Wed, 08 May 2019

Package MVar.pt updated to version 2.0.6 with previous version 2.0.5 dated 2019-03-15

Title: Analise multivariada (brazilian portuguese)
Description: Pacote para analise multivariada, tendo funcoes que executam analise de correspondencia simples (CA) e multipla (MCA), analise de componentes principais (PCA), analise de correlacao canonica (CCA), analise fatorial (FA), escalonamento multidimensional (MDS), analise discriminante linear (LDA) e quadratica (QDA), analise de cluster hierarquico e nao hierarquico, regressao linear simples e multipla, analise de multiplos fatores (MFA) para dados quantitativos, qualitativos, de frequencia (MFACT) e dados mistos, projection pursuit (PP), grant tour e outras funcoes uteis para a analise multivariada.
Author: Paulo Cesar Ossani <ossanipc@hotmail.com> Marcelo Angelo Cirillo <macufla@des.ufla.br>
Maintainer: Paulo Cesar Ossani <ossanipc@hotmail.com>

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Package PRISMAstatement updated to version 1.1.1 with previous version 1.0.4 dated 2018-08-08

Title: Plot Flow Charts According to the "PRISMA" Statement
Description: Plot a PRISMA <http://prisma-statement.org/> flow chart describing the identification, screening, eligibility and inclusion or studies in systematic reviews. The PRISMA statement defines an evidence-based, minimal set of items for reporting in systematic reviews and meta-analyses. PRISMA should be used for the reporting of studies evaluating randomized clinical trials (RCT), and is also for reporting on systematic reviews of other types of research. There is also a function to generate flow charts describing exclusions and inclusions for any kind of study.
Author: Jack O. Wasey [aut, cre, cph] (<https://orcid.org/0000-0003-3738-4637>)
Maintainer: Jack O. Wasey <jack@jackwasey.com>

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Package future updated to version 1.13.0 with previous version 1.12.0 dated 2019-03-08

Title: Unified Parallel and Distributed Processing in R for Everyone
Description: The purpose of this package is to provide a lightweight and unified Future API for sequential and parallel processing of R expression via futures. The simplest way to evaluate an expression in parallel is to use `x %<-% { expression }` with `plan(multiprocess)`. This package implements sequential, multicore, multisession, and cluster futures. With these, R expressions can be evaluated on the local machine, in parallel a set of local machines, or distributed on a mix of local and remote machines. Extensions to this package implement additional backends for processing futures via compute cluster schedulers etc. Because of its unified API, there is no need to modify any code in order switch from sequential on the local machine to, say, distributed processing on a remote compute cluster. Another strength of this package is that global variables and functions are automatically identified and exported as needed, making it straightforward to tweak existing code to make use of futures.
Author: Henrik Bengtsson [aut, cre, cph]
Maintainer: Henrik Bengtsson <henrikb@braju.com>

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New package flan with initial version 0.7
Package: flan
Version: 0.7
Date: 2019-04-30
Type: Package
Title: FLuctuation ANalysis on Mutation Models
Authors@R: c(person("Adrien","Mazoyer", role =c("aut","cre"),email="mazoyer.adrien@courrier.uqam.ca"), person("Remy", "Drouilhet", role = "aut"), person("Stephane", "Despreaux", role = "aut"), person("Bernard", "Ycart", role = "aut"))
Author: Adrien Mazoyer [aut, cre], Remy Drouilhet [aut], Stephane Despreaux [aut], Bernard Ycart [aut]
Maintainer: Adrien Mazoyer <mazoyer.adrien@courrier.uqam.ca>
Description: Tools for fluctuations analysis of mutant cells counts.
License: GPL
URL: https://www.r-project.org, https://github.com/AdriMaz/flan
BugReports: https://github.com/AdriMaz/flan/issues
Depends: R (>= 3.0.0), lbfgsb3
Imports: Rcpp (>= 0.12.5), methods
LinkingTo: Rcpp, RcppArmadillo, RcppGSL
RcppModules: flan_module
LazyData: true
NeedsCompilation: yes
SystemRequirements: GNU GSL
Packaged: 2019-05-08 14:27:04 UTC; AdrienMazoyer
Repository: CRAN
Date/Publication: 2019-05-08 22:50:09 UTC

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Package densratio updated to version 0.1.1 with previous version 0.0.3 dated 2016-03-29

Title: Density Ratio Estimation
Description: Density ratio estimation. The estimated density ratio function can be used in many applications such as the inlier-based outlier detection, covariate shift adaptation and etc. The implemented methods are uLSIF (Hido et al. (2011) <doi:10.1007/s10115-010-0283-2>) and KLIEP (Sugiyama et al. (2007) <doi:10.1007/s10463-008-0197-x>).
Author: Koji Makiyama [aut, cre]
Maintainer: Koji Makiyama <hoxo.smile@gmail.com>

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Package gravity updated to version 0.9.8 with previous version 0.9.7 dated 2019-04-21

Title: Estimation Methods for Gravity Models
Description: A wrapper of different standard estimation methods for gravity models. This package provides estimation methods for log-log models and multiplicative models.
Author: Anna-Lena Woelwer [aut, cph], Jan Pablo Burgard [aut, cph], Joshua Kunst [aut, cph], Mauricio Vargas [aut, cre, cph] (<https://orcid.org/0000-0003-1017-7574>), Romain Francois [ctb] (adapted parts of the code to use dplyr 0.8.0), Lionel Henry [ctb] (simplified parts of the code), Hrisyana Doytchinova [rev] (sent us different suggestions and bug reports)
Maintainer: Mauricio Vargas <mvargas@dcc.uchile.cl>

