Mon, 13 Nov 2017

Package Rdimtools updated to version 0.1.2 with previous version 0.1.1 dated 2017-09-24

Title: Dimension Reduction and Estimation Methods
Description: We provide a rich collection of linear and nonlinear dimension reduction techniques implemented using 'RcppArmadillo'. The question on what we should use as the target dimension is addressed by intrinsic dimension estimation methods introduced as well. For more details on dimensionality techniques, see the paper by Ma and Zhu (2013) <doi:10.1111/j.1751-5823.2012.00182.x> if you are interested in statistical approach, or Engel, Huttenberger, and Hamann (2012) <doi:10.4230/OASIcs.VLUDS.2011.135> for a broader cross-disciplinary overview.
Author: Kisung You [aut, cre], Donggun Kim [ctb], Yoon Mo Jung [ctb]
Maintainer: Kisung You <kyou@nd.edu>

Diff between Rdimtools versions 0.1.1 dated 2017-09-24 and 0.1.2 dated 2017-11-13

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Package preText updated to version 0.6.1 with previous version 0.6.0 dated 2017-07-08

Title: Diagnostics to Assess the Effects of Text Preprocessing Decisions
Description: Functions to assess the effects of different text preprocessing decisions on the inferences drawn from the resulting document-term matrices they generate.
Author: Matthew J. Denny <mdenny@psu.edu>, Arthur Spirling <as9934@nyu.edu>,
Maintainer: Matthew J. Denny <mdenny@psu.edu>

Diff between preText versions 0.6.0 dated 2017-07-08 and 0.6.1 dated 2017-11-13

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Package ICCbin updated to version 1.1.1 with previous version 1.1 dated 2017-09-19

Title: Facilitates Clustered Binary Data Generation, and Estimation of Intracluster Correlation Coefficient (ICC) for Binary Data
Description: Assists in generating binary clustered data, estimates of Intracluster Correlation coefficient (ICC) for binary response in 16 different methods, and 5 different types of confidence intervals.
Author: Akhtar Hossain [aut, cre], Hrishikesh Chakraborty [aut]
Maintainer: Akhtar Hossain <mhossain@email.sc.edu>

Diff between ICCbin versions 1.1 dated 2017-09-19 and 1.1.1 dated 2017-11-13

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Package httptest updated to version 2.3.4 with previous version 2.3.2 dated 2017-10-20

Title: A Test Environment for HTTP Requests
Description: Testing code and packages that communicate with remote servers can be painful. Dealing with authentication, bootstrapping server state, cleaning up objects that may get created during the test run, network flakiness, and other complications can make testing seem too costly to bother with. But it doesn't need to be that hard. This package enables one to test all of the logic on the R sides of the API in your package without requiring access to the remote service. Importantly, it provides three test contexts that mock the network connection in different ways, and it offers additional expectations to assert that HTTP requests were--or were not--made. It also allows you to record real API responses to use as mocks in tests. With these tools, one can test that code is making the intended requests and that it handles the expected responses correctly, all without depending on a connection to a remote API.
Author: Neal Richardson [aut, cre]
Maintainer: Neal Richardson <neal.p.richardson@gmail.com>

Diff between httptest versions 2.3.2 dated 2017-10-20 and 2.3.4 dated 2017-11-13

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Package Rfast updated to version 1.8.5 with previous version 1.8.4 dated 2017-09-23

Title: Fast R Functions
Description: A collection of fast (utility) functions for data analysis. Column- and row- wise means, medians, variances, minimums, maximums, many t, F and G-square tests, many regressions (normal, logistic, Poisson), are some of the many fast functions.
Author: Manos Papadakis, Michail Tsagris, Marios Dimitriadis, Stefanos Fafalios, Ioannis Tsamardinos, Matteo Fasiolo, Giorgos Borboudakis, John Burkardt, Changliang Zou and Kleanthi Lakiotaki
Maintainer: Manos Papadakis <papadakm95@gmail.com>

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 Rfast-1.8.5/Rfast/src/reg_lib.cpp                |  591 ++++++++++++-----------
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 Rfast-1.8.5/Rfast/src/rmdp.cpp                   |   15 
 Rfast-1.8.5/Rfast/src/sort_mat.cpp               |   11 
 Rfast-1.8.5/Rfast/src/sort_mat_stable.cpp        |   29 -
 Rfast-1.8.5/Rfast/src/spml_mle.cpp               |  117 ++--
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 290 files changed, 2790 insertions(+), 2218 deletions(-)

More information about Rfast at CRAN
Permanent link

New package ipumsr with initial version 0.1.0
Package: ipumsr
Title: Read 'IPUMS' Extract Files
Version: 0.1.0
Authors@R: c( person("Greg Freedman Ellis", email = "gfellis@umn.edu", role = c("aut", "cre")), person("Derek Burk", role = "ctb"), person("Joe Grover", role = "ctb"), person("Minnesota Population Center", email = "ipums@umn.edu", role = "cph") )
Contact: ipums@umn.edu
URL: https://www.ipums.org, https://github.com/mnpopcenter/ipumsr
BugReports: https://github.com/mnpopcenter/ipumsr/issues
Description: An easy way to import census, survey and geographic data provided by 'IPUMS' into R plus tools to help use the associated metadata to make analysis easier. 'IPUMS' data describing 1.4 billion individuals drawn from over 750 censuses and surveys is available free of charge from our website <https://ipums.org>.
License: Mozilla Public License 2.0
Encoding: UTF-8
LazyData: true
Imports: dplyr (>= 0.7.0), haven, purrr, raster, readr, rlang, stringr, tibble, tidyr, xml2, Rcpp
RoxygenNote: 6.0.1
Suggests: DT, ggplot2, htmltools, knitr, rgdal, rmarkdown, rstudioapi, scales, sf, sp, shiny, testthat, covr
VignetteBuilder: knitr
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2017-11-13 20:44:36 UTC; gfellis
Author: Greg Freedman Ellis [aut, cre], Derek Burk [ctb], Joe Grover [ctb], Minnesota Population Center [cph]
Maintainer: Greg Freedman Ellis <gfellis@umn.edu>
Repository: CRAN
Date/Publication: 2017-11-13 23:27:19 UTC

More information about ipumsr at CRAN
Permanent link

Package ripums (with last version 0.1.0) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2017-11-03 0.1.0

