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R-disposables-1.0.3-1.lbn25.noarch
Create disposable R packages for testing. You can create, install and load
multiple R packages with a single function call, and then unload,
uninstall and destroy them with another function call. This is handy when
testing how some R code or an R package behaves with respect to other
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R-evaluate-0.10.1-6.lbn25.noarch
Parsing and evaluation tools that make it easy to recreate the command
line behaviour of R.
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R-expm-0.999.2-5.lbn25.x86_64
Efficient calculation of the exponential of a matrix. The package
contains an R interface and a C API that package authors can use.
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R-expm-0.999.2-5.lbn25.x86_64
Efficient calculation of the exponential of a matrix. The package
contains an R interface and a C API that package authors can use.
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R-fastmatch-1.1.0-1.lbn25.x86_64
Package providing a fast match() replacement for cases that require
repeated look-ups. It is slightly faster that R's built-in match()
function on first match against a table, but extremely fast on any
subsequent lookup as it keeps the hash table in memory.
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R-filehash-2.4.1-2.lbn25.x86_64
Implements a simple key-value style database where character string keys
are associated with data values that are stored on the disk. A simple
interface is provided for inserting, retrieving, and deleting data from
the database. Utilities are provided that allow 'filehash' databases to be
treated much like environments and lists are already used in R. These
utilities are provided to encourage interactive and exploratory analysis
on large datasets. Three different file formats for representing the
database are currently available and new formats can easily be
incorporated by third parties for use in the 'filehash' framework.
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R-fortunes-1.5.4-1.lbn25.noarch
A collection of fortunes from the R community.
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R-fts-0.9.9-1.lbn25.x86_64
fast operations for time series objects
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R-future-1.8.0-1.lbn25.noarch
The purpose of this package is to provide a lightweight and unified Future API
for sequential and parallel processing of R expression via futures. The
simplest way to evaluate an expression in parallel is to use `x %<-% {
expression }` with `plan(multiprocess)`. This package implements sequential,
multicore, multisession, and cluster futures. With these, R expressions can be
evaluated on the local machine, in parallel a set of local machines, or
distributed on a mix of local and remote machines. Extensions to this package
implement additional backends for processing futures via compute cluster
schedulers etc. Because of its unified API, there is no need to modify any code
in order switch from sequential on the local machine to, say, distributed
processing on a remote compute cluster. Another strength of this package is
that global variables and functions are automatically identified and exported
as needed, making it straightforward to tweak existing code to make use of
futures.
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R-gamlss.dist-5.0.5-1.lbn25.x86_64
A set of distributions which can be used for modelling the response
variables in Generalized Additive Models for Location Scale and Shape,
Rigby and Stasinopoulos (2005), <doi:10.1111/j.1467-9876.2005.00510.x>.
The distributions can be continuous, discrete or mixed distributions.
Extra distributions can be created, by transforming, any continuous
distribution defined on the real line, to a distribution defined on
ranges 0 to infinity or 0 to 1, by using a "log" or a "logit"
transformation respectively.
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