Advantages and Disadvantages of ARIMA Model
Advantages of ARIMA
- Simplicity: ARIMA is relatively simple to understand and implement, making it accessible to users with basic knowledge of time series analysis.
- Versatility: It can handle a wide range of time series data, including stationary and non-stationary series, making it applicable in various domains.
- Interpretability: The parameters of ARIMA models (e.g., autoregressive coefficients, moving average coefficients) can provide insights into the underlying dynamics of the time series.
Disadvantages of ARIMA
- Assumption of Linearity: ARIMA assumes that the relationship between the observations and their lagged values is linear, which may not always hold true in real-world scenarios.
- Limited Handling of Seasonality: ARIMA models are not explicitly designed to capture seasonal patterns in the data, which can lead to inaccuracies in forecasting for datasets with significant seasonal variations.
- Parameter Selection: Determining the appropriate values for the ARIMA parameters (p, d, q) often requires experimentation and can be challenging, particularly for users without extensive experience in time series analysis.
ARIMA vs SARIMA Model
Time series data, consisting of observations measured at regular intervals, is prevalent across various domains. Accurately forecasting future values from this data is crucial for informed decision-making. Two powerful statistical models, ARIMA and SARIMA, are widely used in time series forecasting. In this tutorial, we will explore the difference between ARIMA and SARIMA models for time series forecasting, understanding their strengths, limitations, and practical applications.
Table of Content
- What is ARIMA (Autoregressive Integrated Moving Average)?
- What is SARIMA(Seasonal Autoregressive Integrated Moving Average)?
- ARIMA vs SARIMA: Seasonality
- ARIMA vs SARIMA: Model flexibility
- ARIMA vs SARIMA: Forecast accuracy
- ARIMA vs SARIMA : Use-Cases
- Difference Between ARIMA and SARIMA
- Advantages and Disadvantages of ARIMA Model
- Advantages and Disadvantages of SARIMA Model
- When to use : ARIMA VS SARIMA
- Conclusion
- ARIMA V/S SARIMA Model – FAQs