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R-matrixStats-0.52.2-3.lbn25.x86_64
High-performing functions operating on rows and columns of matrices, e.g.
col / rowMedians(), col / rowRanks(), and col / rowSds(). Functions optimized
per data type and for subsetted calculations such that both memory usage and
processing time is minimized. There are also optimized vector-based methods,
e.g. binMeans(), madDiff() and weightedMedian().
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R-mime-0.5-2.lbn25.x86_64
Guesses the MIME type from a filename extension using the data derived
from /etc/mime.types in UNIX-type systems.
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R-mlbench-2.1.1-1.lbn25.x86_64
A collection of artificial and real-world machine learning benchmark
problems, including, e.g., several data sets from the UCI repository.
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R-mnormt-1.5.5-1.lbn25.x86_64
Functions are provided for computing the density and the distribution
function of multivariate normal and "t" random variables, and for
generating random vectors sampled from these distributions. Probabilities
are computed via non-Monte Carlo methods; different routines are used in
the case d=1, d=2, d>2, if d denotes the number of dimensions.
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R-mockery-0.4.1-1.lbn25.noarch
The two main functionalities of this package are creating mock objects
(functions) and selectively intercepting calls to a given function that
originate in some other function. It can be used with any testing
framework available for R. Mock objects can be injected with either this
package's own stub() function or a similar with_mock() facility present in
the testthat package.
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R-mockr-0.1-1.lbn25.noarch
Provides a means to mock a package function, i.e., temporarily substitute
it for testing. Designed as a drop-in replacement for
'testthat::with_mock()', which may break in R 3.4.0 and later.
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R-msm-1.6.4-3.lbn25.x86_64
Functions for fitting general continuous-time Markov and hidden Markov
multi-state models to longitudinal data. Both Markov transition rates
and the hidden Markov output process can be modeled in terms of
covariates. A variety of observation schemes are supported, including
processes observed at arbitrary times, completely-observed processes,
and censored states.
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R-multtest-2.32.0-3.lbn25.x86_64
Non-parametric bootstrap and permutation resampling-based multiple testing
procedures for controlling the family-wise error rate (FWER), generalized
family-wise error rate (gFWER), tail probability of the proportion of
false positives (TPPFP), and false discovery rate (FDR). Single-step and
step-wise methods are implemented. Tests based on a variety of t- and
F-statistics (including t-statistics based on regression parameters from
linear and survival models) are included. Results are reported in terms
of adjusted p-values, confindence regions and test statistic cutoffs.
The procedures are directly applicable to identifying differentially
expressed genes in DNA microarray experiments.
This Library is a part of the Bioconductor (bioconductor.org) proejct.
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R-munsell-0.4.3-1.lbn25.noarch
Provides easy access to, and manipulation of, the Munsell colours.
Provides a mapping between Munsell's original notation (e.g. "5R 5/10")
and hexadecimal strings suitable for use directly in R graphics. Also
provides utilities to explore slices through the Munsell colour tree, to
transform Munsell colours and display colour palettes.
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R-mvtnorm-1.0.6-3.lbn25.x86_64
This R package computes multivariate normal and t probabilities, quantiles
and densities.
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