powered by
A handy function for adding multiple fourier series to a data frame. Works with dplyr groups too.
dplyr
tk_augment_fourier(.data, .date_var, .periods, .K = 1, .names = "auto")
Returns a tibble object describing the timeseries.
tibble
A tibble.
A date or date-time column used to calculate a fourier series
One or more periods for the fourier series
The maximum number of fourier orders.
A vector of names for the new columns. Must be of same length as the number of output columns. Use "auto" to automatically rename the columns.
Benefits
This is a scalable function that is:
Designed to work with grouped data using dplyr::group_by()
dplyr::group_by()
Add multiple differences by adding a sequence of differences using the .periods argument (e.g. lags = 1:20)
.periods
lags = 1:20
Augment Operations:
tk_augment_timeseries_signature() - Group-wise augmentation of timestamp features
tk_augment_timeseries_signature()
tk_augment_holiday_signature() - Group-wise augmentation of holiday features
tk_augment_holiday_signature()
tk_augment_slidify() - Group-wise augmentation of rolling functions
tk_augment_slidify()
tk_augment_lags() - Group-wise augmentation of lagged data
tk_augment_lags()
tk_augment_differences() - Group-wise augmentation of differenced data
tk_augment_differences()
tk_augment_fourier() - Group-wise augmentation of fourier series
tk_augment_fourier()
Underlying Function:
fourier_vec() - Underlying function that powers tk_augment_fourier()
fourier_vec()
library(tidyverse) library(timetk) m4_monthly %>% group_by(id) %>% tk_augment_fourier(date, .periods = c(6, 12), .K = 2)
Run the code above in your browser using DataLab