Permanent link
New package tmuxr with initial version 0.1.0
Package: tmuxr
Title: Manage 'tmux'
Version: 0.1.0
Authors@R: c( person("Jeroen", "Janssens", email = "jeroen@datascienceworkshops.com", role = c("aut", "cre")), person("Data Science Workshops", role = c("cph", "fnd")) )
Description: Create, control, and record 'tmux' sessions, windows, and panes using a pipeable API.
Depends: R (>= 3.3.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
URL: https://github.com/datascienceworkshops/tmuxr
BugReports: https://github.com/datascienceworkshops/tmuxr/issues
SystemRequirements: tmux
OS_type: unix
Imports: purrr, stringr, magrittr
Collate: tmuxr.R server.R session.R window.R pane.R prompt.R send.R
RoxygenNote: 6.0.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2017-11-13 09:16:28 UTC; jeroen
Author: Jeroen Janssens [aut, cre], Data Science Workshops [cph, fnd]
Maintainer: Jeroen Janssens <jeroen@datascienceworkshops.com>
Repository: CRAN
Date/Publication: 2017-11-13 19:30:44 UTC

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Package tables updated to version 0.8.3 with previous version 0.8 dated 2017-01-03

Title: Formula-Driven Table Generation
Description: Computes and displays complex tables of summary statistics. Output may be in LaTeX, HTML, plain text, or an R matrix for further processing.
Author: Duncan Murdoch
Maintainer: Duncan Murdoch <murdoch@stats.uwo.ca>

Diff between tables versions 0.8 dated 2017-01-03 and 0.8.3 dated 2017-11-13

 DESCRIPTION                |    8 ++-
 MD5                        |   34 +++++++--------
 R/Hline.R                  |   10 ++--
 R/pseudo.R                 |    3 -
 R/tabular.R                |   89 +++++++++++++++++++++++++++-------------
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 inst/doc/HTML.html         |   98 ++++++++++++++++++++++-----------------------
 inst/doc/tables.R          |   73 ++++++++++++++++++---------------
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 inst/todo.txt              |    7 ++-
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 man/Heading.Rd             |   14 +++++-
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 man/Literal.Rd             |    5 +-
 vignettes/tables.Rnw       |   16 +++++++
 vignettes/tables.Rout.save |   23 ++++++++--
 18 files changed, 266 insertions(+), 148 deletions(-)

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Package StakeholderAnalysis updated to version 1.2 with previous version 1.1 dated 2017-10-24

Title: Measuring Stakeholder Influence
Description: Proposes an original instrument for measuring stakeholder influence on the development of an infrastructure project that is carried through by a municipality, drawing on stakeholder classifications (Mitchell, Agle, & Wood, 1997) and input-output modelling (Hester & Adams, 2013). Mitchell R., Agle B.R., & Wood D.J. <doi:10.2307/259247> Hester, P.T., & Adams, K.M. (2013) <doi:10.1016/j.procs.2013.09.282>.
Author: Anna Zamojska [aut], Piotr Zientara [aut], Sebastian Susmarski [aut], Lech Kujawski [aut, cre]
Maintainer: Lech Kujawski <lech.kujawski@ug.edu.pl>

Diff between StakeholderAnalysis versions 1.1 dated 2017-10-24 and 1.2 dated 2017-11-13

 StakeholderAnalysis-1.1/StakeholderAnalysis/man/StakeholderAnalysis_1.1-package.Rd |only
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 StakeholderAnalysis-1.2/StakeholderAnalysis/R/kod_do_11.R                          |    2 ++
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 6 files changed, 10 insertions(+), 8 deletions(-)

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Package raster updated to version 2.6-7 with previous version 2.5-8 dated 2016-06-02

Title: Geographic Data Analysis and Modeling
Description: Reading, writing, manipulating, analyzing and modeling of gridded spatial data. The package implements basic and high-level functions. Processing of very large files is supported.
Author: Robert J. Hijmans [cre, aut], Jacob van Etten [ctb], Joe Cheng [ctb], Matteo Mattiuzzi [ctb], Michael Sumner [ctb], Jonathan A. Greenberg [ctb], Oscar Perpinan Lamigueiro [ctb], Andrew Bevan [ctb], Etienne B. Racine [ctb], Ashton Shortridge [ctb], Aniruddha Ghosh [ctb]
Maintainer: Robert J. Hijmans <r.hijmans@gmail.com>

Diff between raster versions 2.5-8 dated 2016-06-02 and 2.6-7 dated 2017-11-13

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 136 files changed, 1398 insertions(+), 928 deletions(-)

More information about raster at CRAN
Permanent link

New package yasp with initial version 0.1.0
Package: yasp
Type: Package
Title: String Functions for Compact and Expressive Code
Version: 0.1.0
Author: Tomasz Kalinowski
Maintainer: Tomasz Kalinowski <tkalinow@asu.edu>
Description: A collection of string functions designed for writing more compact and expressive code. 'yasp' (Yet Another String Package) is simple, fast, dependency-free, and written in pure R. The package provides: a coherent set of abbreviations for paste() from package 'base' with a variety of defaults, such as p() for "paste" and pcc() for "paste and collapse with commas"; wrap(), bracket(), and others for wrapping a string in flanking characters; unwrap() for removing pairs of characters (at any position in a string); and sentence() for cleaning whitespace around punctuation and capitalization appropriate for prose sentences.
License: MIT + file LICENSE
URL: https://github.com/t-kalinowski/yasp
BugReports: https://github.com/t-kalinowski/yasp/issues
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-11-13 13:45:11 UTC; tomasz
Repository: CRAN
Date/Publication: 2017-11-13 18:35:52 UTC

More information about yasp at CRAN
Permanent link

Package utilsIPEA updated to version 0.0.5 with previous version 0.0.4 dated 2017-10-24

Title: IPEA Common Functions
Description: The most used functions on IPEA (Instituto de Pesquisa Economica Aplicada). Most of functions deal with brazilian names. It can guess the women single's name, extract prepositions or extract the first name.
Author: Gustavo Coelho [aut, cre], Lucas Mation [aut], Daniel Lima [ctb], Igor Noberto [ctb], João Victor Machado [ctb]
Maintainer: Gustavo Coelho <gustavo.coelho@ipea.gov.br>

Diff between utilsIPEA versions 0.0.4 dated 2017-10-24 and 0.0.5 dated 2017-11-13

