sdrobnorm {stepR}

Robust standard deviation estimate

Description

Robust estimation of the standard deviation of Gaussian data.

Usage

sdrobnorm(x, p = c(0.25, 0.75), lag = 1,
          supressWarningNA = FALSE, supressWarningResultNA = FALSE)

Arguments

x

a vector of numerical observations. NA entries will be removed with a warning. The warning can be supressed by setting supressWarningNA to TRUE. Other non finite values are not allowed

p

vector of two distinct probabilities

lag

a single integer giving the lag of the difference used, see diff, if a numeric is passed a small tolerance will be added and the value will be converted by as.integer

supressWarningNA

a single logical, if TRUE no warning will be given for NA entries in x

supressWarningResultNA

a single logical, if TRUE no warning will be given if the result is NA

Details

Compares the difference between the estimated sample quantile corresponding to p after taking (lagged) differences) with the corresponding theoretical quantiles of Gaussian white noise to determine the standard deviation under a Gaussian assumption. If the data contain (few) jumps, this will (on average) be a slight overestimate of the true standard deviation.

This estimator has been inspired by (1.7) in (Davies and Kovac, 2001).

Value

Returns the estimate of the sample's standard deviation, i.e. a single non-negative numeric, NA if length(x) < lag + 2.

References

Davies, P. L., Kovac, A. (2001) Local extremes, runs, strings and multiresolution. The Annals of Statistics 29, 1–65.

See Also

sd, diff, parametricFamily, family

Examples

# simulate data sample
y <- rnorm(100, c(rep(1, 50), rep(10, 50)), 2)
# estimate standard deviation
sdrobnorm(y)