sw_augment: Augment data according to a tidied model

In business-science/sweep: Tidy Tools for Forecasting

Augment data according to a tidied model

Description

Given an R statistical model or other non-tidy object, add columns to the original dataset such as predictions, residuals and cluster assignments.

Usage

sw_augment(x, ...)

Arguments

x	model or other R object to convert to data frame
...	other arguments passed to methods

Details

sw_augment() is a wrapper for broom::augment(). The benefit of sw_augment is that it has methods for various time-series model classes such as HoltWinters, ets, Arima, etc.

For non-time series, sw_augment() defaults to broom::augment(). The only difference is that the return is a tibble.

Note that by convention the first argument is almost always data, which specifies the original data object. This is not part of the S3 signature, partly because it prevents rowwise_df_tidiers from taking a column name as the first argument.

See Also

broom::augment()

business-science/sweep documentation built on Feb. 2, 2024, 2:49 a.m.