Skip to content

Navigation Menu

Sign in
Appearance settings

Search code, repositories, users, issues, pull requests...

Provide feedback

We read every piece of feedback, and take your input very seriously.

Saved searches

Use saved searches to filter your results more quickly

Sign up
Appearance settings
forked from facebook/prophet

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

License

Notifications You must be signed in to change notification settings

jianfly/prophet

Folders and files

NameName
Last commit message
Last commit date

Latest commit

History

60 Commits
R
R

Repository files navigation

Prophet: Automatic Forecasting Procedure

Prophet is a procedure for forecasting time series data. It is based on an additive model where non-linear trends are fit with yearly and weekly seasonality, plus holidays. It works best with daily periodicity data with at least one year of historical data. Prophet is robust to missing data, shifts in the trend, and large outliers.

Prophet is open source software released by Facebook's Core Data Science team. It is available for download on CRAN and PyPI.

Important links

Installation in R

Prophet is a CRAN package so you can use install.packages:

# R
> install.packages('prophet')

After installation, you can get started!

Windows

On Windows, R requires a compiler so you'll need to follow the instructions provided by rstan. The key step is installing Rtools before attempting to install the package.

Installation in Python

Prophet is on PyPI, so you can use pip to install it:

# bash
$ pip install fbprophet

The major dependency that Prophet has is pystan. PyStan has its own installation instructions.

After installation, you can get started!

Windows

On Windows, PyStan requires a compiler so you'll need to follow the instructions. The key step is installing a recent C++ compiler.

About

Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

Resources

License

Contributing

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Python 48.9%
  • R 41.9%
  • Stan 9.2%

AltStyle によって変換されたページ (->オリジナル) /