[R] Recognizing patterns in time series data

[PIKAL Petr]

Hi

I am not able to see the picture but from what you write maybe you can consult

?strucchange or ?segmented packages

Regards
Petr

> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
> project.org] On Behalf Of James Courtier-Dutton
> Sent: Friday, February 28, 2014 11:00 AM
> To: r-help at r-project.org
> Subject: [R] Recognizing patterns in time series data
>
> See the attached picture.
> http://imagebin.org/296311
>
> It shows the temperature of a water pipe in a heating system.
> Notice the up/down/up/down bit. This is the boiler turning on and off
> again to keep the water at a particular temperature.
> Are there any R libs/modules that would help me recognizing patterns
> like this in graphs?
> I have looked through the various R libs/modules and found lots of
> statistical analysis tools, but I want pattern recognition and not
> statistical tests.
>
> I.e. So I can tell when the boiler was fired up, and when it was
> waiting.
> I also want to use to graph to estimate how much time the boiler was
> actually lit and heating water, to get an idea regarding gas usage, and
> then compare that to the gas meter for calibration purposes.
> I would also like to recognize other features of the graph, like any
> unexpected changes in temperature, due to someone running a hot tap
> etc.
>
> For those interested, I have made my own heating/hot water controller
> and monitoring setup with an arduino, DS18B20 digital temp sensors, and
> relays for switching values on/off and sending "call for heat" to the
> boiler.
> The graph is the output from one of the DS18B20 one wire temp sensors.
> For safety, I am not connecting anything to the boiler circuitry
> itself, so this is why I wish to infer what the boiler is doing from
> the temp sensor graphs.
>
> I could probably work out some algorithms myself, but if a tool (R
> lib/module) already exists, I will use that.
>
> Kind Regards
>
> James
>
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> PLEASE do read the posting guide http://www.R-project.org/posting-
> guide.html
> and provide commented, minimal, self-contained, reproducible code.

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