi 8JMKD3MGPCW/3DT298S
Identifier8JMKD3MGP3W34R/42EDGML
Repositorysid.inpe.br/mtc-m21c/2020/05.05.12.12   (restricted access)
Last Update2020:05.05.12.12.29 (UTC) simone
Metadata Repositorysid.inpe.br/mtc-m21c/2020/05.05.12.12.29
Metadata Last Update2022:01.04.01.35.08 (UTC) administrator
DOI10.1016/j.physa.2020.124301
ISSN0378-4371
Citation KeyRamosCasaMaca:2020:InHiAp
TitleInvestigation on the high-order approximation of the entropy bias
Year2020
MonthJuly
Access Date2024, May 19
Type of Workjournal article
Secondary TypePRE PI
Number of Files1
Size521 KiB
2. Context
Author1 Ramos, Antônio Mário de torres
2 Casagrande, Helder Luciani
3 Macau, Elbert Einstein Nehrer
Resume Identifier1
2
3 8JMKD3MGP5W/3C9JGUT
Group1
2 LABAC-COCTE-INPE-MCTIC-GOV-BR
3 LABAC-COCTE-INPE-MCTIC-GOV-BR
Affiliation1 Itaú Asset Management
2 Instituto Nacional de Pesquisas Espaciais (INPE)
3 Instituto Nacional de Pesquisas Espaciais (INPE)
Author e-Mail Address1 amtramos@protonmail.com
2 helder.grande@inpe.br
3 elbert.macau@inpe.br
JournalPhysica A: Statistical Mechanics and its Applications
Volume549
Pagese124301
Secondary MarkA1_ADMINISTRAÇÃO,_CIÊNCIAS_CONTÁBEIS_E_TURISMO A2_INTERDISCIPLINAR A2_ENGENHARIAS_III B1_PSICOLOGIA B1_MEDICINA_VETERINÁRIA B1_GEOCIÊNCIAS B1_ENGENHARIAS_IV B1_ENGENHARIAS_II B1_ENGENHARIAS_I B1_CIÊNCIAS_AMBIENTAIS B1_CIÊNCIAS_AGRÁRIAS_I B1_BIODIVERSIDADE B2_NUTRIÇÃO B2_MEDICINA_II B2_MATERIAIS B2_MATEMÁTICA_/_PROBABILIDADE_E_ESTATÍSTICA B2_FARMÁCIA B2_ECONOMIA B2_DIREITO B2_CIÊNCIAS_BIOLÓGICAS_II B2_CIÊNCIA_DA_COMPUTAÇÃO B2_BIOTECNOLOGIA B2_ASTRONOMIA_/_FÍSICA B3_QUÍMICA B3_EDUCAÇÃO_FÍSICA B3_CIÊNCIAS_BIOLÓGICAS_I
History (UTC)2020-05-05 12:12:55 :: simone -> administrator :: 2020
2020-05-10 00:54:02 :: administrator -> simone :: 2020
2020-06-19 13:43:54 :: simone -> administrator :: 2020
2022-01-04 01:35:08 :: administrator -> simone :: 2020
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
Version Typepublisher
KeywordsEntropy bias
Mutual information
Multiple comparison analysis
Complex network
AbstractThe estimation of entropy from experimental data has a considerable bias when the discretization of the variable domain is comparable to the sample size. In this case, the source of the bias is the difference between the a priori distribution and the observed distribution from sampled data. In this paper, we estimate the entropy bias considering an infinite sum of central moments of the binomial distribution using two probability mass functions. We analyze the bias in the light of the ratio between the number of the partition of the domain and the sample size. The main motivation of this study is improving statistical hypothesis testing in which probabilities are conceived beforehand. We examine the adequacy of high-order approximation according to the ratio between the sample size and the number of domain partitions. Finally, we expand the analysis to the entropy-derived mutual information and present an application for network reconstruction.
AreaCOMP
Arrangementurlib.net > BDMCI > Fonds > Produção anterior à 2021 > LABAC > Investigation on the...
doc Directory Contentaccess
source Directory Contentthere are no files
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4. Conditions of access and use
Languageen
Target Fileramos_investigation.pdf
User Groupsimone
Reader Groupadministrator
simone
Visibilityshown
Archiving Policydenypublisher denyfinaldraft24
Read Permissiondeny from all and allow from 150.163
Update Permissionnot transferred
5. Allied materials
Next Higher Units8JMKD3MGPCW/3ESGTTP
Citing Item Listsid.inpe.br/bibdigital/2013/09.22.23.14 3
sid.inpe.br/mtc-m21/2012/07.13.14.45.07 2
DisseminationWEBSCI; PORTALCAPES; MGA; COMPENDEX; SCOPUS.
Host Collectionurlib.net/www/2017/11.22.19.04
6. Notes
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