AN ANALYSIS OF THE WATER OF RIVERS JAGUARI AND ATIBAIA USING DISTRIBUTION-FREE MULTIPLE IMPUTATION AND BLOCKS BOOTSTRAP - OLIVEIRA, Eduardo Schneider Bueno de; PIÃO, Antonio Carlos Simões; ANGELIS, Dejanira de Franceschi de (Brazilian Journal of Biometrics, 2016)
Longitudinal data have a huge relevance to evaluate several factors. Sometimes, there is also a problem of non collected data at some moment during the study, which leads to the necessity of, or desconsidering them, or using suitable techniques to estimate missing data. In this study, results based on data about the water quality of rivers Jaguari and Atibaia, results of multiple imputation for non normal data, through the \Distribution-free multiple imputation" and posteriorly results for data analysis using blocks Bootstrap techniques are presented. Lastly, practical results obtained through the analysis are shown, aiming to brie y identify the situation of both rivers along the 15 years of study.