Implements a procedure for forecasting time series data based on
an additive model where non-linear trends are fit with yearly, weekly, and
daily seasonality, plus holiday effects. It works best with time series
that have strong seasonal effects and several seasons of historical data.
Prophet is robust to missing data and shifts in the trend, and typically
handles outliers well.

Automatic Forecasting Procedure

package-ubuntu-20.04-r-4.0.5#cran#prophet-1.0

<p>Prepare dataframe for plotting seasonal components.
</p>

<table summary="R argblock">
<tr valign="top">
<td><code>m</code></td>
<td>
<p>Prophet object.</p>
</td>
</tr>
<tr valign="top">
<td><code>ds</code></td>
<td>
<p>Array of dates for column ds.</p>
</td>
</tr>
</table>

<p>A dataframe with seasonal components on ds.
</p>

package-ubuntu-20.04-r-4.0.5#cran#prophet-1.0#docs#seasonality_plot_df

seasonality_plot_df

Description

Usage

Arguments

Value

prophet

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