RJ-NPN / TimeSeriesAnalysis

Time series analysis using AR, ARIMA, SARIMAX on monthly Beer production by Austrian company.

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TimeSeriesAnalysis

Production

Following is the prediction made using auto regressive model on australian beer production:

Prediction

Since in production their is presence of trend and sesonality, lets us check how SARIMAX model behaves, following are the results:

SARIMAX

Outliers in ARIMA models disrupt linear relationships and Gaussian error assumptions, leading to biased estimates and inaccurate forecasts. They distort historical patterns, complicating model interpretation and reducing predictive reliability. Refer: ARIMA_Isues_With_Outliers_Or_Spike_Data

Dataset: Walmart Recruiting - Store Sales Forecasting Source: Kaggle

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Time series analysis using AR, ARIMA, SARIMAX on monthly Beer production by Austrian company.


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