Fast Running Mean Computation

Source: R/core_func.R

Computes running sample mean of a time-series x in a fixed length window.

RunningMean(x, W, circular = FALSE)

Arguments

x

A numeric vector.
W

A numeric scalar; length of x window over which sample mean is computed.
circular

Logical; whether running sample mean is computed assuming circular nature of x time-series (see Details).

Value

A numeric vector.

Details

The length of output vector equals the length of x vector. Parameter circular determines whether x time-series is assumed to have a circular nature. Assume \(l_x\) is the length of time-series x, W is a fixed length of x time-series window.

If circular equals TRUE then

  • first element of the output time-series corresponds to sample mean of x[1:W],

  • last element of the output time-series corresponds to sample mean of c(x[l_x], x[1:(W - 1)]).

If circular equals FALSE then

  • first element of the output time-series corresponds to sample mean of x[1:W],

  • \(l_x - W + 1\)-th element of the output time-series corresponds to sample mean of x[(l_x - W + 1):l_x],

  • last W-1 elements of the output time-series are filled with NA.

See runstats.demo(func.name = "RunningMean") for a detailed presentation.

Examples

x <- rnorm(10)
RunningMean(x, 3, circular = FALSE)
#>  [1] -0.1144907  0.3980760  0.8190281  0.3265208  0.1380470  0.7299686
#>  [7]  1.4916578  0.7567328         NA         NA
RunningMean(x, 3, circular = TRUE)
#>  [1] -0.11449070  0.39807597  0.81902807  0.32652080  0.13804704  0.72996859
#>  [7]  1.49165778  0.75673284 -0.02002755 -1.00306972