Langmuir adsortion isotherm with regular and irregular autoregressive error structures
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Acta scientiarum. Technology (Online) |
Texto Completo: | http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/37792 |
Resumo: | The Langmuir isotherm is a nonlinear regression model, being one of the most applied in adsorption studies. In this type of study, the data are collected over time, which can provide correlated errors; in addition, the collection is not always done in an equidistant way, which may influence the estimation of model parameters. One way of modelling the dependent errors in a regression model is to use an autoregressive process that assumes that the observations are performed at equidistant intervals. However, the definition of the independent variable is often performed at irregular intervals, causing a reduction of information obtained from the dataset. One possible improvement in the adjustment quality of these models is the use of the irregular autoregressive process. The objective of this work was to compare the estimates of isotherm parameters with different irregular and regular autoregressive error structures, considering the positive autocorrelation in different sample sizes, error autocorrelation values and positioning of non-equidistant observations. It was found that there is a need to respect the assumptions of the model. The irregular autoregressive model is more appropriate because it is mostly more precise and accurate, especially when non-equidistance occurs in the initial third. |
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Langmuir adsortion isotherm with regular and irregular autoregressive error structuresnonlinear modelMonte Carlo simulationestimatorsprecisionaccuracyautoregressive error.Estatística AplicadaThe Langmuir isotherm is a nonlinear regression model, being one of the most applied in adsorption studies. In this type of study, the data are collected over time, which can provide correlated errors; in addition, the collection is not always done in an equidistant way, which may influence the estimation of model parameters. One way of modelling the dependent errors in a regression model is to use an autoregressive process that assumes that the observations are performed at equidistant intervals. However, the definition of the independent variable is often performed at irregular intervals, causing a reduction of information obtained from the dataset. One possible improvement in the adjustment quality of these models is the use of the irregular autoregressive process. The objective of this work was to compare the estimates of isotherm parameters with different irregular and regular autoregressive error structures, considering the positive autocorrelation in different sample sizes, error autocorrelation values and positioning of non-equidistant observations. It was found that there is a need to respect the assumptions of the model. The irregular autoregressive model is more appropriate because it is mostly more precise and accurate, especially when non-equidistance occurs in the initial third. Universidade Estadual De Maringá2018-09-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionAdsorção; Regressão Não-Linear; Erros correlacionados; Autorregressivoapplication/pdfhttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/3779210.4025/actascitechnol.v40i1.37792Acta Scientiarum. Technology; Vol 40 (2018): Publicação Contínua; e37792Acta Scientiarum. Technology; v. 40 (2018): Publicação Contínua; e377921806-25631807-8664reponame:Acta scientiarum. Technology (Online)instname:Universidade Estadual de Maringá (UEM)instacron:UEMenghttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/37792/pdfCopyright (c) 2018 Acta Scientiarum. Technologyhttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessCintra, Cristiane Costa da FonsecaNogueira, Denismar AlvesBeijo, Luiz Alberto2019-07-17T11:53:49Zoai:periodicos.uem.br/ojs:article/37792Revistahttps://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/indexPUBhttps://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/oai||actatech@uem.br1807-86641806-2563opendoar:2019-07-17T11:53:49Acta scientiarum. Technology (Online) - Universidade Estadual de Maringá (UEM)false |
dc.title.none.fl_str_mv |
Langmuir adsortion isotherm with regular and irregular autoregressive error structures |
title |
Langmuir adsortion isotherm with regular and irregular autoregressive error structures |
spellingShingle |
Langmuir adsortion isotherm with regular and irregular autoregressive error structures Cintra, Cristiane Costa da Fonseca nonlinear model Monte Carlo simulation estimators precision accuracy autoregressive error. Estatística Aplicada |
title_short |
Langmuir adsortion isotherm with regular and irregular autoregressive error structures |
title_full |
Langmuir adsortion isotherm with regular and irregular autoregressive error structures |
title_fullStr |
Langmuir adsortion isotherm with regular and irregular autoregressive error structures |
title_full_unstemmed |
Langmuir adsortion isotherm with regular and irregular autoregressive error structures |
title_sort |
Langmuir adsortion isotherm with regular and irregular autoregressive error structures |
author |
Cintra, Cristiane Costa da Fonseca |
author_facet |
Cintra, Cristiane Costa da Fonseca Nogueira, Denismar Alves Beijo, Luiz Alberto |
author_role |
author |
author2 |
Nogueira, Denismar Alves Beijo, Luiz Alberto |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Cintra, Cristiane Costa da Fonseca Nogueira, Denismar Alves Beijo, Luiz Alberto |
dc.subject.por.fl_str_mv |
nonlinear model Monte Carlo simulation estimators precision accuracy autoregressive error. Estatística Aplicada |
topic |
nonlinear model Monte Carlo simulation estimators precision accuracy autoregressive error. Estatística Aplicada |
description |
The Langmuir isotherm is a nonlinear regression model, being one of the most applied in adsorption studies. In this type of study, the data are collected over time, which can provide correlated errors; in addition, the collection is not always done in an equidistant way, which may influence the estimation of model parameters. One way of modelling the dependent errors in a regression model is to use an autoregressive process that assumes that the observations are performed at equidistant intervals. However, the definition of the independent variable is often performed at irregular intervals, causing a reduction of information obtained from the dataset. One possible improvement in the adjustment quality of these models is the use of the irregular autoregressive process. The objective of this work was to compare the estimates of isotherm parameters with different irregular and regular autoregressive error structures, considering the positive autocorrelation in different sample sizes, error autocorrelation values and positioning of non-equidistant observations. It was found that there is a need to respect the assumptions of the model. The irregular autoregressive model is more appropriate because it is mostly more precise and accurate, especially when non-equidistance occurs in the initial third. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-09-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Adsorção; Regressão Não-Linear; Erros correlacionados; Autorregressivo |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/37792 10.4025/actascitechnol.v40i1.37792 |
url |
http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/37792 |
identifier_str_mv |
10.4025/actascitechnol.v40i1.37792 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/37792/pdf |
dc.rights.driver.fl_str_mv |
Copyright (c) 2018 Acta Scientiarum. Technology https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2018 Acta Scientiarum. Technology https://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Estadual De Maringá |
publisher.none.fl_str_mv |
Universidade Estadual De Maringá |
dc.source.none.fl_str_mv |
Acta Scientiarum. Technology; Vol 40 (2018): Publicação Contínua; e37792 Acta Scientiarum. Technology; v. 40 (2018): Publicação Contínua; e37792 1806-2563 1807-8664 reponame:Acta scientiarum. Technology (Online) instname:Universidade Estadual de Maringá (UEM) instacron:UEM |
instname_str |
Universidade Estadual de Maringá (UEM) |
instacron_str |
UEM |
institution |
UEM |
reponame_str |
Acta scientiarum. Technology (Online) |
collection |
Acta scientiarum. Technology (Online) |
repository.name.fl_str_mv |
Acta scientiarum. Technology (Online) - Universidade Estadual de Maringá (UEM) |
repository.mail.fl_str_mv |
||actatech@uem.br |
_version_ |
1799315336835629056 |