Services & Resources / Wolfram Forums / MathGroup Archive
-----

MathGroup Archive 2012

[Date Index] [Thread Index] [Author Index]

Search the Archive

Re: Derivative of experimental data

  • To: mathgroup at smc.vnet.net
  • Subject: [mg124744] Re: Derivative of experimental data
  • From: Ingolf Dahl <ingolf.dahl at telia.com>
  • Date: Sat, 4 Feb 2012 06:26:05 -0500 (EST)
  • Delivered-to: l-mathgroup@mail-archive0.wolfram.com
  • References: <201202010848.DAA15135@smc.vnet.net>

Yet another method:
Download my "Obtuse" interpolation package from
http://www.familydahl.se/mathematica and 
Use the Interpolation functions with the options 
Method -> "ObtuseAngle", InterpolationOrder -> 2, NeighborLevel -> 3 
or 
Method -> "ObtuseAngle", InterpolationOrder -> 2, SmoothenDistance -> 0.2

See examples below "options" on the help page
http://www.familydahl.se/mathematica/Obtuse/ref/InterpolationMethodObtuseAng
le.html 

Best regards

Ingolf Dahl
Sweden

> -----Original Message-----
> From: Gabriel Landi [mailto:gtlandi at gmail.com]
> Sent: den 1 februari 2012 09:48
> To: mathgroup at smc.vnet.net
> Subject: Derivative of experimental data
> 
> Dear MathGroup users,
> 
> I have a question which is very important for my current research, and
which involves not
> only Mathematica, but computer science in general.
> 
> I have experimental data which is not very noisy, a small example of which
may be
> downloaded here.
> 
> Basically I need to compute the derivative of this data. Here are my
options so far:
> 
> Option 1: Finite differencing. Its terrible since the noise enhances
dramatically.
> Option 2: Fitting some arbitrary function. The problem is that the general
functional form of
> the data changes from experiment to experiment, so it is not possible to
find a function
> which fits adequately in all cases.
> Option 3: Savitzky-Golay filters (self-implemented in Mathematica, based
on the discussion
> in Numerical Recipes, 3rd Ed.). It doesn't seem to make much of a
difference; probably
> because my data is not really that noisy.
> Option 4: Smoothing Splines filter. I am currently using Mr. Ludsteck
package HPFilter. So
> far it is by far the best outcome. However, it is not free of some wild
oscillations that are
> clearly non-analytical and which are giving me quite the headache.
> 
> Any suggestions are more than welcome.
> I really appreciate any help I can get.
> 
> Best regards,
> 
> Gabriel Landi




  • Prev by Date: PDE with RecurrenceTable
  • Next by Date: Re: Funny Behavior of Module
  • Previous by thread: Re: Derivative of experimental data
  • Next by thread: Re: Derivative of experimental data