On 30/10/14 21:33, Jim Lemon wrote:
> On Fri, 31 Oct 2014 07:19:01 AM Jim Lemon wrote:
>> On Wed, 29 Oct 2014 05:12:19 PM CJ Davies wrote:
>>> I am trying to show that the red line ('yaw') in the upper of the two
>>> plots here;
>>>
>>> http://i.imgur.com/N4Xxb4f.png
>>>
>>> varies more within the pink sections ('transition 1') than in the
> light
>>> blue sections ('real').
>>>
>>> I tried to use var.test() however this runs into a problem because
>>> although the red line doesn't vary much *within* any particular
> light
>>> blue section, it does vary a lot *between* light blue sections.
>>>
>>> For example, in the light blue section around t=90 the red line
>> doesn't
>>
>>> move much & likewise in the light blue section around t=160 the
>> red line
>>
>>> doesn't move much. But between these two sections the red line
>> has moved
>>
>>> substantially.
>>>
>>> So if I simply subset the data according to pink/light blue & then
> put
>>> those resultant subsets into var.test(), the answer does not show
>> the
>>
>>> relationship that I want it to.
>>>
>>> Can anybody shed some light on a sensible method of solving
> this?
>> Hi CJ,
>> If your dataset has the transition type coded for each observation:
>>
>> rotation transition
>> 90 blue
>> 90 blue
>> 115 pink
>> -10 pink
>> 30 green
>> ...
>>
>> you could aggregate all the observations within each transition type
>> and test that.
>>
>> Jim
>>
> Oops,
> What I meant was aggregate all the _deviations_ within each transition
> type.
>
> Jim
>
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If I understand, you mean to calculate deviations for each individual
'chunk' of each transition & then aggregate the results? This is what
I'd been thinking about, but is there a sensible manner within R to
achieve this, or is it something for which it would be easier to
preprocess the data in an external tool? Is there some way to subset the
data such that I can work over just contiguous 'chunks'?
Regards,
CJ Davies
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