Assessment of left-censored data treatment methods using stochastic simulation
ABSTRACT The paper evaluates the influence of size series, percentage of censored data, and coefficients of variation used to generate synthetic series on the estimation of means, standard deviations, coefficients of variation, and medians in series with censored data. Seven techniques were applied...
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Published in: | Revista brasileira de recursos hídricos Vol. 28 |
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Abstract | ABSTRACT The paper evaluates the influence of size series, percentage of censored data, and coefficients of variation used to generate synthetic series on the estimation of means, standard deviations, coefficients of variation, and medians in series with censored data. Seven techniques were applied to treat censored data in synthetic series with 180 scenarios (four size series, nine censoring percentages and five coefficients of variation): values proportional to the DL: zero, DL/2, DL/20.5 and DL - and parametric (MLE), robust (ROS) and Kaplan-Meier methods. Predictions were analyzed with four performance metrics (MPE, MAPE, KGE, and RMSE). It is found that the percentage of censored data and the coefficient of variation significantly alter forecast quality. It is also found that substitution by DL/2, by DL/20.5 and ROS are the most appropriate techniques for estimating the variables described, emphasizing ROS when estimating parametric variables and substitution by DL/20.5 for medians.
RESUMO O artigo avalia a influência do tamanho das séries, do percentual de dados censurados e dos coeficientes de variação utilizados para gerar séries sintéticas na estimativa de médias, desvios-padrão, coeficientes de variação e medianas em séries com dados censurados. Foram aplicadas sete técnicas de tratamento de dados censurados em séries sintéticas em 180 cenários (quatro tamanhos de séries, nove percentuais de censura e cinco coeficientes de variação): valores proporcionais ao DL: zero, DL/2, DL/20.5 e DL - e métodos paramétrico (MLE), robustos (ROS) e Kaplan-Meier. As previsões foram analisadas com quatro métricas de desempenho (MPE, MAPE, KGE e RMSE). Verificou-se que o percentual de dados censurados e o coeficiente de variação alteram significativamente a qualidade das previsões. Verificou-se também que a substituição por DL/2, por DL/20.5 e ROS são as técnicas mais adequadas para estimar as variáveis descritas, destacando-se a ROS para estimar variáveis paramétricas e a substituição por DL/20.5 para medianas. |
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AbstractList | ABSTRACT The paper evaluates the influence of size series, percentage of censored data, and coefficients of variation used to generate synthetic series on the estimation of means, standard deviations, coefficients of variation, and medians in series with censored data. Seven techniques were applied to treat censored data in synthetic series with 180 scenarios (four size series, nine censoring percentages and five coefficients of variation): values proportional to the DL: zero, DL/2, DL/20.5 and DL - and parametric (MLE), robust (ROS) and Kaplan-Meier methods. Predictions were analyzed with four performance metrics (MPE, MAPE, KGE, and RMSE). It is found that the percentage of censored data and the coefficient of variation significantly alter forecast quality. It is also found that substitution by DL/2, by DL/20.5 and ROS are the most appropriate techniques for estimating the variables described, emphasizing ROS when estimating parametric variables and substitution by DL/20.5 for medians. ABSTRACT The paper evaluates the influence of size series, percentage of censored data, and coefficients of variation used to generate synthetic series on the estimation of means, standard deviations, coefficients of variation, and medians in series with censored data. Seven techniques were applied to treat censored data in synthetic series with 180 scenarios (four size series, nine censoring percentages and five coefficients of variation): values proportional to the DL: zero, DL/2, DL/20.5 and DL - and parametric (MLE), robust (ROS) and Kaplan-Meier methods. Predictions were analyzed with four performance metrics (MPE, MAPE, KGE, and RMSE). It is found that the percentage of censored data and the coefficient of variation significantly alter forecast quality. It is also found that substitution by DL/2, by DL/20.5 and ROS are the most appropriate techniques for estimating the variables described, emphasizing ROS when estimating parametric variables and substitution by DL/20.5 for medians. RESUMO O artigo avalia a influência do tamanho das séries, do percentual de dados censurados e dos coeficientes de variação utilizados para gerar séries sintéticas na estimativa de médias, desvios-padrão, coeficientes de variação e medianas em séries com dados censurados. Foram aplicadas sete técnicas de tratamento de dados censurados em séries sintéticas em 180 cenários (quatro tamanhos de séries, nove percentuais de censura e cinco coeficientes de variação): valores proporcionais ao DL: zero, DL/2, DL/20.5 e DL - e métodos paramétrico (MLE), robustos (ROS) e Kaplan-Meier. As previsões foram analisadas com quatro métricas de desempenho (MPE, MAPE, KGE e RMSE). Verificou-se que o percentual de dados censurados e o coeficiente de variação alteram significativamente a qualidade das previsões. Verificou-se também que a substituição por DL/2, por DL/20.5 e ROS são as técnicas mais adequadas para estimar as variáveis descritas, destacando-se a ROS para estimar variáveis paramétricas e a substituição por DL/20.5 para medianas. |
Author | Pinto, Éber José de Andrade Silva, Fábio Henrique Rodrigues da |
AuthorAffiliation | Universidade Federal de Minas Gerais Serviço Geológico do Brasil |
AuthorAffiliation_xml | – name: Universidade Federal de Minas Gerais – name: Serviço Geológico do Brasil |
Author_xml | – sequence: 1 givenname: Fábio Henrique Rodrigues da orcidid: 0000-0003-3503-3761 surname: Silva fullname: Silva, Fábio Henrique Rodrigues da organization: Universidade Federal de Minas Gerais, Brasil – sequence: 2 givenname: Éber José de Andrade orcidid: 0000-0002-4543-8829 surname: Pinto fullname: Pinto, Éber José de Andrade organization: Universidade Federal de Minas Gerais, Brasil; Serviço Geológico do Brasil, Brasil |
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Cites_doi | 10.1016/j.asoc.2023.110066 10.5194/hess-26-5341-2022 10.1029/95WR03294 10.1021/acs.est.0c02256 10.5194/hess-23-3057-2019 10.1002/2017SW001669 10.1016/j.marpolbul.2022.113524 10.1007/s00244-020-00769-0 10.1128/AEM.01203-18 10.1061/(ASCE)ST.1943-541X.0002159 10.1590/S0100-40422014000100019 10.1021/es0111129 10.5194/hess-23-4323-2019 10.1111/j.1752-1688.1997.tb03536.x 10.1002/bimj.201900366 10.1007/s12539-015-0132-9 10.1029/WR024i012p01997 10.1002/sim.8995 10.1021/es071301c 10.1016/j.chemosphere.2020.127095 10.1177/09622802211060520 |
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Keywords | Séries sintéticas Statistic summaries Simulações estocásticas Log-normal distribution Sumários estatísticos Distribuição log-normal Synthetic series Censored data treatment methods Stochastic simulations Métodos de tratamento de dados censurados |
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SubjectTerms | Censored data treatment methods ENGINEERING, ENVIRONMENTAL ENGINEERING, GEOLOGICAL ENGINEERING, MARINE ENGINEERING, OCEAN Log-normal distribution Statistic summaries Stochastic simulations Synthetic series |
Title | Assessment of left-censored data treatment methods using stochastic simulation |
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