This article shows, using R software, how to seasonally adjust a time series using the X13-ARIMA-SEATS program and the seasonal package developed by Christoph Sax. In addition to presenting step-by-step seasonal adjustment, the article also explores how to analyze the program output and how to forecast the original and seasonally adjusted time series. A case study was proposed using the Brazilian industrial production. It was verified that the effect of Carnival, Easter and working days improved the seasonal adjustment when treated by the model.
