MazamaRollUtils (version 0.1.4)

roll_median: Roll Median

Description

Apply a moving-window median function to a numeric vector.

Usage

roll_median(
  x,
  width = 1L,
  by = 1L,
  align = c("center", "left", "right"),
  na.rm = FALSE
)

Value

Numeric vector of the same length as x.

Arguments

x

Numeric vector.

width

Integer width of the rolling window.

by

Integer shift by which the window is moved each iteration.

align

Character position of the return value within the window. One of: "left" | "center" | "right".

na.rm

Logical specifying whether NA values should be removed before the calculations within each window.

Details

For every index in the incoming vector x, a value is returned that is the median of all values in x that fall within a window of width width.

The align parameter determines the alignment of the return value within the window. Thus:

• align = -1 [*------] will cause the returned vector to have width-1 NA values at the right end.

• align = 0 [---*---] will cause the returned vector to have width/2 NA values at either end.

• align = 1 [------*] will cause the returned vector to have width-1 NA values at the left end.

For large vectors, theby parameter can be used to force the window to jump ahead by indices for the next calculation. Indices that are skipped over will be assigned NA values so that the return vector still has the same length as the incoming vector. This can dramatically speed up calculations for high resolution time series data.

Examples

library(MazamaRollUtils)

# Example air quality time series
t <- example_pm25$datetime
x <- example_pm25$pm25

plot(t, x, pch = 16, cex = 0.5)
lines(t, roll_median(x, width = 3), col = "goldenrod")
lines(t, roll_median(x, width = 23), col = "purple")
legend("topright", lty = c(1, 1),
       col = c("goldenrod", "purple"),
       legend = c("3-hr median", "12-hr median"))
title("3- and 23-hr Rolling median")