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Re: MPFIT parameter errors -0.00000 [message #75959] Thu, 12 May 2011 07:18
Eoj is currently offline  Eoj
Messages: 7
Registered: June 2010
Junior Member
Any suggestions on this?
Re: MPFIT parameter errors -0.00000 [message #75982 is a reply to message #75959] Tue, 10 May 2011 08:35 Go to previous message
Eoj is currently offline  Eoj
Messages: 7
Registered: June 2010
Junior Member
I did, they are identically zero, and should be in the neighborhood of
10^14 given the best fit values.
Re: MPFIT parameter errors -0.00000 [message #75987 is a reply to message #75982] Tue, 10 May 2011 02:11 Go to previous message
Gray is currently offline  Gray
Messages: 253
Registered: February 2010
Senior Member
On May 9, 4:35 pm, JoeM <josephmeir...@gmail.com> wrote:
> Hello,
>
>     I was wondering about something strange that seems to be going on
> with MPFIT in IDL. MPFIT seems to be working and producing a fine
> looking fit, but the errors on some of the parameters are identically
> -0.00000. These parameters are not limited or tied to anything at the
> moment, so they should be producing some parameter error. Output is
> attached below, MPFIT is ending with a "2" status. Any idea what is
> going on here? This only seems to happen for a specific data file, for
> other fits it seems to be working fine.
>
> Cheers,
> Joe
>
> IDL>
> % MPFIT: WARNING: data is DOUBLE but parameters are FLOAT
> % MPFIT:          (converting parameters to DOUBLE)
> Iter      1   CHI-SQUARE =       148.65044          DOF = 99
>     P(0) =          2.70126E+16
>     P(1) =          2.02481E+16
>     P(2) =              32.2569
>     P(3) =              37.7481
>     P(4) =          0.000100000
>     P(5) =              71.0903
>     P(6) =             0.273900
>     P(7) =             0.273900
>     P(8) =              930.748
>     P(9) =              930.748
> Iter      1   CHI-SQUARE =       148.65044          DOF = 99
>     P(0) =          2.70126E+16
>     P(1) =          2.02481E+16
>     P(2) =              32.2569
>     P(3) =              37.7481
>     P(4) =          0.000100000
>     P(5) =              71.0903
>     P(6) =             0.273900
>     P(7) =             0.273900
>     P(8) =              930.748
>     P(9) =              930.748
>
>       STATUS
>       2
>
>       PERROR
>      -0.00000     -0.00000     0.492911      1.38439      0.00000
> 0.930223      0.00000
>       0.00000      0.00000      0.00000

Try printing out PERROR with more digits.
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