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Package Rfast2 updated to version 0.0.2 with previous version 0.0.1 dated 2019-03-22

Title: A Collection of Efficient and Extremely Fast R Functions II
Description: A collection of fast statistical and utility functions for data analysis. Functions for regression, maximum likelihood, column-wise statistics and many more have been included. C++ has been utilized to speed up the functions.
Author: Manos Papadakis, Michail Tsagris, Stefanos Fafalios and Marios Dimitriadis.
Maintainer: Manos Papadakis <rfastofficial@gmail.com>

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Package MAINT.Data updated to version 2.2.0 with previous version 2.1.1 dated 2019-04-23

Title: Model and Analyse Interval Data
Description: Implements methodologies for modelling interval data by Normal and Skew-Normal distributions, considering appropriate parameterizations of the variance-covariance matrix that takes into account the intrinsic nature of interval data, and lead to four different possible configuration structures. The Skew-Normal parameters can be estimated by maximum likelihood, while Normal parameters may be estimated by maximum likelihood or robust trimmed maximum likelihood methods.
Author: Pedro Duarte Silva <psilva@porto.ucp.pt>, Paula Brito <mpbrito.fep.up.pt>
Maintainer: Pedro Duarte Silva <psilva@porto.ucp.pt>

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Package congressbr updated to version 0.2.1 with previous version 0.2.0 dated 2019-02-17

Title: Downloads, Unpacks and Tidies Legislative Data from the Brazilian Federal Senate and Chamber of Deputies
Description: Downloads and tidies data from the Brazilian Federal Senate and Chamber of Deputies Application Programming Interfaces available at <http:// legis.senado.gov.br/dadosabertos/> and <http://www.camara.leg.br/SitCamaraWS/> respectively.
Author: Robert McDonnell [aut, cre], Guilherme Jardim Duarte [aut], Danilo Freire [aut], Julio Trecenti [aut]
Maintainer: Robert McDonnell <mcdonnell.robert5@gmail.com>

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Package hergm updated to version 4.1-2 with previous version 4.1-1 dated 2019-05-01

Title: Hierarchical Exponential-Family Random Graph Models
Description: Hierarchical exponential-family random graph models with local dependence.
Author: Michael Schweinberger <michael.schweinberger@rice.edu> [aut, cre], Mark S. Handcock <handcock@ucla.edu> [aut], Sergii Babkin <babkin.sergii@gmail.com> [aut], Jonathan Stewart <jonathan.stewart@rice.edu> [aut], Duy Vu <duy.vu@unimelb.edu.au> [aut], Pamela Luna <pamela.luna@rice.edu> [ctb]
Maintainer: Michael Schweinberger <michael.schweinberger@rice.edu>

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Package GGIR updated to version 1.9-1 with previous version 1.9-0 dated 2019-03-15

Title: Raw Accelerometer Data Analysis
Description: A tool to process and analyse data collected with wearable raw acceleration sensors as described in van Hees and colleagues (2014) <doi: 10.1152/japplphysiol.00421.2014> and (2015) <doi: 10.1371/journal.pone.0142533>. The package has been developed and tested for binary data from 'GENEActiv' <https://www.activinsights.com/> and GENEA devices (not for sale), .csv-export data from 'Actigraph' <http://actigraphcorp.com> devices, and .cwa and .wav-format data from 'Axivity' <https://axivity.com/product/ax3>. These devices are currently widely used in research on human daily physical activity.
Author: Vincent T van Hees [aut, cre], Zhou Fang [ctb], Jing Hua Zhao [ctb], Joe Heywood [ctb], Evgeny Mirkes [ctb], Severine Sabia [ctb], Joan Capdevila Pujol [ctb], Jairo H Migueles [ctb]
Maintainer: Vincent T van Hees <vincentvanhees@gmail.com>

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Package awsMethods updated to version 1.1-1 with previous version 1.1-0 dated 2018-02-01

Title: Class and Methods Definitions for Packages 'aws', 'adimpro', 'fmri', 'dwi'
Description: Defines the method extract and provides 'openMP' support as needed in several packages.
Author: Joerg Polzehl [aut, cre], Felix Anker [ctb]
Maintainer: Joerg Polzehl <joerg.polzehl@wias-berlin.de>

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Package aws.signature updated to version 0.5.0 with previous version 0.4.4 dated 2018-07-27

Title: Amazon Web Services Request Signatures
Description: Generates version 2 and version 4 request signatures for Amazon Web Services ('AWS') <https://aws.amazon.com/> Application Programming Interfaces ('APIs') and provides a mechanism for retrieving credentials from environment variables, 'AWS' credentials files, and 'EC2' instance metadata. For use on 'EC2' instances, users will need to install the suggested package 'aws.ec2metadata' <https://cran.r-project.org/package=aws.ec2metadata>.
Author: Thomas J. Leeper [aut] (<https://orcid.org/0000-0003-4097-6326>), Jonathan Stott [cre, aut]
Maintainer: Jonathan Stott <jonathan.stott@magairports.com>

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Package pivot (with last version 18.4.17) was removed from CRAN

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

2018-05-01 18.4.17

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Package cytominer (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:

2017-09-17 0.1.0

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Package dplyr.teradata (with last version 0.3.1) was removed from CRAN

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

2019-03-20 0.3.1

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Package NetworkChange updated to version 0.5 with previous version 0.4 dated 2018-10-10

Title: Bayesian Package for Network Changepoint Analysis
Description: Network changepoint analysis for undirected network data. The package implements a hidden Markov network change point model (Park and Sohn 2019). Functions for break number detection using the approximate marginal likelihood and WAIC are also provided.
Author: Jong Hee Park [aut,cre], Yunkyu Sohn [aut]
Maintainer: Jong Hee Park <jongheepark@snu.ac.kr>

