Parents (Total: 377)

The searched file hash is included in 377 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
MD5	2D7C9615FC17A1BDD2E1DE5F66E04054
PackageArch	i586
PackageDescription	Multiple Precision Arithmetic (big integers and rationals, prime number tests, matrix computation), "arithmetic without limitations" using the C library GMP (GNU Multiple Precision Arithmetic).
PackageName	R-gmp
PackageRelease	lp150.3.23
PackageVersion	0.5_12
SHA-1	004402B56A82002EA83F75C4E69C425FD4BC5946
SHA-256	7B50450FB273507E28B71687A06B74CFE6BA272E0E8E5ECC20912369D50F238A

Key	Value
MD5	398146AF452676E64AC7454CA2CD3758
PackageArch	i586
PackageDescription	Provides an extensible framework for the efficient calculation of auto- and cross-proximities, along with implementations of the most popular
PackageName	R-proxy
PackageRelease	lp150.2.4
PackageVersion	0.4_13
SHA-1	011C6F67984CC678C563DC31144D379FF53F8243
SHA-256	2D57CAE825581AC2C67A2F00ECA57E696086C56D6AD165150B04EE8F72674B09

Key	Value
MD5	646EA49AFD6B7F96EB5AB1F694FE17DC
PackageArch	i586
PackageDescription	A lightweight package that adds progress bar to vectorized R functions ('*apply'). The implementation can easily be added to functions, where showing the progress is useful for the user (e.g. bootstrap).
PackageName	R-pbapply
PackageRelease	lp150.1.23
PackageVersion	1.2_1
SHA-1	0204502B4834732F7DE14C2B5387220FE21FC473
SHA-256	C5C24A9FAA3263C9717C91A3FF8EDF620F6662B430460D0AF3FE5E04F1DE58D9

Key	Value
MD5	A512D0CAD186C8E25DD379DB9BD47F87
PackageArch	i586
PackageDescription	Provides a parallel backend for the %dopar% function using the multicore functionality of the parallel package..
PackageName	R-doMC
PackageRelease	lp150.2.21
PackageVersion	1.3.3
SHA-1	02517ABF600EBBD3E20DA619FFA218156091AD87
SHA-256	C5890E23B8E746F92510A79796AFF87B6D1E28DB7E572FC9E40DECA9F4CCBE8D

Key	Value
MD5	A8A8F02BEB21F113F254BC23B0454359
PackageArch	i586
PackageDescription	Classification and regression based on a forest of trees using random
PackageName	R-randomForest
PackageRelease	lp150.2.4
PackageVersion	4.6_12
SHA-1	02CA9356F3A42FB035852DCD2F2037FB6BF3FB19
SHA-256	38D8BD719EAFE7419338CAE865ECB4D51A6AC47F3516CDA1DDAC5DBFA272EF33

Key	Value
MD5	D1CD15E284BFE4A6E766A330E97D57C1
PackageArch	i586
PackageDescription	Carries out mapping between assorted color spaces including RGB, HSV, HLS, CIEXYZ, CIELUV, HCL (polar CIELUV), CIELAB and polar CIELAB. Qualitative, sequential, and diverging color palettes based on HCL colors are provided.
PackageName	R-colorspace
PackageRelease	lp150.2.5
PackageVersion	1.2_4
SHA-1	043364863EC6905ADD9294CC51A6DEF8DF253592
SHA-256	3B3BD20A8EC7EA6CFEFE9AEC21E949C0B671E70B7271187A2D572E05412FB1CC

Key	Value
MD5	1844F770F3A391FEE4FFF98594E3E7E0
PackageArch	i586
PackageDescription	Fit generalized linear models with binomial responses using either an adjusted-score approach to bias reduction or maximum penalized likelihood where penalization is by Jeffreys invariant prior. These procedures return estimates with improved frequentist properties (bias, mean squared error) that are always finite even in cases where the maximum likelihood estimates are infinite (data separation). Fitting takes place by fitting generalized linear models on iteratively updated pseudo-data. The interface is essentially the same as 'glm'. More flexibility is provided by the fact that custom pseudo-data representations can be specified and used for model fitting. Functions are provided for the construction of confidence intervals for the reduced-bias estimates.
PackageName	R-brglm
PackageRelease	lp150.3.5
PackageVersion	0.5_9
SHA-1	054928618816F0338B95569E9A4ED25664599750
SHA-256	F02413D347C51B95A250E1891811782A9FCF93D50541B34F58F0A09E058C6BAC

Key	Value
MD5	826CB6B6E028CFA84AB65B2DF49D1240
PackageArch	i586
PackageDescription	A computational toolbox for recursive partitioning. The core of the package is ctree(), an implementation of conditional inference trees which embed tree-structured regression models into a well defined theory of conditional inference procedures. This non-parametric class of regression trees is applicable to all kinds of regression problems, including nominal, ordinal, numeric, censored as well as multivariate response variables and arbitrary measurement scales of the covariates. Based on conditional inference trees, cforest() provides an implementation of Breiman's random forests. The function mob() implements an algorithm for recursive partitioning based on parametric models (e.g. linear models, GLMs or survival regression) employing parameter instability tests for split selection. Extensible functionality for visualizing tree-structured regression models is available.
PackageName	R-party
PackageRelease	lp150.2.4
PackageVersion	1.0_17
SHA-1	062E201217A25CD976DC7A80738E63F8605F0CBC
SHA-256	D126A57C473924293B26DECDE5F755432A8F2CC1CF6B8120BFA36B3A522E4F28

Key	Value
MD5	272DED5FECCD788B123049992A8523FA
PackageArch	i586
PackageDescription	DescTools contains a bunch of basic statistic functions and convenience wrappers for efficiently describing data, creating specific plots, doing reports using MS Word, Excel or PowerPoint. The package's intention is to offer a toolbox, which facilitates the (notoriously time consuming) first descriptive tasks in data analysis, consisting of calculating descriptive statistics, drawing graphical summaries and reporting the results. Many of the included functions can be found scattered in other packages and other sources written partly by Titans of R. The reason for collecting them here, was primarily to have them consolidated in ONE instead of dozens of packages (which themselves might depend on other packages which are not needed at all), and to provide a common and consistent interface as far as function and arguments naming, NA handling, recycling rules etc. are concerned. Google style guides were used as naming rules (in absence of convincing alternatives). The 'camel style' was consequently applied to functions borrowed from contributed R packages as well.
PackageName	R-DescTools
PackageRelease	lp150.3.5
PackageVersion	0.99.8.1
SHA-1	0656FAE9528F868AE67170A58C6A08F1471FA152
SHA-256	D1D613987226E6678D273068859D10707279834D505F72A86938C6F2D8E0F0FC

Key	Value
MD5	5E578CF4AFB41A0B6FD74A0DE17CD0AB
PackageArch	i586
PackageDescription	Representations, conversions and display of orientation SO(3) data. See the orientlib help topic for details.
PackageName	R-orientlib
PackageRelease	lp150.1.23
PackageVersion	0.10.3
SHA-1	06871836B3BBB982B7AC745725037697F65EFD84
SHA-256	7208F6CB3B7CC64CD4CF82A97F89B701A7B014554BFD493AC8B8BC3D262625EB