Robert,
Thanks
for asking. I'm getting a little help from Gabor on the use of zoo, and
will eventually learn how to code the things I want. The R core is
really neat in that what would be 50 tangled lines of code in lisp
are simple short expressions in R. That, however, means learning lots
and lots of objects and functions with complex properties and no good
reference. It really is a sophisticated environment requiring high level
user knowledge. Like I looked and looked tonight to find out how to
print one graph on top of another, or open multiple graph windows.
Couldn't find it.
My
other problem is the one that had me writing my own entire software interface
and analytic routines in the first place. I seem to be using curves for a
different purpose than other people. Say you have
a time-series of measures that reflect the life history of several
independent overlapping natural feedback loop systems, each with their own
separate growth, climax, disordering and decay periods. ¸¸¸¸.·´ ¯ `·.¸¸¸¸ You wouldn't want your way of
rendering the record of those events to erase all that critical beginning and
ending information, and paint the whole history with shapes displaying the same
wiggly but basically uneventful dynamics throughout. That would make the
underlying systems much harder to find and figure
out.
That's what I think splines do, for example, hide all
the natural system beginning and ending periods.
It may not be impossible to use splines to faithfully represent underlying
dynamics, but only the rendering philosophy of their designers.
Of course stochastic and simple differential equations are much
worse. On the other hand, I don't know all the kinds of
non-parametric methods of rendering histories of events, but I get no hint from
the discussion that anyone is aware of this problem. I can't find
anyone who seems to be using the shapes of their curves as a way of identifying
and investigating the behavior of natural feedback loop systems.
Everyone still seems to be treating nature as if it should be
following some formula, instead of rendering events as part of local
systems development.
Do you
know of anyone else with this complaint?
Phil Henshaw ¸¸¸¸.·´ ¯ `·.¸¸¸¸
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-----Original Message-----Exactly what you want to do with these different timescales? If it's just a case of sticking two lines on the same graph, that's simple. If it's some multi-temporal statistic (is there such a thing?) that you know of but isn't in R, then just code it up as an R function.
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Robert Holmes
Sent: Sunday, September 24, 2006 7:15 PM
To: The Friday Morning Applied Complexity Coffee Group
Subject: Re: [FRIAM] R tutorial for idiots.
Can you give us clarification? What are the statistic/statistics you want to calculate to compare your time-series?
Robert
On 9/23/06, Phil Henshaw <[EMAIL PROTECTED]> wrote:Who would guess just asking the R help forum would turn up a grad med student whose PhD in modeling time series of epidemics with R, living around the corner! I guess I'm now officially one small step up from rank beginner... Anyway, it doesn't appear that R makes it at all easy to use data with arbitrary time scales, however, which is disappointing. I just want a graphing database that other systems researchers use that treats time as a real number. Is that too much to ask?? R's time-series objects appear to require orderly data with points at constant time periods, and can't relate to others with different periods... My data and issues tend to fail on both counts!The session did give me a whole bunch of names of other people working on non-parametric data imaging, so I'll bet someone somewhere deals directly with the underlying problem, i.e. that life most certainly happens, but just not on schedule! I've gotten more than a couple great suggestions on FRIAM! Any others?
Phil Henshaw ¸¸¸¸.·´ ¯ `·.¸¸¸¸
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