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Package apollo updated to version 0.0.7 with previous version 0.0.6 dated 2019-03-13

Title: Tools for Choice Model Estimation and Application
Description: The Choice Modelling Centre (CMC) at the University of Leeds has developed flexible code for the estimation and application of choice models in R. Users are able to write their own model functions or use a mix of already available ones. Random heterogeneity, both continuous and discrete and at the level of individuals and choices, can be incorporated for all models. There is support for both standalone models and hybrid model structures. Both classical and Bayesian estimation is available, and multiple discrete continuous models are covered in addition to discrete choice. Multi-threading processing is supported for estimation and a large number of pre and post-estimation routines, including for computing posterior (individual-level) distributions are available. For examples, a manual, and a support forum, visit www.ApolloChoiceModelling.com. For more information on choice models see Train, K. (2009) <isbn:978-0-521-74738-7> and Hess, S. & Daly, A.J. (2014) <isbn:978-1-781-00314-5> for an overview of the field.
Author: Stephane Hess [aut], David Palma [aut, cre]
Maintainer: David Palma <D.Palma@leeds.ac.uk>

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Permanent link

Package rabhit updated to version 0.1.1 with previous version 0.1.0.0 dated 2019-04-09

Title: Inference Tool for Antibody Haplotype
Description: Infers V-D-J haplotypes and gene deletions from AIRR-seq data, based on IGHJ, IGHD or IGHV as anchor, by adapting a Bayesian framework. It also calculates a Bayes factor, a number that indicates the certainty level of the inference, for each haplotyped gene. Citation: Gidoni, et al (2019) <doi:10.1038/s41467-019-08489-3>.
Author: Ayelet Peres [aut, cre], Moriah Gidoni [aut], Gur Yaari [aut, cph]
Maintainer: Ayelet Peres <peresay@biu.ac.il>

Diff between rabhit versions 0.1.0.0 dated 2019-04-09 and 0.1.1 dated 2019-05-08

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 rabhit-0.1.1/rabhit/NAMESPACE                                                                                       |    4 
 rabhit-0.1.1/rabhit/NEWS.md                                                                                         |    7 
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 rabhit-0.1.1/rabhit/R/graphic_functions.R                                                                           |   60 +++---
 rabhit-0.1.1/rabhit/R/internal_functions.R                                                                          |    2 
 rabhit-0.1.1/rabhit/R/rabhit.R                                                                                      |    5 
 rabhit-0.1.1/rabhit/README.md                                                                                       |    8 
 rabhit-0.1.1/rabhit/inst/doc/RAbHIT-vignette.R                                                                      |   31 +++
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 rabhit-0.1.1/rabhit/man/rabhit.Rd                                                                                   |    2 
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Package parsedate updated to version 1.2.0 with previous version 1.1.3 dated 2017-03-02

Title: Recognize and Parse Dates in Various Formats, Including All ISO 8601 Formats
Description: Parse dates automatically, without the need of specifying a format. Currently it includes the git date parser. It can also recognize and parse all ISO 8601 formats.
Author: Gábor Csárdi, Linus Torvalds
Maintainer: Gábor Csárdi <csardi.gabor@gmail.com>

Diff between parsedate versions 1.1.3 dated 2017-03-02 and 1.2.0 dated 2019-05-08

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Package Mediana updated to version 1.0.8 with previous version 1.0.7 dated 2018-07-16

Title: Clinical Trial Simulations
Description: Provides a general framework for clinical trial simulations based on the Clinical Scenario Evaluation (CSE) approach. The package supports a broad class of data models (including clinical trials with continuous, binary, survival-type and count-type endpoints as well as multivariate outcomes that are based on combinations of different endpoints), analysis strategies and commonly used evaluation criteria.
Author: Gautier Paux, Alex Dmitrienko.
Maintainer: Gautier Paux <gautier@paux.fr>

Diff between Mediana versions 1.0.7 dated 2018-07-16 and 1.0.8 dated 2019-05-08

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Package adimpro updated to version 0.9.0 with previous version 0.8.2 dated 2016-09-15

Title: Adaptive Smoothing of Digital Images
Description: Implements tools for manipulation of digital images and the Propagation Separation approach by Polzehl and Spokoiny (2006) <DOI:10.1007/s00440-005-0464-1> for smoothing digital images, see Polzehl and Tabelow (2007) <DOI:10.18637/jss.v019.i01>.
Author: Karsten Tabelow <tabelow@wias-berlin.de>, Joerg Polzehl <polzehl@wias-berlin.de>
Maintainer: Karsten Tabelow <tabelow@wias-berlin.de>

Diff between adimpro versions 0.8.2 dated 2016-09-15 and 0.9.0 dated 2019-05-08

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New package Rpipedrive with initial version 0.1.0
Package: Rpipedrive
Type: Package
Title: 'Pipedrive API's' Functions to Improvement and Integration's Systems
Version: 0.1.0
Author: Ney Moresco
Maintainer: Ney Moresco <neymoresco@hotmail.com>
Description: R interaction with 'pipedrive.com API'. All functions were created and documented according to <https://developers.pipedrive.com/docs/api/v1/>. Created with the objective of offering integration and even the development of 'APIs'. Making possible to create workflows and easily downloading databases for analysis.
License: GPL-2
Imports: httr (>= 1.3.1), jsonlite (>= 1.5), dplyr (>= 0.7.6), utils (>= 3.0.0)
Depends: R (>= 3.0.0)
Encoding: UTF-8
LazyData: false
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-05-06 13:26:01 UTC; ney.moresco
Repository: CRAN
Date/Publication: 2019-05-08 11:30:18 UTC

