| Name : R-PP3
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| Version : 1.2
| Vendor : obs://build_opensuse_org/devel:languages:R
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| Release : lp153.2.13
| Date : 2024-06-14 11:03:20
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| Group : Development/Libraries/Other
| Source RPM : R-PP3-1.2-lp153.2.13.src.rpm
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| Size : 0.13 MB
| |
| Packager : (none)
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| Summary : Three-Dimensional Exploratory Projection Pursuit
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Description :
Exploratory projection pursuit is a method to discovers structure in
multivariate data. At heart this package uses a projection index to
evaluate how interesting a specific three-dimensional projection of
multivariate data (with more than three dimensions) is. Typically, the
main structure finding algorithm starts at a random projection and then
iteratively changes the projection direction to move to a more
interesting one. In other words, the projection index is maximised over
the projection direction to find the most interesting projection. This
maximum is, though, a local maximum. So, this code has the ability to
restart the algorithm from many different starting positions
automatically. Routines exist to plot a density estimate of projection
indices over the runs, this enables the user to obtain an idea of the
distribution of the projection indices, and, hence, which ones might be
interesting. Individual projection solutions, including those
identified as interesting, can be extracted and plotted individually.
The package can make use of the mclapply() function to execute multiple
runs in parallel to speed up index discovery. Projection pursuit is
similar to independent component analysis. This package uses a
projection index that maximises an entropy measure to look for
projections that exhibit non-normality, and operates on sphered data.
Hence, information from this package is different from that obtained
from principal components analysis, but the rationale behind both
methods is similar. Nason, G. P. (1995) < doi:10.2307/2986135>.
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RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
