Univariate, time series models

An autoregressive integrated moving average (ARIMA) model is a generalization of an autoregressive moving average (ARMA)…

Exponential smoothing is a rule of thumb technique for smoothing time series data using the exponential window…

An artificial neural network (ANN) is a model which is based on a collection of connected units or nodes called artificial neurons, which loosely model the…

Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality,…

STL is a versatile and robust method for decomposing time series. STL is an acronym for “Seasonal and Trend decomposition using Loess”, while Loess is a method…

TBATS is a time series model that is useful for handling data with multiple seasonal patterns. TBATS is an acronym for key features of the model: T:…

The Theta model is a simple method for forecasting that involves fitting two theta-lines, forecasting the lines using simple exponential smoothing, and then…

A simple model using the last value as a prediction for the…