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[Octave-bug-tracker] [bug #38063] optim: expfit inaccurate (incorrect)
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From: |
Muhali |
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Subject: |
[Octave-bug-tracker] [bug #38063] optim: expfit inaccurate (incorrect) |
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Date: |
Wed, 10 Apr 2013 06:27:20 +0000 |
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User-agent: |
Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:20.0) Gecko/20100101 Firefox/20.0 |
Follow-up Comment #8, bug #38063 (project octave):
>> Can we get someone to run some expfit test cases in Matlab and compare
results?
expfit in ML is about the 1-parameter exponential distribution, a*exp(a*x),
unlike expfit in octave.
prony in ML is about impulse response functions, and I have the impression
that is what the current expfit actually does.
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