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New package ToolsForCoDa with initial version 1.0.2
Package: ToolsForCoDa
Type: Package
Title: Multivariate Tools for Compositional Data Analysis
Version: 1.0.2
Date: 2017-11-12
Author: Jan Graffelman <jan.graffelman@upc.edu>
Maintainer: Jan Graffelman <jan.graffelman@upc.edu>
Depends: R (>= 1.8.0), MASS, HardyWeinberg, calibrate
Description: Provides functions for multivariate analysis with compositional data. Includes a function for doing compositional canonical correlation analysis. This analysis requires two data matrices of compositions, which can be adequately transformed and used as entries in a specialized program for canonical correlation analysis, that is able to deal with singular covariance matrices. The methodology is described in Graffelman et al. (2017) <doi:10.1101/144584>.
License: GPL (>= 2)
URL: www.R-project.org, http://www-eio.upc.edu/~jan
NeedsCompilation: no
Packaged: 2017-11-13 13:06:38 UTC; jan
Repository: CRAN
Date/Publication: 2017-11-13 18:17:38 UTC

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New package imbalance with initial version 0.1.0
Package: imbalance
Type: Package
Title: Preprocessing Algorithms for Imbalanced Datasets
Version: 0.1.0
Authors@R: c( person("Ignacio", "Cordón", email = "nacho.cordon.castillo@gmail.com", role = c("aut", "cre")) )
Maintainer: Ignacio Cordón <nacho.cordon.castillo@gmail.com>
Description: Algorithms to treat imbalanced datasets. Imbalanced datasets usually damage the performance of the classifiers. Thus, it is important to treat data before applying a classifier algorithm. This package includes recent preprocessing algorithms in the literature.
License: GPL (>= 2) | file LICENSE
Encoding: UTF-8
LazyData: true
BugReports: http://github.com/ncordon/imbalance/issues
URL: http://github.com/ncordon/imbalance
Depends: R (>= 3.4.0)
Imports: bnlearn, KernelKnn, ggplot2, utils, stats, mvtnorm, Rcpp
Suggests: testthat, C50, knitr, rmarkdown, FNN, smotefamily
RoxygenNote: 6.0.1
VignetteBuilder: knitr
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Packaged: 2017-11-13 14:59:05 UTC; nuwanda
Author: Ignacio Cordón [aut, cre]
Repository: CRAN
Date/Publication: 2017-11-13 18:19:24 UTC

More information about imbalance at CRAN
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Package dparser updated to version 0.1.8 with previous version 0.1.7 dated 2017-10-05

Title: Port of 'Dparser' Package
Description: A Scannerless GLR parser/parser generator. Note that GLR standing for "generalized LR", where L stands for "left-to-right" and R stands for "rightmost (derivation)". For more information see <https://en.wikipedia.org/wiki/GLR_parser>. This parser is based on the Tomita (1987) algorithm. (Paper can be found at <http://acl-arc.comp.nus.edu.sg/archives/acl-arc-090501d3/data/pdf/anthology-PDF/J/J87/J87-1004.pdf>). The original 'dparser' package documentation can be found at <http://dparser.sourceforge.net/>. This allows you to add mini-languages to R (like RxODE's ODE mini-language Wang, Hallow, and James 2015 <DOI:10.1002/psp4.12052>) or to parse other languages like 'NONMEM' to automatically translate them to R code. To use this in your code, add a LinkingTo dparser in your DESCRIPTION file and instead of using #include <dparse.h> use #include <dparser.h>. This also provides a R-based port of the make_dparser <http://dparser.sourceforge.net/d/make_dparser.cat> command called mkdparser(). Additionally you can parse an arbitrary grammar within R using the dparse() function, which works on most OSes and is mainly for grammar testing. The fastest parsing, of course, occurs at the C level, and is suggested.
Author: Matthew Fidler [aut, cre], John Plevyak [aut, cph]
Maintainer: Matthew Fidler <matthew.fidler@gmail.com>

Diff between dparser versions 0.1.7 dated 2017-10-05 and 0.1.8 dated 2017-11-13

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Package sglg updated to version 0.1.1 with previous version 0.1.0 dated 2017-09-22

Title: Fitting Semi-Parametric Generalized log-Gamma Regression Models
Description: Set of tools to fit a linear multiple or semi-parametric regression models and non-informative right-censoring may be considered. Under this setup, the localization parameter of the response variable distribution is modeled by using linear multiple regression or semi-parametric functions, whose non-parametric components may be approximated by natural cubic spline or P-splines. The supported distribution for the model error is a generalized log-gamma distribution which includes the generalized extreme value distribution as an important special case.
Author: Carlos Alberto Cardozo Delgado <cardozorpackages@gmail.com> and G. Paula and L. Vanegas
Maintainer: Carlos Alberto Cardozo Delgado <cardozorpackages@gmail.com>

Diff between sglg versions 0.1.0 dated 2017-09-22 and 0.1.1 dated 2017-11-13

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New package shinyKGode with initial version 1.0.0
Package: shinyKGode
Type: Package
Title: A Shiny User Interface of Time Warping for Improved Gradient Matching
Version: 1.0.0
Author: Joe Wandy
Maintainer: Joe Wandy <joe.wandy@glasgow.ac.uk>
Description: Interactive shiny application to perform inference of non-linear differential equations via gradient matching. Three (Lotka-Volterra, Fitz hugh Nagumo, and Biopathway) pre-defined models are provided, and users can also load their own models (in the Systems Biology Markup Language format) into the application.
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: tools (>= 3.4.1), shiny (>= 1.0.5), shinyjs (>= 0.9.1), ggplot2 (>= 2.2.1), reshape2 (>= 1.4.2), gridExtra (>= 2.3), mvtnorm (>= 1.0.6), KGode (>= 1.0.0), XML (>= 3.98.1.9),
Depends: pracma (>= 2.0.7), pspline (>= 1.0.18)
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-11-13 12:08:09 UTC; joewandy
Repository: CRAN
Date/Publication: 2017-11-13 16:44:18 UTC

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Package osrm updated to version 3.1.0 with previous version 3.0.2 dated 2017-08-10

Title: Interface Between R and the OpenStreetMap-Based Routing Service OSRM
Description: An interface between R and the OSRM API. OSRM is a routing service based on OpenStreetMap data. See <http://project-osrm.org/> for more information. This package allows to compute distances (travel time and kilometric distance) between points and travel time matrices.
Author: Timothée Giraud [cre, aut], Robin Cura [ctb], Matthieu Viry [ctb]
Maintainer: Timothée Giraud <timothee.giraud@cnrs.fr>

