tk_augment_fourier: Add many fourier series to the data

In timetk: A Tool Kit for Working with Time Series

Add many fourier series to the data

Description

A handy function for adding multiple fourier series to a data frame. Works with dplyr groups too.

Usage

tk_augment_fourier(.data, .date_var, .periods, .K = 1, .names = "auto")

Arguments

.data	A tibble.
.date_var	A date or date-time column used to calculate a fourier series
.periods	One or more periods for the fourier series
.K	The maximum number of fourier orders.
.names	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.

Details

Benefits

This is a scalable function that is:

• Designed to work with grouped data using dplyr::group_by()

• Add multiple differences by adding a sequence of differences using the .periods argument (e.g. lags = 1:20)

Value

Returns a tibble object describing the timeseries.

See Also

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:

• fourier_vec() - Underlying function that powers tk_augment_fourier()

Examples

library(dplyr)

m4_monthly %>%
    group_by(id) %>%
    tk_augment_fourier(date, .periods = c(6, 12), .K = 2)

timetk documentation built on Nov. 2, 2023, 6:18 p.m.