# name
Sèries temporals amb memòria llarga: models ARFIMA

# metadata.dc.description[].value
Treballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2023 , Director: Josep Vives i Santa Eulàlia

# metadata.dc.description.abstract[].value
[en] Time series analysis plays a vital role in understanding various phenomena in a wide variety of fields. Over the years, more complex statistical models have been developed that allow us to analyze time series in a more accurate way. This project studies in depth one of them: the ARFIMA models. These models are very useful for examining long memory time series. The main purpose of this project is to provide a comprehensive analysis of these models, including their theoretical foundations, estimation methods and a practical implementation. In particular, the $R$ programming language is used to evaluate the possibility of modeling the time series that shows the air quality of Barcelona between 2017 and 2019 using an ARFIMA model.

# metadata.dc.rights[].value
cc-by-nc-nd (c) Sergio Muñoz Martı́nez, 2023

# metadata.dc.source[].value
Treballs Finals de Grau (TFG) - Matemàtiques

# metadata.dc.title[].value
Sèries temporals amb memòria llarga: models ARFIMA