Diff between osrm versions 3.0.2 dated 2017-08-10 and 3.1.0 dated 2017-11-13

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Package cartography updated to version 2.0.2 with previous version 2.0.1 dated 2017-09-25

Title: Thematic Cartography
Description: Create and integrate maps in your R workflow. This package allows various cartographic representations such as proportional symbols, chroropleth, typology, flows or discontinuities maps. It also offers several features enhancing the graphic presentation of maps like cartographic palettes, layout elements (scale, north arrow, title...), labels, legends or access to some cartographic APIs. See Giraud and Lambert (2017) <doi:10.1007/978-3-319-57336-6_13>.
Author: Timothée Giraud [cre, aut], Nicolas Lambert [aut], Ian Fellows [cph] (no overlap algorithm for labels, from wordcloud package)
Maintainer: Timothée Giraud <timothee.giraud@cnrs.fr>

Diff between cartography versions 2.0.1 dated 2017-09-25 and 2.0.2 dated 2017-11-13

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Package episensr updated to version 0.9.2 with previous version 0.9.1 dated 2017-09-12

Title: Basic Sensitivity Analysis of Epidemiological Results
Description: Basic sensitivity analysis of the observed relative risks adjusting for unmeasured confounding and misclassification of the exposure/outcome, or both. It follows the bias analysis methods and examples from the book by Lash T.L, Fox M.P, and Fink A.K. "Applying Quantitative Bias Analysis to Epidemiologic Data", ('Springer', 2009).
Author: Denis Haine [aut, cre]
Maintainer: Denis Haine <denis.haine@gmail.com>

Diff between episensr versions 0.9.1 dated 2017-09-12 and 0.9.2 dated 2017-11-13

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Package decisionSupport updated to version 1.102.2 with previous version 1.102.1 dated 2017-10-06

Title: Quantitative Support of Decision Making under Uncertainty
Description: Supporting the quantitative analysis of binary welfare based decision making processes using Monte Carlo simulations. Decision support is given on two levels: (i) The actual decision level is to choose between two alternatives under probabilistic uncertainty. This package calculates the optimal decision based on maximizing expected welfare. (ii) The meta decision level is to allocate resources to reduce the uncertainty in the underlying decision problem, i.e to increase the current information to improve the actual decision making process. This problem is dealt with using the Value of Information Analysis. The Expected Value of Information for arbitrary prospective estimates can be calculated as well as Individual Expected Value of Perfect Information. The probabilistic calculations are done via Monte Carlo simulations. This Monte Carlo functionality can be used on its own.
Author: Eike Luedeling [cre, aut] (ICRAF), Lutz Göhring [aut] (ICRAF and Lutz Göhring Consulting)
Maintainer: Eike Luedeling <eike@eikeluedeling.com>

Diff between decisionSupport versions 1.102.1 dated 2017-10-06 and 1.102.2 dated 2017-11-13

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New package bootcluster with initial version 0.1.0
Package: bootcluster
Type: Package
Title: Bootstrapping Estimates of Clustering Stability
Version: 0.1.0
Author: Han Yu
Maintainer: Han Yu <hyu9@buffalo.edu>
Description: Implementation of the bootstrapping approach for the estimation of clustering stability on observation and cluster level, as well as its application in estimating the number of clusters.
Depends: R (>= 3.3.1)
Imports: cluster, mclust, flexclust, sets, fpc, plyr
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-11-12 17:35:20 UTC; Han
Repository: CRAN
Date/Publication: 2017-11-13 15:38:38 UTC

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Package Bergm updated to version 4.1.0 with previous version 4.0.0 dated 2017-03-14

Title: Bayesian Exponential Random Graph Models
Description: Set of tools to analyse Bayesian exponential random graph models.
Author: Alberto Caimo [aut, cre], Lampros Bouranis [aut], Florian Maire [ctb], Nial Friel [ctb]
Maintainer: Alberto Caimo <acaimo.stats@gmail.com>

Diff between Bergm versions 4.0.0 dated 2017-03-14 and 4.1.0 dated 2017-11-13

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New package SELF with initial version 0.1.0
Package: SELF
Type: Package
Title: A Structural Equation Embedded Likelihood Framework for Causal Discovery
Version: 0.1.0
Authors@R: c( person("Ruichu","Cai",email="cairuichu@gmail.com",role=c("ths")), person("Jie","Qiao",email="qiaojie2004@vip.qq.com",role=c("aut","cre")), person("Zhenjie","Zhang",email="zhenjie@adsc.com.sg",role=c("ths")), person("Zhifeng","Hao",email="zfhao@gdut.edu.cn",role=c("ths")) )
Author: Ruichu Cai [ths], Jie Qiao [aut, cre], Zhenjie Zhang [ths], Zhifeng Hao [ths]
Maintainer: Jie Qiao <qiaojie2004@vip.qq.com>
Description: Provides the SELF criteria to learn causal structure. Details of the algorithm can be found in "SELF: A Structural Equation Embedded Likelihood Framework for Causal Discovery" (AAAI 2018).
License: GPL-2
LazyData: true
Imports: data.table (>= 1.10.4), xgboost (>= 0.6-4), Rcpp (>= 0.12.10), CompareCausalNetworks (>= 0.1.0), bnlearn (>= 4.1.1)
LinkingTo: Rcpp
RoxygenNote: 6.0.1
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2017-11-13 11:46:02 UTC; qj
Repository: CRAN
Date/Publication: 2017-11-13 12:03:22 UTC

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Package gMCP updated to version 0.8-11 with previous version 0.8-10 dated 2015-08-31

Title: Graph Based Multiple Comparison Procedures
Description: Functions and a graphical user interface for graphical described multiple test procedures.
Author: Kornelius Rohmeyer [aut, cre], Florian Klinglmueller [aut]
Maintainer: Kornelius Rohmeyer <rohmeyer@small-projects.de>

Diff between gMCP versions 0.8-10 dated 2015-08-31 and 0.8-11 dated 2017-11-13

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More information about gMCP at CRAN
Permanent link

Package rethinker updated to version 1.1.0 with previous version 1.0.0 dated 2015-12-10

Title: RethinkDB Client
Description: Simple, native 'RethinkDB' client.
Author: Miron B. Kursa
Maintainer: Miron B. Kursa <M.Kursa@icm.edu.pl>