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New package multilevelMatching with initial version 1.0.0
Package: multilevelMatching
Type: Package
Title: Propensity Score Matching and Subclassification in Observational Studies with Multi-Level Treatments
Authors@R: c( person("Shu", "Yang", email = "shuyang@hsph.harvard.edu", role = c("aut")), person("Brian G.", "Barkley", email = "BarkleyBG@outlook.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-1787-4735")) )
Date: 2019-05-06
Version: 1.0.0
Description: Implements methods to estimate causal effects from observational studies when there are 2+ distinct levels of treatment (i.e., "multilevel treatment") using matching estimators, as introduced in Yang et al. (2016) <doi:10.1111/biom.12505>. Matching on covariates, and matching or stratification on modeled propensity scores, are available. These methods require matching on only a scalar function of generalized propensity scores.
Depends: R (>= 3.1.2)
Imports: Matching (>= 4.8-3.4), MASS (>= 7.3-35), nnet (>= 7.3-8), boot (>= 1.3-13)
License: GPL-2
VignetteBuilder: knitr
Suggests: knitr, rmarkdown, testthat, rprojroot
RoxygenNote: 6.1.0
LazyData: TRUE
URL: https://shuyang1987.github.io/multilevelMatching/
BugReports: https://github.com/shuyang1987/multilevelMatching/issues
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-05-06 13:12:21 UTC; tkg9iov
Author: Shu Yang [aut], Brian G. Barkley [aut, cre] (<https://orcid.org/0000-0003-1787-4735>)
Maintainer: Brian G. Barkley <BarkleyBG@outlook.com>
Repository: CRAN
Date/Publication: 2019-05-08 11:30:03 UTC

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Package MAVE updated to version 1.3.9 with previous version 1.3.8 dated 2018-05-20

Title: Methods for Dimension Reduction
Description: Functions for dimension reduction, using MAVE (Minimum Average Variance Estimation), OPG (Outer Product of Gradient) and KSIR (sliced inverse regression of kernel version). Methods for selecting the best dimension are also included. Xia (2002) <doi:10.1111/1467-9868.03411>; Xia (2007) <doi:10.1214/009053607000000352>; Wang (2008) <doi:10.1198/016214508000000418>.
Author: Hang Weiqiang<E0010758@u.nus.edu>, Xia Yingcun<staxyc@nus.edu.sg>
Maintainer: Hang Weiqiang<E0010758@u.nus.edu>

Diff between MAVE versions 1.3.8 dated 2018-05-20 and 1.3.9 dated 2019-05-08

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New package empichar with initial version 1.0.0
Package: empichar
Type: Package
Title: Evaluates the Empirical Characteristic Function for Multivariate Samples
Version: 1.0.0
Authors@R: person("Guillermo", "Basulto-Elias", email = "guillermobasulto@gmail.com", role = c("aut", "cre"))
Description: Evaluates the empirical characteristic function of univariate and multivariate samples. This package uses 'RcppArmadillo' for fast evaluation. It is also possible to export the code to be used in other packages at 'C++' level.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
LinkingTo: Rcpp, RcppArmadillo
Imports: Rcpp
Suggests: testthat (>= 2.1.0), spelling, covr
Language: en-US
NeedsCompilation: yes
Packaged: 2019-05-06 12:05:44 UTC; basulto
Author: Guillermo Basulto-Elias [aut, cre]
Maintainer: Guillermo Basulto-Elias <guillermobasulto@gmail.com>
Repository: CRAN
Date/Publication: 2019-05-08 11:30:14 UTC

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Package crch updated to version 1.0-3 with previous version 1.0-2 dated 2019-04-22

Title: Censored Regression with Conditional Heteroscedasticity
Description: Different approaches to censored or truncated regression with conditional heteroscedasticity are provided. First, continuous distributions can be used for the (right and/or left censored or truncated) response with separate linear predictors for the mean and variance. Second, cumulative link models for ordinal data (obtained by interval-censoring continuous data) can be employed for heteroscedastic extended logistic regression (HXLR). In the latter type of models, the intercepts depend on the thresholds that define the intervals.
Author: Jakob Messner [aut, cre] (<https://orcid.org/0000-0002-1027-3673>), Achim Zeileis [aut] (<https://orcid.org/0000-0003-0918-3766>), Reto Stauffer [aut] (<https://orcid.org/0000-0002-3798-5507>)
Maintainer: ORPHANED

Diff between crch versions 1.0-2 dated 2019-04-22 and 1.0-3 dated 2019-05-08

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New package todor with initial version 0.0.5
Package: todor
Title: Find All TODO Comments and More
Version: 0.0.5
Authors@R: person("Dominik", "Krzemiński", email = "raymon92@gmail.com", role = c("aut", "cre"))
Description: This is a simple addin to 'RStudio' that finds all 'TODO', 'FIX ME', 'CHANGED' etc. comments in your project and shows them as a markers list.
Depends: R (>= 3.3)
Imports: stringr, rex, rstudioapi
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-05-04 10:12:15 UTC; dominik
Author: Dominik Krzemiński [aut, cre]
Maintainer: Dominik Krzemiński <raymon92@gmail.com>
Repository: CRAN
Date/Publication: 2019-05-08 10:20:03 UTC

