adjust_known: Adjust for Known Drift
In mkoohafkan/wqptools: Outlier Detection Working Group Toolbox

Description Usage Arguments Details Value Examples

Adjust a regular time series for a known drift over a known period. The drift is assumed to increase linearly in time from 0 at the beginning of the time series to the specified drift value at the end of the time series.

1	adjust_known(x, mask, drift)

`x`	A vector of data with missing values.
`mask`	A logical mask that identifies a subgroup of `x` to correct for drift. Values outside the subgroup are ignored. If no mask is specified, no overall trend is assumed.
`drift`	The drift value to correct for. The drift is assumed to occur at the last element of the masked vector `x` and linearly shrink to zero at the first element of the masked vector `x`.

This function assumes that mask specifies a contiguous block, and that the time series values are equally spaced. No consideration is given to noncontiguous masks or unequal-interval time series.

The vector x with corrected values for the subgroup specified by mask.

x = rnorm(100, 10, 0.1) + 0.025 * (0:99)
newx = adjust_known(x, drift = 99*0.025)
if (interactive()) {
  plot(x, type = 'l')
  lines(newx, col = 'red')
}