.sampling

Obtain the joint posterior distribution of the parameters of the Prophet
model using MCMC sampling.

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

.sampling function

<dl><dt>args</dt>
<dd>Named list of arguments suitable for the chosen backend. Must
include arguments required for MCMC sampling.</dd>
<dt>backend</dt>
<dd>"rstan" or "cmdstanr".</dd></dl>

Arguments

Obtain the joint posterior distribution of the parameters of the Prophet
model using MCMC sampling. — .sampling

<dl>

<dt>args</dt>
<dd>Named list of arguments suitable for the chosen backend. Must
include arguments required for MCMC sampling.</dd>


<dt>backend</dt>
<dd>"rstan" or "cmdstanr".</dd>

</dl>

.sampling: Obtain the joint posterior distribution of the parameters of the Prophet model using MCMC sampling.

Description

Usage

Value

Arguments