Getting started with runner

Dawid Kałędkowski

2026-01-30

About

Package contains standard running functions (aka. rolling) with additional options like varying window size, lagging, handling missings and windows depending on date. runner brings also rolling streak and rolling which, what extends beyond range of functions already implemented in R packages. This package can be successfully used to manipulate and aggregate time series or longitudinal data.

Using runner

runner package provides functions applied on running windows. The most universal function is runner::runner which gives user possibility to apply any R function f in running window. In example below 4-months correlation is calculated lagged by 1 month.

library(runner)

x <- data.frame(
  date = seq.Date(Sys.Date(), Sys.Date() + 365, length.out = 20),
  a = rnorm(20),
  b = rnorm(20)
)

runner(
  x,
  lag = "1 months",
  k = "4 months",
  idx = x$date,
  f = function(x) {
    cor(x$a, x$b)
  }
)

There are different kinds of running windows and all of them are implemented in runner.

Running windows

Following diagram illustrates what running windows are - in this case running windows of length k = 4. For each of 15 elements of a vector each window contains current 4 elements.

Window size

k denotes number of elements in window. If k is a single value then window size is constant for all elements of x. For varying window size one should specify k as integer vector of length(k) == length(x) where each element of k defines window length. If k is empty it means that window will be cumulative (like base::cumsum). Example below illustrates window of k = 4 for 10th element of vector x.

runner(1:15, k = 4)

Window lag

lag denotes how many observations windows will be lagged by. If lag is a single value than it is constant for all elements of x. For varying lag size one should specify lag as integer vector of length(lag) == length(x) where each element of lag defines lag of window. Default value of lag = 0. Example below illustrates window of k = 4 lagged by lag = 2 for 10-th element of vector x. Lag can also be negative value, which shifts window forward instead of backward.

runner(
  1:15,
  k = 4,
  lag = 2
)