RunningSd: Fast Running Standard Deviation Computation

In martakarass/runstats: Fast Computation of Running Statistics for Time Series

Fast Running Standard Deviation Computation

Description

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

Usage

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).

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.

Value

A numeric vector.

Examples

x <- rnorm(10)
RunningSd(x, 3, circular = FALSE)
RunningSd(x, 3, circular = FALSE)

martakarass/runstats documentation built on April 7, 2022, 11:37 a.m.