This report describes and explains the results of a programming laboratory in R which had the aim of implementing an interactive tool for the illustration of theoretical quantities and analysis methods relating to stochastic processes and the modern approach to time series. In particular, by exploiting the R shiny library and other related graphics packages, such as dygraphs and shinydashboard, an application was created which, starting from the concept of random variable, develops examples on stochastic processes, and then graphically shows some main characteristics of the ARIMA processes, the steps of the Box and Jenkins procedure and the prediction according to these models. The exposition concludes with a generalization to the SARIMA models.
In questa relazione vengono descritti e spiegati i risultati di un laboratorio di programmazione in R che aveva la finalità di implementare uno strumento interattivo per l’illustrazione di quantità teoriche e di metodi di analisi relativi ai processi stocastici e all’approccio moderno alle serie storiche. In particolare, sfruttando la libreria shiny di R e altri pacchetti grafici correlati, quali dygraphs e shinydashboard, si è creata un’applicazione che, partendo dal concetto di variabile aleatoria, si sviluppa in esempi sui processi stocastici, per poi mostrare graficamente alcune caratteristiche principali dei processi ARIMA, i passi della procedura di Box e Jenkins e la previsione secondo questi modelli. Conclude l’esposizione una generalizzazione ai modelli SARIMA.
Realizzazione di un laboratorio di serie storiche con R: l'approccio moderno
CALISTI, RICCARDO
2023/2024
Abstract
This report describes and explains the results of a programming laboratory in R which had the aim of implementing an interactive tool for the illustration of theoretical quantities and analysis methods relating to stochastic processes and the modern approach to time series. In particular, by exploiting the R shiny library and other related graphics packages, such as dygraphs and shinydashboard, an application was created which, starting from the concept of random variable, develops examples on stochastic processes, and then graphically shows some main characteristics of the ARIMA processes, the steps of the Box and Jenkins procedure and the prediction according to these models. The exposition concludes with a generalization to the SARIMA models.File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.12608/71248