znorm: Z-normalizes a time series by subtracting its mean and...

In jMotif/jmotif-R: Time Series Analysis Toolkit Based on Symbolic Aggregate Discretization, i.e. SAX

Z-normalizes a time series by subtracting its mean and dividing by the standard deviation.

Description

Z-normalizes a time series by subtracting its mean and dividing by the standard deviation.

Usage

znorm(ts, threshold = 0.01)

Arguments

ts	the input time series.
threshold	the z-normalization threshold value, if the input time series' standard deviation will be found less than this value, the procedure will not be applied, so the "under-threshold-noise" would not get amplified.

References

Dina Goldin and Paris Kanellakis, On similarity queries for time-series data: Constraint specification and implementation. In Principles and Practice of Constraint Programming (CP 1995), pages 137-153. (1995)

Examples

x = seq(0, pi*4, 0.02)
y = sin(x) * 5 + rnorm(length(x))
plot(x, y, type="l", col="blue")
lines(x, znorm(y, 0.01), type="l", col="red")

jMotif/jmotif-R documentation built on Sept. 27, 2022, 4:31 p.m.