[R] ts or xts with high-frequency data within a year

[Bert Gunter]

TYPO on TYPO!

It should be X[,3]

Cheers,
Bert
Bert Gunter

"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )


On Thu, Mar 31, 2016 at 9:47 AM, Bert Gunter <bgunter.4567 at gmail.com> wrote:
> Inline.
>
> Bert Gunter
>
> "The trouble with having an open mind is that people keep coming along
> and sticking things into it."
> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
>
>
> On Wed, Mar 30, 2016 at 5:37 PM, Ryan Utz <utz.ryan at gmail.com> wrote:
>> Bill, Josh, and Bert,
>>
>> Thanks for your responses. I still can't quite get this when I use actual
>> dates. Here's an example of what is going wrong:
>>
>> X=as.data.frame(1:6000)
>> X[2]=seq.POSIXt(ISOdate(2015,11,1),by='hour',length.out=6000)
>> X[3]=sample(100,size=6000,replace=T)
>>
>> Y=xts(X[,3],order.by=X[,2])
>> decompose(Y)
>>
>> Z=ts(X[,2],frequency=24*365)
>> plot(decompose(Z))
>
> ## TYPO!  It should be X[,2].
>
> ***WARNING***
> I am not a time series expert. The remarks below are therefore subject
> to confirmation or correction by those who are. Caveat emptor!
>
> Also, you seem to be somewhat confused about how the seasonal
> decomposition in decompose() works.
>
> My understanding from what you said is that your unit of time is days
> and that you have samples every 15 minutes, but that you wish to
> estimate hourly effects. If this is correct, you first need to first
> combine (e.g. via by() ) your 4 observations into a single summary
> (e.g. average or median, maybe) so that you have an hourly time
> series. Run this through ts() with frequency = 24: your period is
> daily = 24 hours and you have 24 observations/period.
>
> (Note that you could use the original data to get 96 15 minute
> estimates instead of hourly estimates).
>
> When you run this through decompose(), it will give you 24 "seasonal"
> effects/period, the hourly effects. The "trend" component will try to
> remove longer term effects and trends over time.
>
> Note, however, this is probably **not** what you want. I suspect you
> want both hourly effects and daily or monthly effects to reflect
> annual seasonalities as well as daily. decompose() cannot do this,
> apparently, so you should look for an alternative solution. Better
> yet, consult with a local time series expert to help you figure out
> what you might want and how to get it in R.
>
> Cheers,
> Bert
>
>
>>
>> When I specify an actual date/time (rather than just a number as Bill
>> posited), it does not like anything short of a year. This seems like I'm
>> overlooking something obvious, but I can't get this for the life of me...
>>
>> Thanks for your time,
>> r
>>
>>
>> On Wed, Mar 30, 2016 at 1:03 PM, William Dunlap <wdunlap at tibco.com> wrote:
>>>
>>> You said you specified frequency=96 when you constructed the time
>>> series, but when I do that the decomposition looks reasonable:
>>>
>>> > time <- seq(0,9,by=1/96) # 15-minute intervals, assuming time unit is
>>> > day
>>> > measurement <- sqrt(time) + 1/(1.2+sin(time*2*pi)) +
>>> > rnorm(length(time),0,.3)
>>> > plot(decompose(ts(measurement, frequency=96)))
>>>
>>> How is your code different from the above?
>>>
>>>
>>>
>>> Bill Dunlap
>>> TIBCO Software
>>> wdunlap tibco.com
>>>
>>> On Wed, Mar 30, 2016 at 8:03 AM, Ryan Utz <utz.ryan at gmail.com> wrote:
>>>>
>>>> Hello,
>>>>
>>>> I have a time series that represents data sampled every 15-minutes. The
>>>> data currently run from November through February, 8623 total readings.
>>>> There are definitely daily periodic trends and non-stationary long-term
>>>> trends. I would love to decompose this using basic time series analysis.
>>>>
>>>> However, every time I attempt decomposition, I get the
>>>>
>>>> Error in decompose( ) : time series has no or less than 2 periods
>>>>
>>>> Is it only possible to do basic time-series analysis if you have a year
>>>> or
>>>> more worth of data? That seems absurd to me, since there is definite
>>>> periodicity and the data are a time series. I have tried every manner of
>>>> specifying frequency= with no luck (96 does not work). All manner of
>>>> searching for help has turned up fruitless.
>>>>
>>>> Can I only do this after I wait another year or two?
>>>>
>>>> Thanks,
>>>> Ryan
>>>>
>>>> --
>>>>
>>>> Ryan Utz, Ph.D.
>>>> Assistant professor of water resources
>>>> *chatham**UNIVERSITY*
>>>> Home/Cell: (724) 272-7769
>>>>
>>>>         [[alternative HTML version deleted]]
>>>>
>>>> ______________________________________________
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>>>> and provide commented, minimal, self-contained, reproducible code.
>>>
>>>
>>
>>
>>
>> --
>>
>> Ryan Utz, Ph.D.
>> Assistant professor of water resources
>> chathamUNIVERSITY
>> Home/Cell: (724) 272-7769
>>