| tk_augment_lags {timetk} | R Documentation |
A handy function for adding multiple lagged columns to a data frame.
Works with dplyr groups too.
tk_augment_lags(.data, .value, .lags = 1, .names = "auto")
.data |
A tibble. |
.value |
A column to have a difference transformation applied |
.lags |
One or more lags for the difference(s) |
.names |
A vector of names for the new columns. Must be of same length as |
Benefits
This is a scalable function that is:
Designed to work with grouped data using dplyr::group_by()
Add multiple lags by adding a sequence of lags using
the .lags argument (e.g. .lags = 1:20)
Returns a tibble object describing the timeseries.
Augment Operations:
tk_augment_timeseries_signature() - Group-wise augmentation of timestamp features
tk_augment_holiday_signature() - Group-wise augmentation of holiday features
tk_augment_slidify() - Group-wise augmentation of rolling functions
tk_augment_lags() - Group-wise augmentation of lagged data
tk_augment_differences() - Group-wise augmentation of differenced data
tk_augment_fourier() - Group-wise augmentation of fourier series
Underlying Function:
lag_vec() - Underlying function that powers tk_augment_lags()
library(tidyverse)
library(timetk)
m4_monthly %>%
group_by(id) %>%
tk_augment_lags(value, .lags = 1:20)