sample_predictive_trend

Simulate the trend using the extrapolated generative model.

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

sample_predictive_trend function

<dl><dt>model</dt>
<dd>Prophet object.</dd>
<dt>df</dt>
<dd>Prediction dataframe.</dd>
<dt>iteration</dt>
<dd>Int sampling iteration to use parameters from.</dd></dl>

Arguments

Simulate the trend using the extrapolated generative model. — sample_predictive_trend

<dl>

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


<dt>df</dt>
<dd>Prediction dataframe.</dd>


<dt>iteration</dt>
<dd>Int sampling iteration to use parameters from.</dd>

</dl>

sample_predictive_trend: Simulate the trend using the extrapolated generative model.

Description

Usage

Value

Arguments