使用 R 对不均匀间隔的单变量时间序列进行缺失值插补

Question

I have the following dataset:

timestamp   value

1           90

3           78

6           87

8           NA

12          98

15          100

18          NA

24          88

27          101

As you can see, the gaps between the consecutive timestamps are not equi-spaced. Is there a way to imputate values to replace the NA using a timestamp dependend method?

All packages I found are only suitable for equi-spaced time series... Thanks!

Answer 1

The zoo R package can be used to handle irregular spaced / unevenly spaced time series.

First you have to create a zoo ts object. You can either specify indices or use POSIXct timestamps.

Afterwards you can use a imputation method on this object. Zoo's imputation methods are limited, but they also work on irregular speced time series. You can use linear interpolation (na.approx) or spline interpolation (na.spline), which also account for the uneven time stamps.

# First create a unevenly spaced zoo time series object
# First vector with values, second with your indices
zoo_ts <- zoo(c(90,78,87,NA,98,100,NA,88,101), c(1, 3, 6,8,12,15,18,24,27))

# Perform the imputation
na.approx(zoo_ts)

Your zoo object looks like this:

>  1   3   6   8  12  15  18  24  27 
> 90  78  87  NA  98 100  NA  88 101 

Your imputed series like this afterwards:

> 1         3         6         8        12        15        18        24        27 
> 90.00000  78.00000  87.00000  90.66667  98.00000 100.00000  96.00000  88.00000 101.00000 

When you have time stamps and the series is only slightly / few seconds off for each time stamp, you could also try to transform the series into a regular time series by mapping your values to the correct regular intervals. (only reasonably if the differences are small). By doing this you could also use additional imputation methods eg by the imputeTS package (which only works for regular spaced data).