Parents (Total: 84)

The searched file hash is included in 84 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
MD5	65536DDF11117D18091EFD62E28910ED
PackageArch	x86_64
PackageDescription	A header only library integrating 'testthat' with 'trompeoeil' to provide mocking for C++ code in R packages. Mocking is a technique for making a fake version of a software service. You can mock services to test that your code interacts correctly with external interfaces, to make your tests deterministic, or to break your tests down into smaller units. 'testthat' provides a testing framework for R and C++ code in R packages. 'trompeoeil' is a C++ header only library for mocking.
PackageName	R-mockcpp
PackageRelease	lp153.3.3
PackageVersion	0.0.1
SHA-1	05BA6043E95B5A6A08654BCB4A8E11E9B18BD7EC
SHA-256	4CB55702BB551AB4416F27466F395DB3A2A8F17BE8B620CC2D1152E58EBB912F

Key	Value
MD5	12EFD163599AFE0C1ED194AB043E70A4
PackageArch	x86_64
PackageDescription	Deprecated.
PackageName	R-hse
PackageRelease	1.19
PackageVersion	0.0.28
SHA-1	06223CE25DC22BD3C9DA28512A45095E4B0A5700
SHA-256	9496759BFD236A92E04E2201C35F7557675A0D53E5B4C17DD8B424ECA5E2FF13

Key	Value
MD5	B8FC9A6DC7046200775677D8D35FFA13
PackageArch	x86_64
PackageDescription	Enhances the 'R' Optimization Infrastructure ('ROI') package by registering the free 'GLPK' solver. It allows for solving mixed integer linear programming ('MILP') problems as well as all variants/combinations of 'LP', 'IP'.
PackageName	R-ROI.plugin.glpk
PackageRelease	lp152.3.6
PackageVersion	1.0.0
SHA-1	1052A7E0ECF94AA0BF44F1308CB44B7BDDC678AE
SHA-256	A6A18311B87CAE6E03106ED9B96F689FA74B5AE63F24DF33E31223B6BC6EBC02

Key	Value
MD5	9682DFE149A4FC402660ED8A98ECB279
PackageArch	x86_64
PackageDescription	The C++ header files of the Stan project are provided by this package, but it contains no R code or function documentation. There is a shared object containing part of the 'CVODES' library, but it is not accessible from R. 'StanHeaders' is only useful for developers who want to utilize the 'LinkingTo' directive of their package's DESCRIPTION file to build on the Stan library without incurring unnecessary dependencies. The Stan project develops a probabilistic programming language that implements full or approximate Bayesian statistical inference via Markov Chain Monte Carlo or 'variational' methods and implements (optionally penalized) maximum likelihood estimation via optimization. The Stan library includes an advanced automatic differentiation scheme, 'templated' statistical and linear algebra functions that can handle the automatically 'differentiable' scalar types (and doubles, 'ints', etc.), and a parser for the Stan language. The 'rstan' package provides user-facing R functions to parse, compile, test, estimate, and analyze Stan models.
PackageName	R-StanHeaders
PackageRelease	1.53
PackageVersion	2.19.0
SHA-1	11E893B8AFCA3BDEDC8A6DE3BE05072FA73DE9BA
SHA-256	37C4D5957F2AC1C42F77DEB29E35D553249B390ECAAE9F3C080D34D019CA1257

Key	Value
MD5	685C27BE8426F150E804C31EB1FC21E4
PackageArch	x86_64
PackageDescription	Fits mixed-effects models using a variety of distributions.
PackageName	R-glmmADMB
PackageRelease	lp153.1.12
PackageVersion	0.8.3.3
SHA-1	12C57164455AE46620B9A15E7589677A9ACD75E7
SHA-256	917EE177561F99EF1E3593D7598332A194F0BFB497417B8A2043E15CD2EF5CC5

Key	Value
MD5	F242DEB93550FAB4BF8F6B2836692333
PackageArch	x86_64
PackageDescription	Sejong(http://www.sejong.or.kr/) corpus and Hannanum(http://semanticweb.kaist.ac.kr/home/index.php/HanNanum) dictionaries for KoNLP
PackageName	R-Sejong
PackageRelease	lp153.2.3
PackageVersion	0.01
SHA-1	1420EEFCA894E7DFF0B4531C8F076BCBD6A2F310
SHA-256	416EEB5273BC9EE1DCFD2D17B2A188F0CC578763969FDD11483EA6C5B6175646

Key	Value
MD5	C0243FD047C2BBE34CB178AB83354099
PackageArch	x86_64
PackageDescription	This package allows R users to create interactive maps.
PackageName	R-rMaps
PackageRelease	lp151.1.72
PackageVersion	0.1.1
SHA-1	15D48D9C55510C3DD4E0719ECCE89E516C00761C
SHA-256	7498A55CD8BEE9743C31460024118010A13A7FD3F84A03194171B80061D1CA99

Key	Value
MD5	58292CF923E2B23CF9CDBB4C281A5A1F
PackageArch	x86_64
PackageDescription	Enhances the 'R' Optimization Infrastructure ('ROI') package by registering the 'ipop' solver from package 'kernlab'.
PackageName	R-ROI.plugin.ipop
PackageRelease	lp153.3.3
PackageVersion	1.0.0
SHA-1	16DFEAE3CEF90B1F52593E0EB6179DB6A1102ACC
SHA-256	0059DE456524FD6EE1089301366F3883EA7A820985F31F44124FB69F51B11535

Key	Value
MD5	696370162A680CE7845BBF162DE88400
PackageArch	armv7hl
PackageDescription	External jars required for package RWeka.
PackageName	R-RWekajars
PackageRelease	1.98
PackageVersion	3.9.3.1
SHA-1	186813C973A887A495BA025FDB435CA4ABDEC9A4
SHA-256	C3BA081AE0D5A0EA4167C36BBF4D2586C66C3F6392763B0F263BCE6B07F6CE83

Key	Value
MD5	E43A53C3C1E906572D50BA4616CABC40
PackageArch	x86_64
PackageDescription	The C++ header files of the Stan project are provided by this package, but it contains no R code or function documentation. There is a shared object containing part of the 'CVODES' library, but it is not accessible from R. 'StanHeaders' is only useful for developers who want to utilize the 'LinkingTo' directive of their package's DESCRIPTION file to build on the Stan library without incurring unnecessary dependencies. The Stan project develops a probabilistic programming language that implements full or approximate Bayesian statistical inference via Markov Chain Monte Carlo or 'variational' methods and implements (optionally penalized) maximum likelihood estimation via optimization. The Stan library includes an advanced automatic differentiation scheme, 'templated' statistical and linear algebra functions that can handle the automatically 'differentiable' scalar types (and doubles, 'ints', etc.), and a parser for the Stan language. The 'rstan' package provides user-facing R functions to parse, compile, test, estimate, and analyze Stan models.
PackageName	R-StanHeaders
PackageRelease	lp150.1.11
PackageVersion	2.19.0
SHA-1	19356E1554D3C280FF856A9B9CC27183303C323E
SHA-256	15B3913667A3EEE91B935AFE83E9EE406266E60DB2D9C2B943B12FD4BEF97003