Forecasting: Principles And Practice Online

Forecasts are equal to the mean of historical data.

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 Forecasting: Principles and Practice

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 Forecasts are equal to the mean of historical data

Forecasts are equal to the value of the last observation. Forecasting: Principles and Practice

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):