Description Usage Arguments Details Value
View source: R/utils-data-processing.R
Impute missing samples using linear interpolation
1 2 3 4 5 6 | interpolate_missing_samples(
data,
period = NULL,
tol = 1e-06,
interpolate_covariates = FALSE
)
|
data |
dataset to modify |
period |
period to check the times against (if |
tol |
tolerance for the period |
interpolate_covariates |
|
First, check if the data are evenly sampled in time. If not, we
exit early. Next, apply forecast::na.interp()
to each variable that has
non-finite values.
the dataset, with interpolated samples
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