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

<table summary="R argblock">
<tr valign="top">
<td><code>m</code></td>
<td>
<p>Prophet model object.</p>
</td>
</tr>
<tr valign="top">
<td><code>cutoff</code></td>
<td>
<p>Date, possibly as string. Changepoints are only retained if
changepoints &lt;= cutoff.</p>
</td>
</tr>
</table>

<p>An unfitted Prophet model object with the same parameters as the
input model.
</p>

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

`m`	Prophet model object.
`cutoff`	Date, possibly as string. Changepoints are only retained if changepoints <= cutoff.

prophet_copy

Description

Usage

Arguments

Value

prophet

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