Hi,
I have a data-matrix:
> CB
                  Zeit         Low
2Â Â 2011-05-02 08:05:05 7596.0
3Â Â 2011-05-02 08:10:06 7593.5
4Â Â 2011-05-02 08:15:11 7594.5
5Â Â 2011-05-02 08:20:15 7597.5
6Â Â 2011-05-02 08:25:18 7595.0
7Â Â 2011-05-02 08:30:20 7593.5
8Â Â 2011-05-02 08:35:21 7593.0
9Â Â 2011-05-02 08:40:21 7593.0
10Â 2011-05-02 08:45:25 7599.0
11Â 2011-05-02 08:50:34 7596.0
12Â 2011-05-02 08:55:59 7591.0
13Â 2011-05-02 09:01:00 7590.5
14Â 2011-05-02 09:06:00 7590.5
15Â 2011-05-02 09:11:04 7590.5
16Â 2011-05-02 09:16:04 7591.0
17Â 2011-05-02 09:21:06 7593.0
18Â 2011-05-02 09:26:08 7596.0
19Â 2011-05-02 09:31:09 7596.0
20Â 2011-05-02 09:36:10 7599.0
21Â 2011-05-02 09:41:11 7601.5
22Â 2011-05-02 09:46:11 7608.0
23Â 2011-05-02 09:51:18 7611.5
24Â 2011-05-02 09:56:20 7605.5
25Â 2011-05-02 10:01:20 7601.5
I want to approximate this data (actually I dont care, whether keep the
time information, or lose it, while making it a function)
With approxfun( ), it seems, like I managed to apprximate a function.
f <- approxfun(2:nrow(CB), CB[2:nrow(CB),2])
But how do I defferentiate f()?
g<-deriv(f(2:nrow(CB)),"x")
Did not work out for me, or at least, I dont know how to get those "x",
with g(x)=0.
My ultimate goal, is to find all the local minima of CB[,2]. (min() gives
only the global minimum)
Any suggestions how to do it?
Thanks for your help in advance.
Michael
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