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New package spectralGraphTopology with initial version 0.1.0
Package: spectralGraphTopology
Title: Learning Graphs from Data via Spectral Constraints
Version: 0.1.0
Description: Block coordinate descent estimators to learn k-component, bipartite, and k-component bipartite graphs from data by imposing spectral constraints on the eigenvalues and eigenvectors of the Laplacian and adjacency matrices. Those estimators leverages spectral properties of the graphical models as a prior information, which turn out to play key roles in unsupervised machine learning tasks such as clustering and community detection. This package is based on the paper "A Unified Framework for Structured Graph Learning via Spectral Constraints" by S. Kumar et al (2019) <arXiv:1904.09792>.
Authors@R: c( person("Ze", "Vinicius", role = c("cre", "aut"), email = "jvmirca@gmail.com"), person(c("Daniel", "P."), "Palomar", role = "aut", email = "daniel.p.palomar@gmail.com") )
Maintainer: Ze Vinicius <jvmirca@gmail.com>
URL: https://github.com/dppalomar/spectralGraphTopology, https://mirca.github.io/spectralGraphTopology, https://www.danielppalomar.com
BugReports: https://github.com/dppalomar/spectralGraphTopology/issues
Depends:
License: GPL-3
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp, RcppArmadillo, RcppEigen
Imports: Rcpp, osqp, MASS, Matrix, progress, rlist
RoxygenNote: 6.1.1
Suggests: bookdown, knitr, prettydoc, rmarkdown, R.rsp, testthat, patrick, corrplot, igraph, kernlab, pals, clusterSim, viridis, quadprog, matrixcalc, CVXR
VignetteBuilder: bookdown, knitr, prettydoc, rmarkdown, R.rsp
NeedsCompilation: yes
Packaged: 2019-05-04 11:46:48 UTC; jvmirca
Author: Ze Vinicius [cre, aut], Daniel P. Palomar [aut]
Repository: CRAN
Date/Publication: 2019-05-08 10:30:03 UTC

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New package RVenn with initial version 1.0.0
Package: RVenn
Type: Package
Title: Set Operations for Many Sets
Version: 1.0.0
Authors@R: person("Turgut Yigit", "Akyol", email = "tyakyol@gmail.com", role = c("aut", "cre"))
Maintainer: Turgut Yigit Akyol <tyakyol@gmail.com>
Description: Set operations for many sets. The base functions for set operations in R are good for only two sets. This package uses 'purrr' to find the union, intersection and difference of three or more sets. Further, based on 'ggplot2' and 'ggforce', Venn diagram can be drawn for two or three sets (Venn diagrams with four or more sets are terrible, please use 'UpSet' if you have lots of sets). Finally, enrichment test can be applied to two sets whether an overlap is statistically significant or not.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: ggforce (>= 0.2.1), ggplot2 (>= 3.0.0), magrittr (>= 1.5), purrr (>= 0.2.5), methods (>= 3.5.1), rlang (>= 0.2.2)
RoxygenNote: 6.1.1
Collate: 'Construct.R' 'Plot.R' 'SetOperations.R' 'package-RVenn.R' 'Enrichment.R'
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-05-05 10:30:10 UTC; tyakyol
Author: Turgut Yigit Akyol [aut, cre]
Repository: CRAN
Date/Publication: 2019-05-08 10:30:16 UTC

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Package readtext updated to version 0.74 with previous version 0.71 dated 2018-05-10

Title: Import and Handling for Plain and Formatted Text Files
Description: Functions for importing and handling text files and formatted text files with additional meta-data, such including '.csv', '.tab', '.json', '.xml', '.html', '.pdf', '.doc', '.docx', '.rtf', '.xls', '.xlsx', and others.
Author: Kenneth Benoit [aut, cre, cph], Adam Obeng [aut], Kohei Watanabe [ctb], Akitaka Matsuo [ctb], Paul Nulty [ctb], Stefan Müller [ctb]
Maintainer: Kenneth Benoit <kbenoit@lse.ac.uk>

Diff between readtext versions 0.71 dated 2018-05-10 and 0.74 dated 2019-05-08

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 NEWS.md                         |   24 +
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 25 files changed, 525 insertions(+), 390 deletions(-)

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New package pvaluefunctions with initial version 1.0.0
Package: pvaluefunctions
Type: Package
Title: Creates and Plots P-Value Functions, S-Value Functions, Confidence Distributions and Confidence Densities
Version: 1.0.0
Authors@R: person("Denis", "Infanger", email = "denis.infanger@unibas.ch", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-9028-7110"))
Maintainer: Denis Infanger <denis.infanger@unibas.ch>
Description: Contains functions to compute and plot confidence distributions, confidence densities, p-value functions and s-value (surprisal) functions for several commonly used estimates. Instead of just calculating one p-value and one confidence interval, p-value functions display p-values and confidence intervals for many levels thereby allowing to gauge the compatibility of several parameter values with the data. These methods are discussed by Poole C. (1987) <doi:10.2105/AJPH.77.2.195>; Schweder T, Hjort NL. (2002) <doi:10.1111/1467-9469.00285>; Bender R, Berg G, Zeeb H. (2005) <doi:10.1002/bimj.200410104> ; Singh K, Xie M, Strawderman WE. (2007) <doi:10.1214/074921707000000102>; Rothman KJ, Greenland S, Lash TL. (2008, ISBN:9781451190052); Amrhein V, Trafimow D, Greenland S. (2019) <doi:10.1080/00031305.2018.1543137>; and Greenland S. (2019) <doi:10.1080/00031305.2018.1529625>.
Depends: R (>= 3.1.0)
Imports: ggplot2 (>= 3.1.1), scales (>= 1.0.0), zipfR (>= 0.6-10), stats
Suggests: knitr, rmarkdown, devtools
License: GPL-3
URL: https://github.com/DInfanger/pvaluefunctions
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-05-06 10:07:36 UTC; denis
Author: Denis Infanger [aut, cre] (<https://orcid.org/0000-0001-9028-7110>)
Repository: CRAN
Date/Publication: 2019-05-08 10:40:03 UTC

