gapfill: Interpolate, subsample and fill gaps in time series by linear...
In GPPFourier: Calculate Gross Primary Production (GPP) from O2 Time Series

Description Usage Arguments Details Value Author(s) Examples

Interpolate, subsample and fill gaps in time series by linear interpolation

Subsample and interpolate oversampled or undersampled time series to obtain equidistant data at a lower or higher sampling frequency. Gaps are filled with linear interpolation

gapfill(x, dt = x[2, 1] - x[1, 1], units = c("auto", "secs", "mins",
  "hours", "days", "weeks"), type = "linear")

subsample(x, dt, units = c("auto", "secs", "mins", "hours", "days", "weeks"))

resample(x, dt, units = c("auto", "secs", "mins", "hours", "days", "weeks"))

`x`	Data frame with time in first column and time series data in second.
`dt`	Sampling interval. Default to time difference of first two observations
`units`	Optional: units of `dt`. Only necessary when time is of class `POSIXt` and `dt` is not of class `difftime`.
`type`	Type of interpolation. Only linear interpolation implemented

Subsampling, interpolating and gapfilling

An equidistant times series with sampling interval dt is created by linear interpolation. gapfill takes the time interval between the first and second observation as default value for dt. subsample and resample require a value of dt.

A data frame with time and interpolated time series.

Tom Cox <tom.cox@uantwerp.be>