Group Fit ( where described )

Group Fit ( where described )

Post by John vanVlaandere » Sat, 24 Jan 1998 04:00:00

Hi All,

I am a statistical newbie but since my business is systems performance I
am taking the risky step of being smarter than my boss and applying
formulae, often translated to perl, to my collected data.

I would be most grateful if you could point me either to 3.6 stuff or
other sources that might help.  So far I am relying on exceptions from
threshold triggers, using linear regression and expn smooting for
forecasting.  These have their problems though, because systems are
fraught with outliers, and these are actully important.

The hugeness of this type of data and streaming batch requirements (a
contradiction) preclude any $1K+ packages entering the picture.  Every
thing has to be written in perl.

Any clues would by most helpful, thanks in advance.

Yours, John van V.

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1. group fit

gnuplot has a concept of a multi-data-set file, but it has no concept
of a multi-file data set -- all of the data to be treated as a single
data set must be in the same file.

You don't necessarily need to save the all-data file ... if your system
supports redirection, you might be able to do everything from within
gnuplot.  In Unix, for example, if you want to fit all the data in files
named "datafile.nnn", you could use
    fit f(x,a1) '< cat datafile.*'

If your files aren't named in a convenient way or you need to pull different
columns from different files, you could write a little program that extracts
the data and writes it to STDOUT and then run it from within the datfile
field in the same way.

I don't know if this helps ...

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