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New package npcure with initial version 0.1-2
Package: npcure
Version: 0.1-2
Date: 2019-05-06
Title: Nonparametric Estimation in Mixture Cure Models
Authors@R: c(person("Ignacio", "López-de-Ullibarri", role = c("aut", "cre"), email = "ignacio.lopezdeullibarri@udc.es"), person("Ana", "López-Cheda", role = "aut", email = "ana.lopez.cheda@udc.es"), person("Maria Amalia", "Jácome", role = "aut", email = "majacome@udc.es"))
Author: Ignacio López-de-Ullibarri [aut, cre], Ana López-Cheda [aut], Maria Amalia Jácome [aut]
Maintainer: Ignacio López-de-Ullibarri <ignacio.lopezdeullibarri@udc.es>
Depends: R (>= 3.5.0)
Suggests: KMsurv
Description: Performs nonparametric estimation in mixture cure models, and significance tests for the cure probability. For details, see López-Cheda et al. (2017a) <doi:10.1016/j.csda.2016.08.002> and López-Cheda et al. (2017b) <doi:10.1007/s11749-016-0515-1>.
License: GPL (>= 2)
Imports: permute, stats, utils, zoo
NeedsCompilation: yes
Encoding: UTF-8
Packaged: 2019-05-06 09:03:37 UTC; ilu
Repository: CRAN
Date/Publication: 2019-05-08 10:40:10 UTC

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New package dragon with initial version 0.1.0
Package: dragon
Type: Package
Title: Deep Time Redox Analysis of the Geobiology Ontology Network
Version: 0.1.0
Authors@R: c( person("Stephanie J.", "Spielman", role = c("aut", "cre"), email = "spielman@rowan.edu"))
Maintainer: Stephanie J. Spielman <spielman@rowan.edu>
Description: Visualization and manipulation of the mineral-chemistry network across deep time on earth.
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/spielmanlab/dragon
BugReports: https://github.com/spielmanlab/dragon/issues
Repository: CRAN
NeedsCompilation: no
RoxygenNote: 6.1.1
Imports: tidyverse, shiny, shinythemes, shinyWidgets, colourpicker, colorspace, RColorBrewer, DT, visNetwork, igraph, magrittr
Suggests: knitr, testthat (>= 2.1.0)
VignetteBuilder: knitr
Packaged: 2019-05-05 16:11:47 UTC; spielman
Author: Stephanie J. Spielman [aut, cre]
Date/Publication: 2019-05-08 10:30:10 UTC

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Package clustrd updated to version 1.3.1 with previous version 1.3 dated 2019-04-23

Title: Methods for Joint Dimension Reduction and Clustering
Description: A class of methods that combine dimension reduction and clustering of continuous, categorical or mixed-type data. For continuous data, the package contains implementations of factorial K-means (Vichi and Kiers 2001; <DOI:10.1016/S0167-9473(00)00064-5>) and reduced K-means (De Soete and Carroll 1994; <DOI:10.1007/978-3-642-51175-2_24>); both methods that combine principal component analysis with K-means clustering. For categorical data, the package provides MCA K-means (Hwang, Dillon and Takane 2006; <DOI:10.1007/s11336-004-1173-x>), i-FCB (Iodice D'Enza and Palumbo 2013, <DOI:10.1007/s00180-012-0329-x>) and Cluster Correspondence Analysis (van de Velden, Iodice D'Enza and Palumbo 2017; <DOI:10.1007/s11336-016-9514-0>), which combine multiple correspondence analysis with K-means. For mixed-type data, it provides mixed Reduced K-means and mixed Factorial K-means (van de Velden, Iodice D'Enza and Markos 2019; <DOI:10.1002/wics.1456>), which combine PCA for mixed-type data with K-means.
Author: Angelos Markos [aut, cre], Alfonso Iodice D'Enza [aut], Michel van de Velden [ctb]
Maintainer: Angelos Markos <amarkos@gmail.com>

Diff between clustrd versions 1.3 dated 2019-04-23 and 1.3.1 dated 2019-05-08

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Package aws updated to version 2.2-1 with previous version 2.2-0 dated 2018-07-30

Title: Adaptive Weights Smoothing
Description: We provide a collection of R-functions implementing adaptive smoothing procedures in 1D, 2D and 3D. This includes the Propagation-Separation Approach to adaptive smoothing as described in "J. Polzehl and V. Spokoiny (2006) <DOI:10.1007/s00440-005-0464-1>", "J. Polzehl and V. Spokoiny (2004) <DOI:10.20347/WIAS.PREPRINT.998>" and "J. Polzehl, K. Papafitsoros, K. Tabelow (2018) <DOI:10.20347/WIAS.PREPRINT.2520>", the Intersecting Confidence Intervals (ICI), variational approaches and a non-local means filter.
Author: Joerg Polzehl [aut, cre], Felix Anker [ctb]
Maintainer: Joerg Polzehl <joerg.polzehl@wias-berlin.de>

Diff between aws versions 2.2-0 dated 2018-07-30 and 2.2-1 dated 2019-05-08

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 25 files changed, 675 insertions(+), 188 deletions(-)

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Package ruimtehol updated to version 0.2 with previous version 0.1.2 dated 2019-01-28

