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History of commit frequency

CVS Commit History:


   2012-09-29 02:50:33 by Aleksej Saushev | Files touched by this commit (158)
Log message:
Drop superfluous PKG_DESTDIR_SUPPORT, "user-destdir" is default these days.
Mark packages that don't or might probably not have staged installation.
   2010-06-14 00:46:55 by Thomas Klausner | Files touched by this commit (271) | Package updated
Log message:
Bump PKGREVISION for libpng shlib name change.
Also add some patches to remove use of deprecated symbols and fix other
problems when looking for or compiling against libpng-1.4.x.
   2010-01-18 10:38:16 by Thomas Klausner | Files touched by this commit (204)
Log message:
Second try at recursive PKGREVISION bump for jpeg shlib major bump (jpeg-8).
   2006-09-09 04:49:32 by OBATA Akio | Files touched by this commit (37)
Log message:
Rename variable MAKEFILE to MAKE_FILE.
   2005-11-03 11:48:48 by Roland Illig | Files touched by this commit (1)
Log message:
Fixed CATEGORIES.
   2005-08-22 22:32:28 by Mahesh Chittur | Files touched by this commit (1) | Package updated
Log message:
updated gstat distinfo checksum
   2005-04-11 23:12:36 by Todd Vierling | Files touched by this commit (1)
Log message:
Remove USE_BUILDLINK3 and NO_BUILDLINK; these are no longer used.

   2004-11-19 20:23:32 by David | Files touched by this commit (5) | Imported package
Log message:
Gstat is a program for the modelling, prediction and simulation ofgeostatistical \ 
data in one, two or three dimensions.  Geostatistical data are data \ 
(measurements) collected at known locations in space,from a function (process) \ 
that has a value at every location in a certain (1, 2 or 3-D) domain. These data \ 
(or some transform of them)are modelled as the sum of a constant or varying \ 
trend and a spatially correlated residual. Given a model for the trend, and \ 
under somestationarity assumptions, geostatistical modelling involves the \ 
estimation of the spatial correlation. Geostatistical prediction('kriging') is \ 
finding the best linear unbiased prediction (the expected value) with its \ 
prediction error for a variable at a location, given observations and a model \ 
for their spatial variation. Simulation of a spatial variable is the creation of \ 
randomly drawn realizations of a field given a model 
 for the data,possibly conditioned on observations.


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