na.interp

0th

Percentile

Interpolate missing values in a time series

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.

Keywords
ts
Usage
na.interp(x, lambda = NULL, linear = (frequency(x) 
Arguments
x

time series

lambda

Box-Cox transformation parameter. If lambda="auto", then a transformation is automatically selected using BoxCox.lambda. The transformation is ignored if NULL. Otherwise, data transformed before model is estimated.

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

See Also

tsoutliers

Aliases
  • na.interp
Examples
# NOT RUN {
data(gold)
plot(na.interp(gold))

# }
Documentation reproduced from package forecast, version 8.7, License: GPL-3

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