plot.lagged_df: Plot datasets with lagged features

In nredell/forecastML: Time Series Forecasting with Machine Learning Methods

Description

Plot datasets with lagged features to view ther direct forecasting setup across horizons.

Usage

## S3 method for class 'lagged_df'
plot(x, ...)

Arguments

x	An object of class 'lagged_df' from create_lagged_df().
...	Not used.

Value

A single plot of class 'ggplot' if lookback was specified in create_lagged_df(); a list of plots, one per feature, of class 'ggplot' if lookback_control was specified.

Examples

# Sampled Seatbelts data from the R package datasets.
data("data_seatbelts", package = "forecastML")
#------------------------------------------------------------------------------
# Example 1 - Training data for 3 horizon-specific models w/ common lags per predictor.
horizons <- c(1, 6, 12)
lookback <- 1:15

data_train <- create_lagged_df(data_seatbelts, type = "train", outcome_col = 1,
                               lookback = lookback, horizon = horizons)
plot(data_train)
#------------------------------------------------------------------------------
# Example 2 - Training data for one 3-month horizon model w/ unique lags per predictor.
horizons <- 3
lookback <- list(c(3, 6, 9, 12), c(4:12), c(6:15), c(8))

data_train <- create_lagged_df(data_seatbelts, type = "train", outcome_col = 1,
                               lookback_control = lookback, horizon = horizons)
plot(data_train)

nredell/forecastML documentation built on June 14, 2020, 5:12 p.m.