Aplicación de modelo ARIMA para el pronóstico de exportación de flores del Ecuador.

Abstract

The world is always changing, and this influences the way people live their daily lives. The technological advances of the recent decade have represented a significant step forward in various fields in which different tools and knowledge stand out, such as business intelligence for better decision making. The present study aims to explain and demonstrate how the autoregressive integrated moving average statistical model is used to analyze and forecast time series. The variables used to carry out the forecast were net weight and FOB, from which the ARIMA (1, 0, 2) (0, 1, 1) model was applied for the net weight variable and the ARIMA (2, 0, 1) (0, 1, 2) model for the FOB variable. To achieve the objective, the Rstudio program was used, which helped to manage efficiently from the preparation of the data to the execution of the statistical analyses. The objective was the exports of the Ecuadorian flower sector for the period 1990-2023 since flower exports are a relevant economic indicator for the country. The study compiles historical data on flower exports and performs an exploratory analysis to understand the trends and patterns present in the data. The results obtained revealed valuable information for companies operating in the agricultural sector.