In time series forecasting, which method captures both trend and seasonality in the data?
- Moving Average
- Exponential Smoothing
- ARIMA (AutoRegressive Integrated Moving Average)
- Exponential Moving Average
ARIMA (AutoRegressive Integrated Moving Average) captures both trend and seasonality in time series data. It combines autoregressive, differencing, and moving average components to model complex time series patterns, making it a powerful method for forecasting data with seasonal and trend components.
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