oscval: Add oscillating values to a time series

In tmeeha/setset: Sensor Time Series Error Tools

Description

This function allows you to inject windows of oscillating values into a time series. This is meant to mimic a broken sensor that is oscillating between values drawn from a uniform distribution for a specified period of time.

Usage

oscval(y, n = 1, min.dur = 1, max.dur = 1, val.mu, val.sd, plot = F)

Arguments

y	The time series into which you would like to inject an error. No default.
n	The number of error events you would like to inject. Defaults to 1.
min.dur	The minimum duration, in time steps, for an error event. A random duration length is chosen to fall between the minimum and maximum (see below) duration event. Defaults to 1.
max.dur	The maximum duration, in time steps, for an error event. A random duration length is chosen to fall between the minimum (see above) and maximum duration event. Defaults to 1.
val.mu	A random oscillation amplitude is chosen for each error event from a normal distribution. val.mu is the average of that distribution. There is no default value.
val.sd	A random oscillation amplitude is chosen for each error event from a normal distribution. val.sd is the standard deviation of that distribution. There is no default value.
plot	A logical value (T or F) indicating if a plot should be returned. Defaults to F.

Value

Returns a list with three components and an optional plot. The three components are the original time series, the new error-injected time series, and a vector of 1 and 0 that indicate the locations (time steps) where errors were injected. The plot is a graphical illustration of these three components.

Examples

library(setset)
data(simseries)
d1 <- simseries
str(d1)
oscval(d1$v1, n=2, min.dur=10000, max.dur=20000, val.mu=0.5, val.sd=0.1, plot=T)
d2 <- oscval(d1$v1, n=2, min.dur=10000, max.dur=20000, val.mu=0.5, val.sd=0.1, plot=T)
str(d2)

tmeeha/setset documentation built on May 31, 2019, 4:38 p.m.