MathGroup Archive 2002

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

Search the Archive

acsplines smoothing

  • To: mathgroup at
  • Subject: [mg33781] acsplines smoothing
  • From: "Mazin M.A." <mazin at>
  • Date: Tue, 16 Apr 2002 03:50:32 -0400 (EDT)
  • References: <a93b0m$phl$>
  • Sender: owner-wri-mathgroup at

Dear All,
Please, recommend me  the package  for smoothing experimental data.
It's necessary manually vary "degree" of smoothing - small at the
region of peak and high at the tails. The dimension list of data - from
2000 to 10000 points.
It's may be similarly "acsplines" from "GNUPLOT".  Below I adduce some
words from documentation on "GNUPLOT" ...
The `acsplines` option approximates the data with a "natural smoothing
After the data are made monotonic in x (see `smooth unique`), a curve is
constructed from segments of cubic polynomials whose coefficients are found
by the
weighting the data points; the weights are taken from the third column in
the data file.

Qualitatively, the absolute magnitude of the weights determines the number
of segments
used to construct the curve. If the weights are large, the effect of each
datum is large
and the curve approaches that produced by connecting consecutive points with
natural cubic
splines. If the weights are small, the curve is composed of fewer segments
and thus is
smoother; the limiting case is the single segment produced by a weighted
linear least
squares fit to all the data.



National Academy of Sciences of the Ukraine
Institute of Semiconductor Physics

Best regards,
Dr. Mikhail Mazin                          mailto:mazin at

Best regards,
 Dr. Mazin  M.                        mailto:mazin at

  • Prev by Date: Redefing a Numberedfigure-Style in a MyReport Style Sheet
  • Next by Date: Passing arguments and pattern matching
  • Previous by thread: Redefing a Numberedfigure-Style in a MyReport Style Sheet
  • Next by thread: Passing arguments and pattern matching