Diff between rethinker versions 1.0.0 dated 2015-12-10 and 1.1.0 dated 2017-11-13

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Permanent link

Package OneArmPhaseTwoStudy updated to version 1.0.3 with previous version 0.1.6 dated 2016-05-23

Title: Planning, Conducting, and Analysing Single-Arm Phase II Studies
Description: Purpose of this package is it to plan, monitor and evaluate oncological phase II studies. In general this kind of studies are single-arm trials with planned interim analysis and binary endpoint. To meet the resulting requirements, the package provides functions to calculate and evaluate 'Simon's two-stage designs' and 'so-called' 'subset designs'. If you are unfamiliar with this package a good starting point is to take a closer look at the functions getSolutions() and getSolutionsSub1().The web-based tool (<https://imbi.shinyapps.io/phaseII-app/>) extends the functionality of our R package by means of a proper dealing with over- and underrunning. The R function binom.test of the 'stats' R package and the package 'binom' might be helpful to assess the performance of the corresponding one-stage design as a reference.
Author: Marius Wirths
Maintainer: Johannes Krisam <krisam@imbi.uni-heidelberg.de>

Diff between OneArmPhaseTwoStudy versions 0.1.6 dated 2016-05-23 and 1.0.3 dated 2017-11-13

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More information about OneArmPhaseTwoStudy at CRAN
Permanent link

Package dendextend updated to version 1.6.0 with previous version 1.5.2 dated 2017-03-28

Title: Extending 'Dendrogram' Functionality in R
Description: Offers a set of functions for extending 'dendrogram' objects in R, letting you visualize and compare trees of 'hierarchical clusterings'. You can (1) Adjust a tree's graphical parameters - the color, size, type, etc of its branches, nodes and labels. (2) Visually and statistically compare different 'dendrograms' to one another.
Author: Tal Galili [aut, cre, cph] (https://www.r-statistics.com), Gavin Simpson [ctb], Gregory Jefferis [aut, ctb] (imported code from his dendroextras package), Marco Gallotta [ctb] (a.k.a: marcog), Johan Renaudie [ctb] (https://github.com/plannapus), The R Core Team [ctb] (Thanks for the Infastructure, and code in the examples), Kurt Hornik [ctb], Uwe Ligges [ctb], Andrej-Nikolai Spiess [ctb], Steve Horvath [ctb], Peter Langfelder [ctb], skullkey [ctb], Mark Van Der Loo [ctb] (https://github.com/markvanderloo d3dendrogram), Andrie de Vries [ctb] (ggdendro author), Zuguang Gu [ctb] (circlize author), Cath [ctb] (https://github.com/CathG), John Ma [ctb] (https://github.com/JohnMCMa), Yoav Benjamini [ths]
Maintainer: Tal Galili <tal.galili@gmail.com>

Diff between dendextend versions 1.5.2 dated 2017-03-28 and 1.6.0 dated 2017-11-13

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New package Dasst with initial version 0.3.3
Package: Dasst
Version: 0.3.3
Date: 2017-11-12
Title: Tools for Reading, Processing and Writing 'DSSAT' Files
Authors@R: c(person("Homero", "Lozza", role = c("aut", "cre"), email = "homerolozza@gmail.com"))
Author: Homero Lozza [aut, cre]
Maintainer: Homero Lozza <homerolozza@gmail.com>
Depends: R (>= 2.14.0)
Description: Provides methods for reading, displaying, processing and writing files originally arranged for the 'DSSAT-CSM' fixed width format. The 'DSSAT-CSM' cropping system model is described at J.W. Jones, G. Hoogenboomb, C.H. Porter, K.J. Boote, W.D. Batchelor, L.A. Hunt, P.W. Wilkens, U. Singh, A.J. Gijsman, J.T. Ritchie (2003) <doi:10.1016/S1161-0301(02)00107-7>.
License: GPL (>= 2)
Imports: methods
Collate: 'Class-Dasst.R' 'Dasst-methods.R' 'Dasst.R' 'dasstOptions.R' 'extractData.R' 'extractHeader.R' 'buildContents.R' 'data.R' 'gatherTables.R' 'read.dssat.R' 'stackTables.R' 'write.dssat.R'
NeedsCompilation: no
Packaged: 2017-11-12 19:11:16 UTC; lozza
Repository: CRAN
Date/Publication: 2017-11-13 11:37:10 UTC

More information about Dasst at CRAN
Permanent link

New package ballr with initial version 0.1.0
Package: ballr
Type: Package
Title: Access to Current and Historical Basketball Data
Version: 0.1.0
Date: 2017-11-07
Authors@R: person("Ryan", "Elmore", email = "rtelmore@gmail.com", role = c("aut", "cre"))
Description: Provides simple functions for accessing data/tables on <http://www.basketball.reference.com>.
License: GPL (>= 2)
Imports: dplyr (>= 0.7.0), lubridate, magrittr, rlang, rvest, XML, xml2, janitor, ggplot2, scales, devtools
Suggests: covr, knitr, rmarkdown
LazyData: TRUE
RoxygenNote: 6.0.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-11-12 22:33:15 UTC; Ryan
Author: Ryan Elmore [aut, cre]
Maintainer: Ryan Elmore <rtelmore@gmail.com>
Repository: CRAN
Date/Publication: 2017-11-13 11:39:44 UTC

More information about ballr at CRAN
Permanent link

New package ALEPlot with initial version 1.0
Package: ALEPlot
Type: Package
Title: Accumulated Local Effects (ALE) Plots and Partial Dependence (PD) Plots
Version: 1.0
Date: 2017-11-08
Author: Dan Apley
Maintainer: Dan Apley <apley@northwestern.edu>
Description: Visualizes the main effects of individual predictor variables and their second-order interaction effects in black-box supervised learning models. The package creates either Accumulated Local Effects (ALE) plots and/or Partial Dependence (PD) plots, given a fitted supervised learning model.
Imports: yaImpute
License: GPL-2
NeedsCompilation: no
Suggests: R.rsp, nnet
VignetteBuilder: R.rsp
RoxygenNote: 6.0.1
Packaged: 2017-11-12 19:17:37 UTC; thair
Repository: CRAN
Date/Publication: 2017-11-13 11:25:06 UTC

More information about ALEPlot at CRAN
Permanent link

Package udpipe updated to version 0.2 with previous version 0.1.1 dated 2017-09-13

