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Paul

2015-Apr-20 23:04 UTC

[R] How numerical data is stored inside ts time series objects

I'm getting familiar with the stl function in the stats packcage by
trying it on an example from Brockwell & Davis's 2002 "Introduction
to
Times Series and Forcasting".  Specifically, I'm using a subset of his
red wine sales data.  It's a detour from the stl material at
http://www.stat.pitt.edu/stoffer/tsa3/R_toot.htm (at some point, I
have to stop simply following and try to make it work with new data).

I need a minimum of 36 wine sales data points in the series, since stl
otherwise complains about the data being less than 2 cycles.  The data
is in ~/tmp/wine.txt:

    464
    675
    703
    887
    1139
    1077
    1318
    1260
    1120
    963
    996
    960
    530
    883
    894
    1045
    1199
    1287
    1565
    1577
    1076
    918
    1008
    1063
    544
    635
    804
    980
    1018
    1064
    1404
    1286
    1104
    999
    996
    1015

My sourced test code is buried in a repeat loop so that I can use a
break command to circumvent the final error-causing statement that I'm
trying to figure out:

    repeat{

        # Clear variables (from stackexchange)
        rm( list=setdiff( ls( all.names=TRUE ), lsf.str(all.names=TRUE ) ) )
        ls()

        head( wine <- read.table("~/tmp/wine.txt") )
        ( x <- ts(wine[[1]],frequency=12) )
        ( y <- ts(wine,frequency=12) )
        ( a=stl(x,"per") )
        #break
        ( b=stl(y,"per") )
    }

The final statement causes the error 'Error in stl(y, "per") :
only
univariate series are allowed'.  I found an explanation at
http://stackoverflow.com/questions/10492155/time-series-and-stl-in-r-error-
only-univariate-series-are-allowed.
That's how I came up with the assignment to x using wine[[1]].  I
found an explanation to the need for
double square brackets at
http://www.r-tutor.com/r-introduction/list/named-list-members.

My problem is that it's not very clear what is happening inside the ts
structures x and y.  If I simply print them, they look 100% identical:

    | > x
    |    Jan  Feb  Mar  Apr  May  Jun  Jul  Aug  Sep  Oct  Nov  Dec
    | 1  464  675  703  887 1139 1077 1318 1260 1120  963  996  960
    | 2  530  883  894 1045 1199 1287 1565 1577 1076  918 1008 1063
    | 3  544  635  804  980 1018 1064 1404 1286 1104  999  996 1015
    | > y
    |    Jan  Feb  Mar  Apr  May  Jun  Jul  Aug  Sep  Oct  Nov  Dec
    | 1  464  675  703  887 1139 1077 1318 1260 1120  963  996  960
    | 2  530  883  894 1045 1199 1287 1565 1577 1076  918 1008 1063
    | 3  544  635  804  980 1018 1064 1404 1286 1104  999  996 1015

Whatever their differences, it's not causing R to misinterpret the
data; that is, they each look like in single series of numerical data.

Can anyone illuminate the difference in the data inside the ts data
structures?  The potential incompatibility with stl is just one
symptom.  Right now, the "solution" is black magic to me, and I would
like to get a clearer picture so that I know when else (and how) to
watch out for this.

I've posted this to the R Help mailing list
http://news.gmane.org/gmane.comp.lang.r.general and to stackoverflow
at
http://stackoverflow.com/questions/29759928/how-numerical-data-is-stored-
inside-ts-time-series-objects.

William Dunlap

2015-Apr-21 00:00 UTC

head link

[R] How numerical data is stored inside ts time series objects

Use the str() function to see the internal structure of most objects.  In
your case it would show something like:
> Data <- data.frame(theData=round(sin(1:38),1))
> x <- ts(Data[[1]], frequency=12) # or Data[,1]
> y <- ts(Data, frequency=12)
> str(x) Time-Series [1:38] from 1 to 4.08: 0.8 0.9 0.1 -0.8 -1 -0.3 0.7 1 0.4 -0.5
...> str(y) ts [1:38, 1] 0.8 0.9 0.1 -0.8 -1 -0.3 0.7 1 0.4 -0.5 ...
 - attr(*, "dimnames")=List of 2
  ..$ : NULL
  ..$ : chr "theData"
 - attr(*, "tsp")= num [1:3] 1 4.08 12

'x' contains a vector of data and 'y' contains a 1-column matrix
of data.
stl(x,"per") and stl(y, "per") give similar results as you
got.

Evidently, stl() does not know that 1-column matrices can be treated much
the same as vectors and gives an error message.  Thus you must extract
the one column into a vector: stl(y[,1], "per").




