na.interp: Interpolate missing values in a time series
In pli2016/forecast: Forecasting Functions for Time Series and Linear Models
Description
Usage
Arguments
Details
Value
Author(s)
See Also
Examples
Description
Uses linear interpolation for non-seasonal series and a periodic stl
decomposition with seasonal series to replace missing values.
Usage
1
Arguments
x
time series
lambda
a numeric value suggesting Box-cox transformation
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
1
2
pli2016/forecast documentation built on May 25, 2019, 8:22 a.m.
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Description Usage Arguments Details Value Author(s) See Also Examples
Description
Uses linear interpolation for non-seasonal series and a periodic stl decomposition with seasonal series to replace missing values.
Usage
1 |
Arguments
x |
time series |
lambda |
a numeric value suggesting Box-cox transformation |
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
1 2 |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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