Title: Learn Text 'Embeddings' with 'Starspace'
Description: Wraps the 'StarSpace' library <https://github.com/facebookresearch/StarSpace> allowing users to calculate word, sentence, article, document, webpage, link and entity 'embeddings'. By using the 'embeddings', you can perform text based multi-label classification, find similarities between texts and categories, do collaborative-filtering based recommendation as well as content-based recommendation, find out relations between entities, calculate graph 'embeddings' as well as perform semi-supervised learning and multi-task learning on plain text. The techniques are explained in detail in the paper: 'StarSpace: Embed All The Things!' by Wu et al. (2017), available at <arXiv:1709.03856>.
Author: Jan Wijffels [aut, cre, cph] (R wrapper), BNOSAC [cph] (R wrapper), Facebook, Inc. [cph] (Starspace (BSD licensed))
Maintainer: Jan Wijffels <jwijffels@bnosac.be>

Diff between ruimtehol versions 0.1.2 dated 2019-01-28 and 0.2 dated 2019-05-08

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Package dimRed updated to version 0.2.3 with previous version 0.2.2 dated 2018-11-13

Title: A Framework for Dimensionality Reduction
Description: A collection of dimensionality reduction techniques from R packages and a common interface for calling the methods.
Author: Guido Kraemer [aut, cre]
Maintainer: Guido Kraemer <gkraemer@bgc-jena.mpg.de>

Diff between dimRed versions 0.2.2 dated 2018-11-13 and 0.2.3 dated 2019-05-08

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Package cepreader updated to version 1.1-3 with previous version 1.1-2 dated 2018-02-05

Title: Read 'CEP' and Legacy 'CANOCO' Files
Description: Read Condensed Cornell Ecology Program ('CEP') and legacy 'CANOCO' files into R data frames.
Author: Jari Oksanen [aut, cre] (<https://orcid.org/0000-0001-7102-9626>), Gavin L. Simpson [aut] (<https://orcid.org/0000-0002-9084-8413>)
Maintainer: Jari Oksanen <jhoksane@gmail.com>

Diff between cepreader versions 1.1-2 dated 2018-02-05 and 1.1-3 dated 2019-05-08

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 LICENCE                               |    2 +-
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Package rgbif updated to version 1.3.0 with previous version 1.2.0 dated 2019-02-26

Title: Interface to the Global 'Biodiversity' Information Facility API
Description: A programmatic interface to the Web Service methods provided by the Global Biodiversity Information Facility ('GBIF'; <https://www.gbif.org/developer/summary>). 'GBIF' is a database of species occurrence records from sources all over the globe. 'rgbif' includes functions for searching for taxonomic names, retrieving information on data providers, getting species occurrence records, getting counts of occurrence records, and using the 'GBIF' tile map service to make 'rasters' summarizing huge amounts of data.
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>), Vijay Barve [ctb] (<https://orcid.org/0000-0002-4852-2567>), Peter Desmet [ctb] (<https://orcid.org/0000-0002-8442-8025>), Laurens Geffert [ctb], Dan Mcglinn [ctb] (<https://orcid.org/0000-0003-2359-3526>), Damiano Oldoni [ctb] (<https://orcid.org/0000-0003-3445-7562>), Karthik Ram [ctb] (<https://orcid.org/0000-0002-0233-1757>)
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

Diff between rgbif versions 1.2.0 dated 2019-02-26 and 1.3.0 dated 2019-05-08

 DESCRIPTION                                              |   17 
 MD5                                                      |  158 
 NEWS.md                                                  |   20 
 R/dataset_search.r                                       |    4 
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 R/occ_get.r                                              |    4 
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 81 files changed, 1332 insertions(+), 25004 deletions(-)

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New package onlineVAR with initial version 0.1-1
Package: onlineVAR
Title: Online Fitting of Time-Adaptive Lasso Vector Auto Regression
Version: 0.1-1
Date: 2019-05-05
Authors@R: c(person(given = "Jakob", family = "Messner", role = c("aut", "cre"), email = "jakob.messner@posteo.net"))
Depends: R (>= 2.10.0)
Imports: parallel, lattice
Suggests:
Description: Functions for recursive online fitting of time-adaptive lasso vector auto regression. A recursive coordinate descent algorithm is used to estimate sparse vector auto regressive models and exponential forgetting is applied to allow model changes. Details can be found in Jakob W. Messner and Pierre Pinson (2018). "Online adaptive LASSO estimation in Vector Auto Regressive models for wind power forecasting in high dimension". International Journal of Forecasting, in press. <doi:10.1016/j.ijforecast.2018.02.001>.
License: GPL-2 | GPL-3
NeedsCompilation: yes
Packaged: 2019-05-05 14:57:25 UTC; jakob
Author: Jakob Messner [aut, cre]
Maintainer: Jakob Messner <jakob.messner@posteo.net>
Repository: CRAN
Date/Publication: 2019-05-08 07:50:03 UTC

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New package msgl with initial version 2.3.9
Package: msgl
Type: Package
Title: Multinomial Sparse Group Lasso
Version: 2.3.9
Date: 2019-05-07
Authors@R: c( person("Martin", "Vincent", role = "aut"), person("Niels", "Richard Hansen", email = "niels.r.hansen@math.ku.dk", role = c("ctb", "cre")) )
Description: Multinomial logistic regression with sparse group lasso penalty. Simultaneous feature selection and parameter estimation for classification. Suitable for high dimensional multiclass classification with many classes. The algorithm computes the sparse group lasso penalized maximum likelihood estimate. Use of parallel computing for cross validation and subsampling is supported through the 'foreach' and 'doParallel' packages. Development version is on GitHub, please report package issues on GitHub.
URL: http://www.sciencedirect.com/science/article/pii/S0167947313002168, https://github.com/nielsrhansen/msgl
BugReports: https://github.com/nielsrhansen/msgl/issues
License: GPL (>= 2)
LazyLoad: yes
Imports: methods, tools, utils, stats
Depends: R (>= 3.2.4), Matrix, sglOptim (>= 1.3.7)
LinkingTo: Rcpp, RcppProgress, RcppArmadillo, BH, sglOptim
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
RoxygenNote: 6.1.1
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2019-05-07 20:02:30 UTC; xqz683
Author: Martin Vincent [aut], Niels Richard Hansen [ctb, cre]
Maintainer: Niels Richard Hansen <niels.r.hansen@math.ku.dk>
Repository: CRAN
Date/Publication: 2019-05-08 08:00:10 UTC

