The White Noise Model – Time Series Analysis, Regression, and Forecasting

The white noise model can be used to represent the nature of noise in a data set. For time series data, auto-correlation plots and the Ljung-Box test are two ways to test for white noise.

8.1 Stationarity and differencing Forecasting: Principles and Practice (2nd ed)

Forecasting, Free Full-Text

5.1 The linear model Forecasting: Principles and Practice (2nd ed)

Multivariate Time Series Analysis for Forecasting & Modeling

Time Series Analysis: Forecasting Trends with Time Series Model Simulation - FasterCapital

A Simple Approach to Hierarchical Time Series Forecasting with Machine Learning, by Leonie Monigatti

8.1 Stationarity and differencing Forecasting: Principles and Practice (2nd ed)

What Is Time-Series Forecasting?

The White Noise Model – Time Series Analysis, Regression, and Forecasting

Forecasting of CO2 level on Mona Loa dataset using Gaussian process regression (GPR) — scikit-learn 1.4.1 documentation

A Deep Dive on ARIMA Models. From white noise to SARIMAX and beyond, by Matt Sosna