Title: Tokenization, Parts of Speech Tagging, Lemmatization and Dependency Parsing with the 'UDPipe' 'NLP' Toolkit
Description: This natural language processing toolkit provides language-agnostic 'tokenization', 'parts of speech tagging', 'lemmatization' and 'dependency parsing' of raw text. Next to text parsing, the package also allows you to train annotation models based on data of 'treebanks' in 'CoNLL-U' format as provided at <http://universaldependencies.org/format.html>. The techniques are explained in detail in the paper: 'Tokenizing, POS Tagging, Lemmatizing and Parsing UD 2.0 with UDPipe', available at <doi:10.18653/v1/K17-3009>.
Author: Jan Wijffels [aut, cre, cph], BNOSAC [cph], Institute of Formal and Applied Linguistics, Faculty of Mathematics and Physics, Charles University in Prague, Czech Republic [cph], Milan Straka [cph], Jana Straková [cph]
Maintainer: Jan Wijffels <jwijffels@bnosac.be>

Diff between udpipe versions 0.1.1 dated 2017-09-13 and 0.2 dated 2017-11-13

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More information about udpipe at CRAN
Permanent link

New package sentometrics with initial version 0.2
Package: sentometrics
Type: Package
Title: An Integrated Framework for Textual Sentiment Time Series Aggregation and Prediction
Version: 0.2
Authors@R: c(person("David", "Ardia", email = "david.ardia@unine.ch", role = c("aut")), person("Keven", "Bluteau", email = "keven.bluteau@unine.ch", role = c("aut")), person("Samuel", "Borms", email = "samuel.borms@unine.ch", role = c("aut", "cre")), person("Kris", "Boudt", email = "kris.boudt@vub.be", role = c("aut")))
Author: David Ardia [aut], Keven Bluteau [aut], Samuel Borms [aut, cre], Kris Boudt [aut]
Maintainer: Samuel Borms <samuel.borms@unine.ch>
Description: Time series analysis based on textual sentiment, accounting for the intrinsic challenge that sentiment can be computed and pooled across texts and time in many ways. As described in Ardia et al. (2017) <https://ssrn.com/abstract=3067734>, the package provides a means to model the impact of sentiment in texts on a target variable, by first computing a wide range of textual sentiment measures and then selecting those that are most informative.
Depends: R (>= 3.4.2), data.table, ggplot2, foreach
License: GPL (>= 2)
BugReports: https://github.com/sborms/sentometrics/issues
URL: https://github.com/sborms/sentometrics
Encoding: UTF-8
LazyData: true
Suggests: testthat, e1071, randomForest
Imports: utils, stats, quanteda, sentimentr, stringi, zoo, abind, glmnet, caret, compiler, Rcpp (>= 0.12.13), RcppRoll, ggthemes, ISOweek, MCS
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2017-11-12 21:50:05 UTC; gebruiker
Repository: CRAN
Date/Publication: 2017-11-13 10:34:52 UTC

More information about sentometrics at CRAN
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Package QuantumClone updated to version 1.0.0.6 with previous version 1.0.0.4 dated 2017-03-08

Title: Clustering Mutations using High Throughput Sequencing (HTS) Data
Description: Using HTS data, clusters mutations in order to recreate putative clones from the data provided. It requires genotype at the location of the variant as well as the depth of coverage and number of reads supporting the mutation. Additional information may be provided, such as the contamination in the tumor sample. This package also provides a function QuantumCat() which simulates data obtained from tumor sequencing.
Author: Paul Deveau [aut, cre]
Maintainer: Paul Deveau <quantumclone.package@gmail.com>

Diff between QuantumClone versions 1.0.0.4 dated 2017-03-08 and 1.0.0.6 dated 2017-11-13

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Package quanteda updated to version 0.99.22 with previous version 0.99.12 dated 2017-10-06

Title: Quantitative Analysis of Textual Data
Description: A fast, flexible, and comprehensive framework for quantitative text analysis in R. Provides functionality for corpus management, creating and manipulating tokens and ngrams, exploring keywords in context, forming and manipulating sparse matrices of documents by features and feature co-occurrences, analyzing keywords, computing feature similarities and distances, applying content dictionaries, applying supervised and unsupervised machine learning, visually representing text and text analyses, and more.
Author: Kenneth Benoit [aut, cre, cph], Kohei Watanabe [ctb], Paul Nulty [ctb], Adam Obeng [ctb], Haiyan Wang [ctb], Benjamin Lauderdale [ctb], Will Lowe [ctb]
Maintainer: Kenneth Benoit <kbenoit@lse.ac.uk>

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 quanteda-0.99.22/quanteda/R/corpus-methods-tm.R                       |    2 
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 quanteda-0.99.22/quanteda/R/fcm.R                                     |   78 -
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 quanteda-0.99.22/quanteda/R/nfunctions.R                              |   35 
 quanteda-0.99.22/quanteda/R/nscrabble.R                               |   13 
 quanteda-0.99.22/quanteda/R/nsyllable.R                               |   22 
 quanteda-0.99.22/quanteda/R/quanteda-documentation.R                  |    4 
 quanteda-0.99.22/quanteda/R/readtext-methods.R                        |   13 
 quanteda-0.99.22/quanteda/R/regex2fixed.R                             |   32 
 quanteda-0.99.22/quanteda/R/spacyr-methods.R                          |   94 --
 quanteda-0.99.22/quanteda/R/stopwords.R                               |    2 
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 quanteda-0.99.22/quanteda/R/textmodel_wordscores.R                    |  177 ++--
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 quanteda-0.99.22/quanteda/R/textstat_dist.R                           |    6 
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 quanteda-0.99.22/quanteda/R/textstat_keyness.R                        |   22 
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 quanteda-0.99.22/quanteda/R/textstat_simil.R                          |    5 
 quanteda-0.99.22/quanteda/R/tokens.R                                  |  223 ++---
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More information about quanteda at CRAN
Permanent link

Package multiway updated to version 1.0-4 with previous version 1.0-3 dated 2017-05-19

Title: Component Models for Multi-Way Data
Description: Fits multi-way component models via alternating least squares algorithms with optional constraints: orthogonal, non-negative, unimodal, monotonic, periodic, smooth, or structure. Fit models include Individual Differences Scaling, Parallel Factor Analysis (1 and 2), Simultaneous Component Analysis, and Tucker Factor Analysis.
Author: Nathaniel E. Helwig <helwig@umn.edu>
Maintainer: Nathaniel E. Helwig <helwig@umn.edu>

