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layout: home | layout: home | |||
title: Prophet | title: Prophet | |||
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Prophet is a procedure for forecasting time series data based on an additive mod el where non-linear trends are fit with yearly, weekly, and daily seasonality, p lus holiday effects. It works best with time series that have strong seasonal ef fects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well. | Prophet is a procedure for forecasting time series data based on an additive mod el where non-linear trends are fit with yearly, weekly, and daily seasonality, p lus holiday effects. It works best with time series that have strong seasonal ef fects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well. | |||
Prophet is [open source software](https://code.facebook.com/projects/) released by Facebook's [Core Data Science team](https://research.fb.com/category/data-sci ence/). It is available for download on [CRAN](https://cran.r-project.org/packa ge=prophet) and [PyPI](https://pypi.python.org/pypi/fbprophet/). | Prophet is [open source software](https://code.facebook.com/projects/) released by Facebook's [Core Data Science team](https://research.fb.com/category/data-sci ence/). It is available for download on [CRAN](https://cran.r-project.org/packa ge=prophet) and [PyPI](https://pypi.python.org/pypi/prophet/). | |||
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