roll_mean {roll}

Rolling Means

Description

A function for computing the rolling and expanding means of time-series data.

Usage

roll_mean(x, width, weights = rep(1, width), min_obs = width,
  complete_obs = FALSE, na_restore = FALSE, online = TRUE)

Arguments

x

vector or matrix. Rows are observations and columns are variables.

width

integer. Window size.

weights

vector. Weights for each observation within a window.

min_obs

integer. Minimum number of observations required to have a value within a window, otherwise result is NA.

complete_obs

logical. If TRUE then rows containing any missing values are removed, if FALSE then each value is used.

na_restore

logical. Should missing values be restored?

online

logical. Process observations using an online algorithm.

Value

An object of the same class and dimension as x with the rolling and expanding means.

Examples

n <- 15
x <- rnorm(n)
weights <- 0.9 ^ (n:1)

# rolling means with complete windows
roll_mean(x, width = 5)

# rolling means with partial windows
roll_mean(x, width = 5, min_obs = 1)

# expanding means with partial windows
roll_mean(x, width = n, min_obs = 1)

# expanding means with partial windows and weights
roll_mean(x, width = n, min_obs = 1, weights = weights)