SARIMA model | Time Series Analysis #timeseriesanalysis #sarima @content-academy

In this video, I detail the SARIMA (Seasonal AutoRegressive Integrated Moving Average) model, a powerful tool for forecasting time series data with seasonal patterns. I break down the components of the SARIMA model, including the non-seasonal (p, d, q) and seasonal (P, D, Q, s) parameters, and explain how to compute and interpret each one. I stated the different parameters - the Autoregressive Parameter, the Backward Shift parameter, the Degree of Differencing, the Time Series Parameter, the Moving Average Parameter and the Error term or White process parameter. I showed a step-by-step approach on how to compute the SARIMA Model

If you're looking to master time series forecasting, understanding and applying SARIMA is a must! Watch the video to get a comprehensive tutorial and practical tips.

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Видео SARIMA model | Time Series Analysis #timeseriesanalysis #sarima @content-academy канала CONTENT-ACADEMY