multilag: Create multiple lags of time series dataframe

In yForecasting/leadingindicators: Find relevant leading indicators for time series forecasting

Description

This function creates lagged versions of time series variables that are given in different columns of a dataframe format. The lag is added to the column name of the data frame.

Usage

multilag(data, x_dates, y_dates, lags)

Arguments

data	Dataframe containing the variables where the lagged versions are created from.
x_dates	Vector of the date arguments for the corresponding dataframe.
y_dates	Vector of the date arguments for the target variable. The x variables will be lagged up until there are no y values.
lags	Vector of lags that should be generated as lagged variables for all the columns in the dataframe. The number of dates in x_dates proceeding the first date of y_dates is equal to the maximul number of lags. Adjust y_dates for higher lags.

Examples

tbl <- data.frame(a = c(1:10), b = c(11:20), c = c(21:30))
x_dat <- c("2021-01-01","2021-02-01","2021-03-01","2021-04-01","2021-05-01","2021-06-01","2021-07-01","2021-08-01","2021-09-01","2021-10-01")
y_dat <- c("2021-06-01","2021-07-01","2021-08-01","2021-09-01","2021-10-01")
lag_nr <- c(1:5)
tbl_lagged <- multilag(data = tbl, x_dates = x_dat, y_dates = y_dat, lags = lag_nr)

yForecasting/leadingindicators documentation built on Dec. 12, 2021, 3:09 p.m.