R Graphical Manual

Last data update: 2014.03.03

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Results 1 - 3 of 3 found.
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DNAtools : Tools for analysing forensic genetic DNA data

Package: DNAtools
Type: Package
Title: Tools for analysing forensic genetic DNA data
Version: 0.1-21
Date: 2014-09-03
Author: Torben Tvedebrink <tvede@math.aau.dk> and James Curran <j.curran@auckland.ac.nz>. Mikkel Meyer Andersen <mikl@math.aau.dk> assisted on the multicore/CPU implementation.
Maintainer: Torben Tvedebrink <tvede@math.aau.dk>
Description: Computationally efficient tools for comparing all pairs of profiles in a DNA database. The expectation and covariance of the summary statistic
is implemented for fast computing. Routines for estimating proportions of close related individuals are available. The use of wildcards (also
called F-designation) is implemented. Dedicated functions ease plotting the results.
License: GPL (>= 2)
Depends: R (>= 2.10.0), Rsolnp, multicool
Imports: Rcpp (>= 0.11.2)
LinkingTo: Rcpp
Packaged: 2014-09-03 09:25:02 UTC; tvede
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2014-09-03 18:07:11

● Data Source: CranContrib
● 0 images, 19 functions, 0 datasets
● Reverse Depends: 0

SIDES : Subgroup Identification Based on Differential Effect Search

Package: SIDES
Type: Package
Title: Subgroup Identification Based on Differential Effect Search
Version: 1.0
Date: 2016-05-09
Author: Marie-Karelle Riviere
Maintainer: Marie-Karelle Riviere <eldamjh@gmail.com>
Copyright: All files are copyright Sanofi Aventis
Description: Provides function to apply "Subgroup Identification based on Differential Effect Search" (SIDES) method proposed by Lipkovich et al. (2011) <doi:10.1002/sim.4289>.
License: GPL-3
Depends: R (>= 3.1.2), memoise (>= 1.0.0), doParallel (>= 1.0.10),
foreach (>= 1.4.3), nnet (>= 7.3-12), multicool (>= 0.1-9)
LinkingTo:
Packaged: 2016-06-01 14:33:27 UTC; I0273717
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2016-06-02 06:10:10

● Data Source: CranContrib
● 0 images, 3 functions, 0 datasets
● Reverse Depends: 0

hpcwld : High Performance Cluster Models Based on Kiefer-Wolfowitz Recursion

Package: hpcwld
Version: 0.5
Date: 2015-02-14
Title: High Performance Cluster Models Based on Kiefer-Wolfowitz
Recursion
Authors@R: c(person("Alexander", "Rumyantsev", role = c("aut", "cre"),
email = "ar0@sampo.ru"))
Depends: R (>= 2.10), multicool, partitions
Description: Probabilistic models describing the behavior
of workload and queue on a High Performance Cluster and computing GRID
under FIFO service discipline basing on modified Kiefer-Wolfowitz
recursion. Also sample data for inter-arrival times, service times,
number of cores per task and waiting times of HPC of Karelian
Research Centre are included, measurements took place from 06/03/2009 to 02/30/2011.
Functions provided to import/export workload traces in Standard Workload Format (swf).
Stability condition of the model may be verified either exactly, or approximately.
License: GPL (>= 2)
URL: http://www.r-project.org
Author: Alexander Rumyantsev [aut, cre]
Maintainer: Alexander Rumyantsev <ar0@sampo.ru>
Repository: CRAN
Repository/R-Forge/Project: hpcwld
Repository/R-Forge/Revision: 11
Repository/R-Forge/DateTimeStamp: 2015-02-17 14:13:21
Date/Publication: 2015-02-17 19:32:19
Packaged: 2015-02-17 14:25:24 UTC; rforge
NeedsCompilation: no

● Data Source: CranContrib
● 0 images, 8 functions, 3 datasets
● Reverse Depends: 0