parse_seasonality_args

Get number of Fourier components for built-in seasonalities.

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

parse_seasonality_args function

<dl><dt>m</dt>
<dd>Prophet object.</dd>
<dt>name</dt>
<dd>String name of the seasonality component.</dd>
<dt>arg</dt>
<dd>'auto', TRUE, FALSE, or number of Fourier components as
provided.</dd>
<dt>auto.disable</dt>
<dd>Bool if seasonality should be disabled when 'auto'.</dd>
<dt>default.order</dt>
<dd>Int default Fourier order.</dd></dl>

Arguments

Get number of Fourier components for built-in seasonalities. — parse_seasonality_args

<dl>

<dt>m</dt>
<dd>Prophet object.</dd>


<dt>name</dt>
<dd>String name of the seasonality component.</dd>


<dt>arg</dt>
<dd>'auto', TRUE, FALSE, or number of Fourier components as
provided.</dd>


<dt>auto.disable</dt>
<dd>Bool if seasonality should be disabled when 'auto'.</dd>


<dt>default.order</dt>
<dd>Int default Fourier order.</dd>

</dl>

parse_seasonality_args: Get number of Fourier components for built-in seasonalities.

Description

Usage

Value

Arguments