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New package ensemblepp with initial version 1.0-0
Package: ensemblepp
Title: Ensemble Postprocessing Data Sets
Version: 1.0-0
Date: 2019-05-03
Authors@R: c(person(given = "Jakob", family = "Messner", role = c("aut", "cre"), email = "jakob.messner@posteo.net"))
Author: Jakob Messner [aut, cre]
Maintainer: Jakob Messner <jakob.messner@posteo.net>
Depends: R (>= 2.10.0)
Suggests: ensembleBMA, crch, gamlss, ensembleMOS, SpecsVerification, scoringRules, glmx, ordinal, pROC, mvtnorm
Description: Data sets for the chapter "Ensemble Postprocessing with R" of the book Stephane Vannitsem, Daniel S. Wilks, and Jakob W. Messner (2018) "Statistical Postprocessing of Ensemble Forecasts", Elsevier, 362pp. These data sets contain temperature and precipitation ensemble weather forecasts and corresponding observations at Innsbruck/Austria. Additionally, a demo with the full code of the book chapter is provided.
License: GPL-2 | GPL-3
NeedsCompilation: no
Packaged: 2019-05-03 11:00:30 UTC; jakob
Repository: CRAN
Date/Publication: 2019-05-08 07:50:10 UTC

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Package rerddap updated to version 0.6.0 with previous version 0.5.0 dated 2019-02-01

Title: General Purpose Client for 'ERDDAP' Servers
Description: General purpose R client for 'ERDDAP' servers. Includes functions to search for 'datasets', get summary information on 'datasets', and fetch 'datasets', in either 'csv' or 'netCDF' format. 'ERDDAP' information: <https://upwell.pfeg.noaa.gov/erddap/information.html>.
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>), Ben Tupper [ctb], Roy Mendelssohn [ctb]
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

Diff between rerddap versions 0.5.0 dated 2019-02-01 and 0.6.0 dated 2019-05-08

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Package processx updated to version 3.3.1 with previous version 3.3.0 dated 2019-03-10

Title: Execute and Control System Processes
Description: Tools to run system processes in the background. It can check if a background process is running; wait on a background process to finish; get the exit status of finished processes; kill background processes. It can read the standard output and error of the processes, using non-blocking connections. 'processx' can poll a process for standard output or error, with a timeout. It can also poll several processes at once.
Author: Gábor Csárdi [aut, cre, cph] (<https://orcid.org/0000-0001-7098-9676>), Winston Chang [aut], RStudio [cph, fnd], Mango Solutions [cph, fnd]
Maintainer: Gábor Csárdi <csardi.gabor@gmail.com>

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Package astsa updated to version 1.9 with previous version 1.8 dated 2017-12-15

Title: Applied Statistical Time Series Analysis
Description: Data sets and scripts to accompany Time Series Analysis and Its Applications: With R Examples (4th ed), by R.H. Shumway and D.S. Stoffer. Springer Texts in Statistics, 2017, <DOI:10.1007/978-3-319-52452-8>, and Time Series: A Data Analysis Approach Using R. Chapman-Hall, 2019, <ISBN: 978-0367221096>.
Author: David Stoffer
Maintainer: David Stoffer <stoffer@pitt.edu>

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Package aphid updated to version 1.3.3 with previous version 1.3.2 dated 2019-03-15

Title: Analysis with Profile Hidden Markov Models
Description: Designed for the development and application of hidden Markov models and profile HMMs for biological sequence analysis. Contains functions for multiple and pairwise sequence alignment, model construction and parameter optimization, file import/export, implementation of the forward, backward and Viterbi algorithms for conditional sequence probabilities, tree-based sequence weighting, and sequence simulation. Features a wide variety of potential applications including database searching, gene-finding and annotation, phylogenetic analysis and sequence classification. Based on the models and algorithms described in Durbin et al (1998, ISBN: 9780521629713).
Author: Shaun Wilkinson [aut, cre]
Maintainer: Shaun Wilkinson <shaunpwilkinson@gmail.com>

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Package emstreeR updated to version 2.2.0 with previous version 2.1.2 dated 2019-03-17

Title: Tools for Fast Computing and Plotting Euclidean Minimum Spanning Trees
Description: Computes Euclidean Minimum Spanning Trees (EMST) using the fast Dual-Tree Boruvka algorithm (March, Ram, Gray, 2010, <doi:10.1145/1835804.1835882>) implemented in 'mlpack' - the C++ Machine Learning library (Curtin et al., 2013). 'emstreeR' heavily relies on 'RcppMLPACK' and 'Rcpp', working as a wrapper to the C++ fast EMST algorithm. Thus, R users do not have to deal with the R-'Rcpp'-C++ integration. The package also provides functions and an S3 method for readily plotting Minimum Spanning Trees (MST) using either 'base' R, 'scatterplot3d' or 'ggplot2' style.
Author: Allan Quadros [aut, cre], Andre Cancado [ctb]
Maintainer: Allan Quadros <allanvcq@gmail.com>

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