For example, if Month 4 showed 200 sales and Month 5 showed 250 sales, add 200 plus 250 and divide by 2 to get 225. You can estimate that you will have 225 sales for Month 6.

The library supports both univariate and multivariate time series, and can generate deterministic or probabilistic forecasts. For example, training an Exponential Smoothing model on a time series of ...

This study has shown that the simple exponential smoothing model (SES) is well suited as a tool for predicting overbreak. Although several forecasting methods are already being used, as evidenced in ...

Keywords Stock Prediction, ARIMA Model, Exponential Smoothing Model, Machine Learning, ARIMAML Model Share and Cite: Ibrahim, A. , Saeed, B. and Fadil, M. (2023) Forecasting Stock Prices with an ...

Moreover, no study has used SEER data to build these models. Therefore, in this study, we explored the ability of SEER time-series data to predict lung cancer death rates using three models: the ...