na.interp {forecast} | R Documentation |
Interpolate missing values in a time series
Description
By default, uses linear interpolation for non-seasonal series. For seasonal series, a robust STL decomposition is first computed. Then a linear interpolation is applied to the seasonally adjusted data, and the seasonal component is added back.
Usage
na.interp(
x,
lambda = NULL,
linear = (frequency(x) <= 1 | sum(!is.na(x)) <= 2 * frequency(x))
)
Arguments
x |
time series |
lambda |
Box-Cox transformation parameter. If |
linear |
Should a linear interpolation be used. |
Details
A more general and flexible approach is available using na.approx
in
the zoo
package.
Value
Time series
Author(s)
Rob J Hyndman
See Also
Examples
data(gold)
plot(na.interp(gold))
[Package forecast version 8.23.0 Index]