modeltime_multiforecast: Forecasting of multiple models over multiple time series

In sknifedatar: Swiss Knife of Data

Description

allows forecasting on multiple time series from multiple fitted models.

Usage

modeltime_multiforecast(models_table, .h = NULL, .prop = NULL)

Arguments

models_table	'table_time' tibble generated with the modeltime_multifit() function.
.h	prediction horizon of the modeltime_forecast() function.
.prop	time series split partition ratio. If "h" is specified, this function predicts on the testing partition.

Details

this function takes the 'table_time' object generated with the modeltime_multifit() function, the modeltime_forecast() from the package 'modeltime' is applied to each model for each series.

Value

'models_table' tibble with a new column called 'nested_forecast' where the predictions are stored.

Examples

# Data
data_serie <- sknifedatar::table_time
                                     
# Forecast
sknifedatar::modeltime_multiforecast(data_serie$table_time, .prop=0.8)

sknifedatar documentation built on June 1, 2021, 9:08 a.m.