Diff between multiway versions 1.0-3 dated 2017-05-19 and 1.0-4 dated 2017-11-13

 ChangeLog                |   35 ++++++++++++++
 DESCRIPTION              |    8 +--
 MD5                      |   48 ++++++++++---------
 NAMESPACE                |    3 -
 R/corcondia.R            |   33 +++++--------
 R/mpinv.R                |   14 ++++-
 R/parafac.R              |  110 +++++++++++++++++++++++++++++++-------------
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More information about multiway at CRAN
Permanent link

Package heatmaply updated to version 0.13.0 with previous version 0.12.1 dated 2017-10-26

Title: Interactive Cluster Heat Maps Using 'plotly'
Description: Create interactive cluster 'heatmaps' that can be saved as a stand- alone HTML file, embedded in 'R Markdown' documents or in a 'Shiny' app, and available in the 'RStudio' viewer pane. Hover the mouse pointer over a cell to show details or drag a rectangle to zoom. A 'heatmap' is a popular graphical method for visualizing high-dimensional data, in which a table of numbers are encoded as a grid of colored cells. The rows and columns of the matrix are ordered to highlight patterns and are often accompanied by 'dendrograms'. 'Heatmaps' are used in many fields for visualizing observations, correlations, missing values patterns, and more. Interactive 'heatmaps' allow the inspection of specific value by hovering the mouse over a cell, as well as zooming into a region of the 'heatmap' by dragging a rectangle around the relevant area. This work is based on the 'ggplot2' and 'plotly.js' engine. It produces similar 'heatmaps' as 'heatmap.2' or 'd3heatmap', with the advantage of speed ('plotly.js' is able to handle larger size matrix), the ability to zoom from the 'dendrogram' panes, and the placing of factor variables in the sides of the 'heatmap'.
Author: Tal Galili [aut, cre, cph] (https://www.r-statistics.com), Jonathan Sidi [ctb] (https://github.com/yonicd), Alan O'Callaghan [ctb] (https://github.com/Alanocallaghan), Yoav Benjamini [ths]
Maintainer: Tal Galili <tal.galili@gmail.com>

Diff between heatmaply versions 0.12.1 dated 2017-10-26 and 0.13.0 dated 2017-11-13

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More information about heatmaply at CRAN
Permanent link

Package esc updated to version 0.4.0 with previous version 0.3.2 dated 2017-09-27

Title: Effect Size Computation for Meta Analysis
Description: Implementation of the web-based 'Practical Meta-Analysis Effect Size Calculator' from David B. Wilson (<http://www.campbellcollaboration.org/escalc/html/EffectSizeCalculator-Home.php>) in R. Based on the input, the effect size can be returned as standardized mean difference, Cohen's f, Hedges' g, Pearson's r or Fisher's transformation z, odds ratio or log odds, or eta squared effect size.
Author: Daniel Lüdecke <d.luedecke@uke.de>
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

Diff between esc versions 0.3.2 dated 2017-09-27 and 0.4.0 dated 2017-11-13

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Package EAinference updated to version 0.2.2 with previous version 0.2.1 dated 2017-10-13

Title: Estimator Augmentation and Simulation-Based Inference
Description: Estimator augmentation methods for statistical inference on high-dimensional data, as described in Zhou, Q. (2014) <arXiv:1401.4425v2> and Zhou, Q. and Min, S. (2017) <doi:10.1214/17-EJS1309>. It provides several simulation-based inference methods: (a) Gaussian and wild multiplier bootstrap for lasso, group lasso, scaled lasso, scaled group lasso and their de-biased estimators, (b) importance sampler for approximating p-values in these methods, (c) Markov chain Monte Carlo lasso sampler with applications in post-selection inference.
Author: Seunghyun Min [aut, cre], Qing Zhou [aut]
Maintainer: Seunghyun Min <seunghyun@ucla.edu>

Diff between EAinference versions 0.2.1 dated 2017-10-13 and 0.2.2 dated 2017-11-13

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Package clubSandwich updated to version 0.3.0 with previous version 0.2.3 dated 2017-08-10

Title: Cluster-Robust (Sandwich) Variance Estimators with Small-Sample Corrections
Description: Provides several cluster-robust variance estimators (i.e., sandwich estimators) for ordinary and weighted least squares linear regression models, including the bias-reduced linearization estimator introduced by Bell and McCaffrey (2002) <http://www.statcan.gc.ca/pub/12-001-x/2002002/article/9058-eng.pdf> and developed further by Pustejovsky and Tipton (2017) <DOI:10.1080/07350015.2016.1247004>. The package includes functions for estimating the variance- covariance matrix and for testing single- and multiple-contrast hypotheses based on Wald test statistics. Tests of single regression coefficients use Satterthwaite or saddle-point corrections. Tests of multiple-contrast hypotheses use an approximation to Hotelling's T-squared distribution. Methods are provided for a variety of fitted models, including lm() and mlm objects, glm(), ivreg (from package 'AER'), plm() (from package 'plm'), gls() and lme() (from 'nlme'), robu() (from 'robumeta'), and rma.uni() and rma.mv() (from 'metafor').
Author: James Pustejovsky [aut, cre]
Maintainer: James Pustejovsky <jepusto@gmail.com>

Diff between clubSandwich versions 0.2.3 dated 2017-08-10 and 0.3.0 dated 2017-11-13

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Package ameco updated to version 0.2.8 with previous version 0.2.7 dated 2017-05-29

Title: European Commission Annual Macro-Economic (AMECO) Database
Description: Annual macro-economic database provided by the European Commission.
Author: Eric Persson [aut, cre]
Maintainer: Eric Persson <expersso5@gmail.com>

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New package LSRS with initial version 0.1.0
Package: LSRS
Type: Package
Title: Land Surface Remote Sensing
Version: 0.1.0
Author: Mehdi Sarparast
Maintainer: Mehdi Sarparast <mehdisarparast@gmail.com>
Description: Rapid satellite data streams in operational applications have clear benefits for monitoring land cover, especially when information can be delivered as fast as changing surface conditions. Over the past decade, remote sensing has become a key tool for monitoring and predicting environmental variables by using satellite data. This package presents the main applications in remote sensing for land surface monitoring and land cover mapping (soil, vegetation, water...). Tomlinson, C.J., Chapman, L., Thornes, E., Baker, C (2011) <doi:10.1002/met.287>.
Suggests: raster, sp, rasterVis, lattice, latticeExtra,RColorBrewer
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-11-12 16:53:22 UTC; mehdis
Repository: CRAN
Date/Publication: 2017-11-13 09:23:43 UTC

