Affiliation:
1. Universidade Federal de Minas Gerais, Brasil
2. Universidade Federal de Minas Gerais, Brasil; Serviço Geológico do Brasil, Brasil
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.
Subject
Earth-Surface Processes,Water Science and Technology,Aquatic Science,Oceanography
Reference36 articles.
1. Evaluation of statistical treatments of left-censored environmental data using coincident uncensored data sets: I. Summary statistics;Antweiller R. C.;Environmental Science & Technology,2008
2. Microbial-Maximum Likelihood estimation tool for microbial quantification in food from left-censored data using maximum likelihood.;Bahk G. J.;Frontiers in Microbiology,2021
3. Portaria GM/MS nº 888, de 4 de maio de 2021. Altera o Anexo XX da Portaria de Consolidação GM/MS nº 5, de 28 de setembro de 2017, para dispor sobre os procedimentos de controle e de vigilância da qualidade da água para consumo humano e seu padrão de potabilidade;Diário Oficial da República Federativa do Brasil,2021
4. Methods for handling left-censored data in quantitative microbial risk assessment;Canales R. A.;Applied and Environmental Biology,2018
5. Statistical assessment of micropollutants occurrence, time trend, fate and human health risk using left-censored water quality data;Cantoni B.;Chemosphere,2020