Bill Dunlap
TIBCO Software
wdunlap tibco.com

On Mon, Apr 20, 2015 at 4:04 PM, Paul <Paul.Domaskis at gmail.com> wrote:
> I'm getting familiar with the stl function in the stats packcage by
> trying it on an example from Brockwell & Davis's 2002
"Introduction to
> Times Series and Forcasting".  Specifically, I'm using a subset of
his
> red wine sales data.  It's a detour from the stl material at
> http://www.stat.pitt.edu/stoffer/tsa3/R_toot.htm (at some point, I
> have to stop simply following and try to make it work with new data).
>
> I need a minimum of 36 wine sales data points in the series, since stl
> otherwise complains about the data being less than 2 cycles.  The data
> is in ~/tmp/wine.txt:
>
>     464
>     675
>     703
>     887
>     1139
>     1077
>     1318
>     1260
>     1120
>     963
>     996
>     960
>     530
>     883
>     894
>     1045
>     1199
>     1287
>     1565
>     1577
>     1076
>     918
>     1008
>     1063
>     544
>     635
>     804
>     980
>     1018
>     1064
>     1404
>     1286
>     1104
>     999
>     996
>     1015
>
> My sourced test code is buried in a repeat loop so that I can use a
> break command to circumvent the final error-causing statement that I'm
> trying to figure out:
>
>     repeat{
>
>         # Clear variables (from stackexchange)
>         rm( list=setdiff( ls( all.names=TRUE ), lsf.str(all.names=TRUE ) )
> )
>         ls()
>
>         head( wine <- read.table("~/tmp/wine.txt") )
>         ( x <- ts(wine[[1]],frequency=12) )
>         ( y <- ts(wine,frequency=12) )
>         ( a=stl(x,"per") )
>         #break
>         ( b=stl(y,"per") )
>     }
>
> The final statement causes the error 'Error in stl(y, "per")
: only
> univariate series are allowed'.  I found an explanation at
> http://stackoverflow.com/questions/10492155/time-series-and-stl-in-r-error-
> only-univariate-series-are-allowed.
> That's how I came up with the assignment to x using wine[[1]].  I
> found an explanation to the need for
> double square brackets at
> http://www.r-tutor.com/r-introduction/list/named-list-members.
>
> My problem is that it's not very clear what is happening inside the ts
> structures x and y.  If I simply print them, they look 100% identical:
>
>     | > x
>     |    Jan  Feb  Mar  Apr  May  Jun  Jul  Aug  Sep  Oct  Nov  Dec
>     | 1  464  675  703  887 1139 1077 1318 1260 1120  963  996  960
>     | 2  530  883  894 1045 1199 1287 1565 1577 1076  918 1008 1063
>     | 3  544  635  804  980 1018 1064 1404 1286 1104  999  996 1015
>     | > y
>     |    Jan  Feb  Mar  Apr  May  Jun  Jul  Aug  Sep  Oct  Nov  Dec
>     | 1  464  675  703  887 1139 1077 1318 1260 1120  963  996  960
>     | 2  530  883  894 1045 1199 1287 1565 1577 1076  918 1008 1063
>     | 3  544  635  804  980 1018 1064 1404 1286 1104  999  996 1015
>
> Whatever their differences, it's not causing R to misinterpret the
> data; that is, they each look like in single series of numerical data.
>
> Can anyone illuminate the difference in the data inside the ts data
> structures?  The potential incompatibility with stl is just one
> symptom.  Right now, the "solution" is black magic to me, and I
would
> like to get a clearer picture so that I know when else (and how) to
> watch out for this.
>
> I've posted this to the R Help mailing list
> http://news.gmane.org/gmane.comp.lang.r.general and to stackoverflow
> at
> http://stackoverflow.com/questions/29759928/how-numerical-data-is-stored-
> inside-ts-time-series-objects.
>
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
	[[alternative HTML version deleted]]

Paul

2015-Apr-22 01:39 UTC

head link

[R] How numerical data is stored inside ts time series objects

William Dunlap <wdunlap <at> tibco.com>
writes:> Use the str() function to see the internal structure of most
> objects.  In your case it would show something like:
>
> > Data <- data.frame(theData=round(sin(1:38),1))
> > x <- ts(Data[[1]], frequency=12) # or Data[,1]
> > y <- ts(Data, frequency=12)
> > str(x)
>  Time-Series [1:38] from 1 to 4.08: 0.8 0.9 0.1 -0.8 -1 -0.3 0.7 1 0.4 -
0.5> ...
> > str(y)
>  ts [1:38, 1] 0.8 0.9 0.1 -0.8 -1 -0.3 0.7 1 0.4 -0.5 ...
>  - attr(*, "dimnames")=List of 2
>   ..$ : NULL
>   ..$ : chr "theData"
>  - attr(*, "tsp")= num [1:3] 1 4.08 12
>
> 'x' contains a vector of data and 'y' contains a 1-column
matrix of
> data.  stl(x,"per") and stl(y, "per") give similar
results as you
> got.
>
> Evidently, stl() does not know that 1-column matrices can be treated
> much the same as vectors and gives an error message.  Thus you must
> extract the one column into a vector: stl(y[,1], "per").
Thanks, William.

Interesting that a 2D matrix of size Nx1 is treated as a different
animal from a length N vector.  It's a departure from math convention,
and from what I'm accustomed to in Matlab.  that R's vector seems
more akin to a list, where the notion of orientation doesn't apply.

I rummaged around the help files for str, summary, dput, args.  This
seems like a more complicated language than Matlab, VBA, or even C++'s
STL of old (which was pretty thoroughly documented).  A function like
str() returns an object description, and I'm guessing the conventions
with which the object is described depends a lot on the person who
wrote the handling code for the class.  The description for the
variable y seems particularly elaborate.

Would I be right in assuming that the notation is ad-hoc and not
documented?  For example, the two invocations str(x) and str(y) show a
Time-Series and a ts.  And there are many lines of output for str(y)
that is heavy in punctuation.

R help - Apr 2015 - How numerical data is stored inside ts time series objects

[R] How numerical data is stored inside ts time series objects

[R] How numerical data is stored inside ts time series objects

[R] How numerical data is stored inside ts time series objects