identifikasi model runtun waktu nonstasioner
This content focuses on the critical process of identifying non-stationary time series models, a fundamental step in accurate time series analysis. Recognizing non-stationarity is crucial because it indicates that a series' statistical properties, such as mean or variance, change over time, rendering standard time series models inappropriate for direct application. Effective identification often involves employing specific stationarity tests to ensure the correct modeling approach is selected for robust forecasting and inference.