plone

R-lubridate-1.7.10-4.fc36.x86_64
Functions to work with date-times and time-spans: fast and user friendly parsing of date-time data, extraction and updating of components of a date-time (years, months, days, hours, minutes, and seconds), algebraic manipulation on date-time and time-span objects. The 'lubridate' package has a consistent and memorable syntax that makes working with dates easy and fun. Parts of the 'CCTZ' source code, released under the Apache 2.0 License, are included in this package. See <https://github.com/google/cctz> for more details.
Located in LBN / … / Big Data / BastionLinux 36
R-mAr-1.1.2-27.fc36.noarch
R package: An R add-on package for estimation of multivariate AR models through a computationally-efficient stepwise least-squares algorithm (Neumaier and Schneider, 2001); the procedure is of particular interest for high-dimensional data without missing values such as geophysical fields.
Located in LBN / … / Big Data / BastionLinux 36
R-magrittr-2.0.1-4.fc36.x86_64
Provides a mechanism for chaining commands with a new forward-pipe operator. This operator will forward a value, or the result of an expression, into the next function call/expression. There is flexible support for the type of right-hand side expressions. For more information, see package vignette. To quote Rene Magritte, "Ceci n'est pas un pipe."
Located in LBN / … / Big Data / BastionLinux 36
R-markdown-1.1-9.fc36.x86_64
Provides R bindings to the 'Sundown' Markdown rendering library (<https://github.com/vmg/sundown>). Markdown is a plain-text formatting syntax that can be converted to 'XHTML' or other formats. See <http://en.wikipedia.org/wiki/Markdown> for more information about Markdown.
Located in LBN / … / Big Data / BastionLinux 36
R-matrixStats-0.59.0-3.fc36.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().
Located in LBN / … / Big Data / BastionLinux 36
R-memoise-2.0.0-4.fc36.noarch
Cache the results of a function so that when you call it again with the same arguments it returns the pre-computed value.
Located in LBN / … / Big Data / BastionLinux 36
R-mime-0.10-4.fc36.x86_64
Guesses the MIME type from a filename extension using the data derived from /etc/mime.types in UNIX-type systems.
Located in LBN / … / Big Data / BastionLinux 36
R-mlbench-2.1.3-4.fc36.x86_64
A collection of artificial and real-world machine learning benchmark problems, including, e.g., several data sets from the UCI repository.
Located in LBN / … / Big Data / BastionLinux 36
R-mnormt-2.0.2-5.fc36.x86_64
Functions are provided for computing the density and the distribution function of d-dimensional normal and "t" random variables, possibly truncated (on one side or two sides), and for generating random vectors sampled from these distributions, except sampling from the truncated "t". Moments of arbitrary order of a multivariate truncated normal are computed, and converted to cumulants up to order 4. Probabilities are computed via non-Monte Carlo methods; different routines are used in the case d=1, d=2, d=3, d>3, if d denotes the dimensionality.
Located in LBN / … / Big Data / BastionLinux 36
R-mockery-0.4.2-8.fc36.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.
Located in LBN / … / Big Data / BastionLinux 36

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