# Forecasting¶

Note

The user guide is under development. We have created a basic structure and are looking for contributions to develop the user guide further. For more details, please go to issue #361 on GitHub.

## Introduction¶

Forecasating is making forward temporal predictions based on past data. The simplest case is the univariate case.

Inputs.

Univariate time series, \(y = y(0), y(1), y(2), ..., y(N)\)

Forecasting horizon, \(fh = N+1, N+2, ..., N+h\)

Output.

Predictions of \(y\) at the times in \(fh\), \(\hat{y} = \hat{y}(N+1), \hat{y}(N+2), ..., \hat{y}(N+h)\)

Examples.

Forecasting the global population

Forecasting the price of a stock

Forecasting the daily maximum temperature in a given location

## Example¶

Predicting flights. See the Tutorial on Forecasting.

## Algorithms included in sktime¶

See the API Reference.