R: Remove spikes from a time series

despike {oce}

R Documentation

Remove spikes from a time series

Description

The method identifies spikes with respect to a "reference" time-series, and replaces these spikes with the reference value, or with NA according to the value of action; see “Details”.

Usage

despike(x, reference = c("median", "smooth", "trim"), n = 4, k = 7,
  min = NA, max = NA, replace = c("reference", "NA"), skip)

Arguments

`x`	a vector of (time-series) values, a list of vectors, a data frame, or an object that inherits from class `oce`.
`reference`	indication of the type of reference time series to be used in the detection of spikes; see ‘Details’.
`n`	an indication of the limit to differences between `x` and the reference time series, used for `reference="median"` or `reference="smooth"`; see ‘Details.’
`k`	length of running median used with `reference="median"`, and ignored for other values of `reference`.
`min`	minimum non-spike value of `x`, used with `reference="trim"`.
`max`	maximum non-spike value of `x`, used with `reference="trim"`.
`replace`	an indication of what to do with spike values, with `"reference"` indicating to replace them with the reference time series, and `"NA"` indicating to replace them with `NA`.
`skip`	optional vector naming columns to be skipped. This is ignored if `x` is a simple vector. Any items named in `skip` will be passed through to the return value without modification. In some cases, `despike` will set up reasonable defaults for `skip`, e.g. for a `ctd` object, `skip` will be set to `c("time", "scan", "pressure")` if it is not supplied as an argument.

Details

Three modes of operation are permitted, depending on the value of reference.

For reference="median", the first step is to linearly interpolate across any gaps (spots where x==NA), using approx with rule=2. The second step is to pass this through runmed to get a running median spanning k elements. The result of these two steps is the "reference" time-series. Then, the standard deviation of the difference between x and the reference is calculated. Any x values that differ from the reference by more than n times this standard deviation are considered to be spikes. If replace="reference", the spike values are replaced with the reference, and the resultant time series is returned. If replace="NA", the spikes are replaced with NA, and that result is returned.
For reference="smooth", the processing is the same as for "median", except that smooth is used to calculate the reference time series.
For reference="trim", the reference time series is constructed by linear interpolation across any regions in which x<min or x>max. (Again, this is done with approx with rule=2.) In this case, the value of n is ignored, and the return value is the same as x, except that spikes are replaced with the reference series (if replace="reference" or with NA, if replace="NA".

Value

A new vector in which spikes are replaced as described above.

Author(s)

Dan Kelley

Examples


n <- 50
x <- 1:n
y <- rnorm(n=n)
y[n/2] <- 10                    # 10 standard deviations
plot(x, y, type='l')
lines(x, despike(y), col='red')
lines(x, despike(y, reference="smooth"), col='darkgreen')
lines(x, despike(y, reference="trim", min=-3, max=3), col='blue')
legend("topright", lwd=1, col=c("black", "red", "darkgreen", "blue"),
       legend=c("raw", "median", "smooth", "trim"))

# add a spike to a CTD object
data(ctd)
plot(ctd)
T <- ctd[["temperature"]]
T[10] <- T[10] + 10
ctd[["temperature"]] <- T
CTD <- despike(ctd)
plot(CTD)

[Package oce version 1.0-1 Index]