Intro to Time Series
The smoothing parameter is a crucial value used in time series analysis that determines the weight given to past observations when making forecasts. It plays a significant role in balancing the trade-off between responsiveness to recent changes and the stability of the forecast. A higher smoothing parameter places more emphasis on recent data, while a lower value gives more weight to older observations, affecting the overall accuracy and reliability of the predictions.
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