Include interactive plots that show how parameters like the "smoothing rate" in Exponential Smoothing change the forecast line in real-time. Implementation Resources You can build this using the following tools and libraries: Forecasting: Principles and Practice (3rd ed) - OTexts
Use STL decomposition (Seasonal-Trend decomposition using LOESS) to break down the user's data into Trend, Seasonality, and Remainder components. Forecasting: Principles and Practice
Forecasts are equal to the value of the last observation. Include interactive plots that show how parameters like
A variation of the naive method that allows forecasts to increase or decrease over time based on the average change in historical data. Core Functionality A variation of the naive method that allows
This interactive tool would let users upload a dataset and instantly compare its performance across the four key benchmark methods mentioned in the "Forecaster's Toolbox" (Chapter 5):