Doing chi square and/or lognormal fits to 1D data? [message #49410] |
Sun, 23 July 2006 14:55  |
swingnut
Messages: 30 Registered: September 2005
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I'm trying to analyze several collections of power law fits. Previous
work implies that the constants and coefficients of these power laws
are lognormal and that the exponents are chi square with 2 degrees of
freedom. We haven't been able to get ahold of the person who did that
previous work for over a year, but the new data I have looks like it
follows the same pattern. It is possible that he did his analysis in
Matlab, but really we have no idea what he used.
I've searched the web and combed through lots of libaries, usenet
posts, webpages, etc, but as far as I can tell, no one has built what I
need: drop-in IDL routines that would let me do lognormal and/or chi
square fits to data. mpfit (and PAN) looked promising, but according to
the documentation they require 2D data to fit to (i.e., they require
X-Y pairs), whereas I only have 1D data (the Y half of each pair). I'm
not trying to find a dependence on some value; rather, I am trying to
find an approximation of the distribution these values could have been
drawn from.
Do you all have any suggestions? I could kludge the lognormal analyses
in SASS and just overplot a histogram of the data with a lognormal
using the parameters it spits out. I'm ok with that for my work, but
I'm trying to set up a system that is mostly automated for future
students (e.g., my advisor's new student, who made it clear she is not
a coder of any sort).
The chi square fit, well, there's plenty of routines to do a
goodness-of-fit test, but I didn't find any at all, not even any
references that this project or that project has code to do it. Has
anyone heard of an IDL routine for this?
Thanks for the help.
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