make_seasonality_features

Data frame with seasonality features.

internal

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.

Cuong Duong

prophet

Automatic Forecasting Procedure

Sean Taylor

Ben Letham

make_seasonality_features function

<dl><dt>dates</dt>
<dd>Vector of dates.</dd>
<dt>period</dt>
<dd>Number of days of the period.</dd>
<dt>series.order</dt>
<dd>Number of components.</dd>
<dt>prefix</dt>
<dd>Column name prefix.</dd></dl>

Arguments

Data frame with seasonality features. — make_seasonality_features

<dl>

<dt>dates</dt>
<dd>Vector of dates.</dd>


<dt>period</dt>
<dd>Number of days of the period.</dd>


<dt>series.order</dt>
<dd>Number of components.</dd>


<dt>prefix</dt>
<dd>Column name prefix.</dd>

</dl>

make_seasonality_features: Data frame with seasonality features.

Description

Usage

Value

Arguments