mdape

<p>Cross-validation results dataframe.</p>

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.

Sean Taylor

prophet

mdape: Median absolute percent error

Description

Usage

Arguments

Value