R Development Page
Contributed R Packages
Below is a list of all packages provided by project Rigorous Analytics.
Important note for package
binaries: R-Forge provides these binaries only for
the most recent version of R, but not for older
versions. In order to successfully install the
packages provided on R-Forge, you have to switch
to the most recent version of R or, alternatively,
install from the package sources (.tar.gz).
dpmixsim | Dirichlet Process Mixture model simulation for clustering and image segmentation
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The package implements a Dirichlet Process Mixture (DPM) model for clustering and image segmentation.
The DPM model is a Bayesian nonparametric methodology that relies on MCMC simulations for exploring mixture models with an unknown number of components.
The code implements conjugate models with normal structure (conjugate normal-normal DP mixture model).
The packages applications are oriented towards the classification of magnetic resonance images according to tissue type or region of interest. |
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Version: 0.0-5 |
Last change: 2010-11-22 22:32:19+01 |
Rev.: 142 |
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Download:
(.tar.gz) |
(.zip) |
Build status: Current | Stable Release: Get dpmixsim 0.0-9 from CRAN |
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R install command:
install.packages("dpmixsim", repos="http://R-Forge.R-project.org") |
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oro.asl | Rigorous - Aterial Spin Labelling
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Medical imaging processing, visualization and statistical
methods for arterial spin labelling (ASL) acquisitions, part of the
Rigorous Analytics bundle. |
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Version: 0.1.0 |
Last change: 2011-02-04 12:57:55+01 |
Rev.: 169 |
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Download:
(.tar.gz) |
(.zip) |
Build status: Current |
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R install command:
install.packages("oro.asl", repos="http://R-Forge.R-project.org") |
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oro.dicom | Rigorous - DICOM Input / Output
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Data input/output functions for data that conform to the
Digital Imaging and Communications in Medicine (DICOM) standard, part
of the Rigorous Analytics bundle. |
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Version: 0.4.3 |
Last change: 2015-01-17 17:01:05+01 |
Rev.: 345 |
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Download:
(.tar.gz) |
(.zip) |
Build status: Current | Stable Release: Get oro.dicom 0.5.3 from CRAN |
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R install command:
install.packages("oro.dicom", repos="http://R-Forge.R-project.org") |
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oro.dti | Rigorous - Diffusion Tensor Imaging
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Medical imaging processing, visualization and statistical
methods for diffusion tensor imaging (DTI) acquisitions, part of the
Rigorous Analytics bundle. |
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Version: 0.1.0 |
Last change: 2010-11-25 16:17:42+01 |
Rev.: 146 |
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Download:
(.tar.gz) |
(.zip) |
Build status: Current |
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R install command:
install.packages("oro.dti", repos="http://R-Forge.R-project.org") |
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oro.nifti | Rigorous - NIfTI+ANALYZE+AFNI Input / Output
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Functions for the input/output and visualization of
medical imaging data that follow either the ANALYZE, NIfTI or AFNI
formats. This package is part of the Rigorous Analytics bundle. |
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Version: 0.4.3 |
Last change: 2015-01-18 14:43:17+01 |
Rev.: 346 |
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Download:
(.tar.gz) |
(.zip) |
Build status: Current | Stable Release: Get oro.nifti 0.9.1 from CRAN |
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R install command:
install.packages("oro.nifti", repos="http://R-Forge.R-project.org") |
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oro.pet | Rigorous - Positron Emission Tomography
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Image analysis techniques for positron emission tomography
(PET) that form part of the Rigorous Analytics bundle. |
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Version: 0.2.4 |
Last change: 2015-01-18 14:51:35+01 |
Rev.: 347 |
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Download:
(.tar.gz) |
(.zip) |
Build status: Current | Stable Release: Get oro.pet 0.2.7 from CRAN |
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R install command:
install.packages("oro.pet", repos="http://R-Forge.R-project.org") |
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qaqc | Quality Assurance and Quality Control Procedures for DICOM Data
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The application of quality assurance and quality control
(QAQC) procedures to both header and image components of the
Digital Imaging and Communications in Medicine (DICOM) standard. |
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Version: 0.1.4 |
Last change: 2011-12-08 13:05:09+01 |
Rev.: 241 |
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Download:
(.tar.gz) |
(.zip) |
Build status: Current |
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R install command:
install.packages("qaqc", repos="http://R-Forge.R-project.org") |
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Build status codes
0 - Current: the package is available for download. The corresponding package passed checks on the Linux and Windows platform without ERRORs.
1 - Scheduled for build: the package has been recognized by the build system and provided in the staging area.
2 - Building: the package has been sent to the build machines. It will be built and checked using the latest patched version of R. Note that it is included in a batch of several packages. Thus, this process will take some time to finish.
3 - Failed to build: the package failed to build or did not pass the checks on the Linux and/or Windows platform. It is not made available since it does not meet the policies.
4 - Conflicts: two or more packages of the same name exist. None of them will be built. Maintainers are asked to negotiate further actions.
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