More information about LSRS at CRAN
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New package keyholder with initial version 0.1.1
Package: keyholder
Title: Store Data About Rows
Version: 0.1.1
Authors@R: person("Evgeni", "Chasnovski", email = "evgeni.chasnovski@gmail.com", role = c("aut", "cre"))
Description: Tools for keeping track of information, named "keys", about rows of data frame like objects. This is done by creating special attribute "keys" which is updated after every change in rows (subsetting, ordering, etc.). This package is designed to work tightly with 'dplyr' package.
Depends: R (>= 3.4.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
URL: https://echasnovski.github.io/keyholder/, https://github.com/echasnovski/keyholder/
BugReports: https://github.com/echasnovski/keyholder/issues/
RoxygenNote: 6.0.1
Imports: dplyr (>= 0.7.0), rlang (>= 0.1)
Suggests: knitr, rmarkdown, testthat, covr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-11-12 16:07:36 UTC; evgeni
Author: Evgeni Chasnovski [aut, cre]
Maintainer: Evgeni Chasnovski <evgeni.chasnovski@gmail.com>
Repository: CRAN
Date/Publication: 2017-11-13 09:21:46 UTC

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New package auctestr with initial version 1.0.0
Package: auctestr
Title: Statistical Testing for AUC Data
Version: 1.0.0
Authors@R: person("Josh", "Gardner", email = "jpgard@umich.edu", role = c("aut", "cre"))
Maintainer: Josh Gardner <jpgard@umich.edu>
Description: Performs statistical testing to compare predictive models based on multiple observations of the A' statistic (also known as Area Under the Receiver Operating Characteristic Curve, or AUC). Specifically, it implements a testing method based on the equivalence between the A' statistic and the Wilcoxon statistic. For more information, see Hanley and McNeil (1982) <doi:10.1148/radiology.143.1.7063747>.
Imports: dplyr, tidyr
Depends: R (>= 3.3.1)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-11-12 18:53:55 UTC; joshgardner
Author: Josh Gardner [aut, cre]
Repository: CRAN
Date/Publication: 2017-11-13 09:46:18 UTC

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Package propr updated to version 3.1.1 with previous version 3.0.7 dated 2017-09-06

Title: Calculating Proportionality Between Vectors of Compositional Data
Description: The bioinformatic evaluation of gene co-expression often begins with correlation-based analyses. However, this approach lacks statistical validity when applied to relative data. This includes, for example, biological count data generated by high-throughput RNA-sequencing, chromatin immunoprecipitation (ChIP), ChIP-sequencing, Methyl-Capture sequencing, and other techniques. This package implements several metrics for proportionality, including phi [Lovell et al (2015) <DOI:10.1371/journal.pcbi.1004075>] and rho [Erb and Notredame (2016) <DOI:10.1007/s12064-015-0220-8>]. This package also implements several metrics for differential proportionality. Unlike correlation, these measures give the same result for both relative and absolute data.
Author: Thomas Quinn [aut, cre], David Lovell [aut], Ionas Erb [aut], Anders Bilgrau [ctb], Greg Gloor [ctb]
Maintainer: Thomas Quinn <contacttomquinn@gmail.com>

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Package rclimateca updated to version 0.4 with previous version 0.2 dated 2017-02-27

Title: Fetch Climate Data from Environment Canada
Description: The Environment Canada climate archives <http://climate.weather.gc.ca/> are an important source of data for climate researchers in Canada and world wide. The repository contains temperature, precipitation, and wind data for more than 8,000 locations. The functions in this package simplify the process of downloading, subsetting, and manipulating these data for the purposes of more efficient workflows in climate research.
Author: Dewey Dunnington <dewey@fishandwhistle.net>
Maintainer: Dewey Dunnington <dewey@fishandwhistle.net>

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Package NNS updated to version 0.3.8 with previous version 0.3.7 dated 2017-09-30

Title: Nonlinear Nonparametric Statistics
Description: Nonlinear nonparametric statistics using partial moments. Partial moments are the elements of variance and asymptotically approximate the area of f(x). These robust statistics provide the basis for nonlinear analysis while retaining linear equivalences. NNS offers: Numerical integration, Numerical differentiation, Clustering, Correlation, Dependence, Causal analysis, ANOVA, Regression, Classification, Seasonality, Autoregressive modelling, Normalization and Stochastic dominance. All routines based on: Viole, F. and Nawrocki, D. (2013), Nonlinear Nonparametric Statistics: Using Partial Moments (ISBN: 1490523995).
Author: Fred Viole
Maintainer: Fred Viole <ovvo.financial.systems@gmail.com>

Diff between NNS versions 0.3.7 dated 2017-09-30 and 0.3.8 dated 2017-11-13

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Package mudata updated to version 0.1.1 with previous version 0.1 dated 2017-02-27

Title: Interchange Tools for Multi-Parameter Spatiotemporal Data
Description: Formatting and structuring multi-parameter spatiotemporal data is often a time-consuming task. This package offers functions and data structures designed to easily organize and visualize these data for applications in geology, paleolimnology, dendrochronology, and paleoclimate.
Author: Authors@R: person("Dewey", "Dunnington", role = c("aut", "cre"), email = "dewey@fishandwhistle.net")
Maintainer: Dewey Dunnington <dewey@fishandwhistle.net>

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Package blogdown updated to version 0.3 with previous version 0.2 dated 2017-11-01

Title: Create Blogs and Websites with R Markdown
Description: Write blog posts and web pages in R Markdown. This package supports the static site generator 'Hugo' (<https://gohugo.io>) best, and it also supports 'Jekyll' (<http://jekyllrb.com>) and 'Hexo' (<https://hexo.io>).
Author: Yihui Xie [aut, cre] (0000-0003-0645-5666), Beilei Bian [ctb], Forest Fang [ctb], Hiroaki Yutani [ctb], JJ Allaire [ctb], Kevin Ushey [ctb], RStudio Inc [cph]
Maintainer: Yihui Xie <xie@yihui.name>

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