uts_interpolate_na: Replace NA by interpolation separate for each time series

In WoVollmer/pkgTS: Time Series functions

Description

If there are there any NAs in monthly data set => replace NA by interpolation separate for each time series

Usage

uts_interpolate_na(data, freq)

Arguments

data	A data frame (column count)
freq	season lenght, e.g. freq = 12 (1 year) for monthly temperature data

Value

data frame

if no NAs exist in count column => return unchanged data frame

otherwise:
A tibble: 120 x 9
City Measure Year_Month Year Month count Raw NA_replace
<chr> <fct> <mth> <dbl> <fct> <dbl> <dbl> <dbl>

data frame with columns

• count (updated) = orig and interplolated counts (replaced NAs, if any)

• Raw (added) = orig counts (w/o replaced NAs)

• NA_replace (added) = NAs (if count value exists) and interplolated counts (replaced NAs, if any)

• for plots w/ & w/o replaced counts

References

Schlittgen, Rainer - De Gruyter, Angewandte Zeitreihenanalyse mit R, 2015 ISBN 978-3-11-041398-4

Examples

dplyr::slice(uts_interpolate_na(monthly_climate_giessen, freq =12), 75:90)

WoVollmer/pkgTS documentation built on June 2, 2021, 4:02 a.m.