stl() decomposition won't accept univariate ts object?

r

Solution

I'm not 100% sure about what the exact cause of the problem is, but you can fix this by passing `dummyData$index` to `ts` instead of the entire object:

tsData2 <- ts(
  data=dummyData$index, 
  start = c(2012,1), 
  end = c(2014,12), 
  frequency = 12)
##
R>  stl(tsData2, s.window="periodic")
 Call:
 stl(x = tsData2, s.window = "periodic")

Components
            seasonal     trend   remainder
Jan 2012 -24.0219753  36.19189   9.8300831
Feb 2012 -20.2516062  37.82808   8.4235219
Mar 2012  -0.4812396  39.46428  -4.9830367
Apr 2012 -10.1034302  41.32047   1.7829612
May 2012   0.6077088  43.17666  -3.7843705
Jun 2012   4.4723800  45.22411 -10.6964877
Jul 2012  -7.6629462  47.27155  -0.6086074
Aug 2012  -1.0551286  49.50673  -3.4516016
Sep 2012   2.2193527  51.74191  -3.9612597
Oct 2012   7.3239448  55.27391  -4.5978509
Nov 2012  18.4285405  58.80591 -13.2344456
Dec 2012  30.5244146  63.70105 -16.2254684

`...`

I'm guessing that when you pass a `data.frame` to the `data` argument of `ts`, some extra attributes carry over, and although this generally doesn't seem to be an issue with many functions that take a `ts` class object (univariate or otherwise), apparently it is an issue for `stl`.

R>  all.equal(tsData2,tsData)
[1] "Attributes: < Names: 1 string mismatch >"                         
[2] "Attributes: < Length mismatch: comparison on first 2 components >"
[3] "Attributes: < Component 2: Numeric: lengths (3, 2) differ >"      
##
R>  str(tsData2)
 Time-Series [1:36] from 2012 to 2015: 22 26 34 33 40 39 39 45 50 58 ...
##
R>  str(tsData)
 'ts' int [1:36, 1] 22 26 34 33 40 39 39 45 50 58 ...
 - attr(*, "dimnames")=List of 2
  ..$ : NULL
  ..$ : chr "index"
 - attr(*, "tsp")= num [1:3] 2012 2015 12

Edit:

Looking into this a little further, I think the problem has to do with the `dimnames` attribute being carried over from the `dummyData` when it is passed as a whole. Note this excerpt from the body of `stl`:

if (is.matrix(x)) 
        stop("only univariate series are allowed")

and from the definition of `matrix`:

is.matrix returns TRUE if x is a vector and has a "dim" attribute of length 2) and FALSE otherwise

so although you are passing `stl` a univariate time series (the original `tsData`), as far as the function is concerned, a vector with a length 2 `dimnames` attribute (i.e. a `matrix`) is not a univariate series. It seems a little strange to do error handling in this way, but I'm sure the author of the function had a very good reason for this.

Problem

I'm have issues with stl() time series decomposition function in R telling me my ts object is not univariate when it actually is? ``` tsData <- ts(data = dummyData, start = c(2012,1), end = c(2014,12), frequency = 12) > tsData Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2012 22 26 34 33 40 39 39 45 50 58 64 78 2013 51 60 80 80 93 100 96 108 111 119 140 164 2014 103 112 154 135 156 170 146 156 166 176 193 204 > class(tsData) [1] "ts" > stl(tsData, s.window = "periodic") Error in stl(tsData, s.window = "periodic") : only univariate series are allowed > dput(dummyData) structure(list(index = c(22L, 26L, 34L, 33L, 40L, 39L, 39L, 45L, 50L, 58L, 64L, 78L, 51L, 60L, 80L, 80L, 93L, 100L, 96L, 108L, 111L, 119L, 140L, 164L, 103L, 112L, 154L, 135L, 156L, 170L, 146L, 156L, 166L, 176L, 193L, 204L)), .Names = "index", class = "data.frame", row.names = c(NA, -36L)) ``` Anyone know how to fix this issue?

Original source

Related problems