Fast Running Standard Deviation Computation

Source: R/core_func.R

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

RunningSd(x, W, circular = FALSE)

Arguments

x

A numeric vector.
W

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

Logical; whether running sample standard deviation 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 standard deviation of x[1:W],

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

If circular equals FALSE then

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

  • the \(l_x - W + 1\)-th element of the output time-series corresponds to sample standard deviation 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 = "RunningSd") for a detailed presentation.

Examples

x <- rnorm(10)
RunningSd(x, 3, circular = FALSE)
#>  [1] 0.8748456 1.2293180 1.3279382 1.1891498 0.5824692 0.7579783 1.1330298
#>  [8] 0.6353522        NA        NA
RunningSd(x, 3, circular = FALSE)
#>  [1] 0.8748456 1.2293180 1.3279382 1.1891498 0.5824692 0.7579783 1.1330298
#>  [8] 0.6353522        NA        NA