Fri, 23 Feb 2018

Package Bolstad updated to version 0.2-37 with previous version 0.2-36 dated 2018-01-24

Title: Functions for Elementary Bayesian Inference
Description: A set of R functions and data sets for the book Introduction to Bayesian Statistics, Bolstad, W.M. (2017), John Wiley & Sons ISBN 978-1-118-09156-2.
Author: James Curran [aut, cre]
Maintainer: James Curran <j.curran@auckland.ac.nz>

Diff between Bolstad versions 0.2-36 dated 2018-01-24 and 0.2-37 dated 2018-02-23

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Package SCperf updated to version 1.1.0 with previous version 1.0 dated 2012-02-05

Title: Functions for Planning and Managing Inventories in a Supply Chain
Description: Implements different inventory models, the bullwhip effect and other supply chain performance variables. Marchena Marlene (2010) <arXiv:1009.3977>.
Author: Marlene Marchena
Maintainer: Marlene Marchena <marchenamarlene@gmail.com>

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Package matchingMarkets updated to version 0.3-5 with previous version 0.3-4 dated 2018-01-11

Title: Analysis of Stable Matchings
Description: Implements structural estimators to correct for the sample selection bias from observed outcomes in matching markets. This includes one-sided matching of agents into groups as well as two-sided matching of students to schools. The package also contains algorithms to find stable matchings in the three most common matching problems: the stable roommates problem, the college admissions problem, and the house allocation problem.
Author: Thilo Klein [aut, cre], Sven Giegerich [ctb]
Maintainer: Thilo Klein <thilo@klein.uk>

Diff between matchingMarkets versions 0.3-4 dated 2018-01-11 and 0.3-5 dated 2018-02-23

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Package brainGraph updated to version 2.0.2 with previous version 2.0.0 dated 2018-02-05

Title: Graph Theory Analysis of Brain MRI Data
Description: A set of tools for performing graph theory analysis of brain MRI data. It works with data from a Freesurfer analysis (cortical thickness, volumes, local gyrification index, surface area), diffusion tensor tractography data (e.g., from FSL) and resting-state fMRI data (e.g., from DPABI). It contains a graphical user interface for graph visualization and data exploration, along with several functions for generating useful figures.
Author: Christopher G. Watson <cgwatson@bu.edu>
Maintainer: Christopher G. Watson <cgwatson@bu.edu>

Diff between brainGraph versions 2.0.0 dated 2018-02-05 and 2.0.2 dated 2018-02-23

 DESCRIPTION     |    8 ++++----
 MD5             |    8 ++++----
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 5 files changed, 45 insertions(+), 11 deletions(-)

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Package assertr updated to version 2.5 with previous version 2.0.2.2 dated 2017-06-06

Title: Assertive Programming for R Analysis Pipelines
Description: Provides functionality to assert conditions that have to be met so that errors in data used in analysis pipelines can fail quickly. Similar to 'stopifnot()' but more powerful, friendly, and easier for use in pipelines.
Author: Tony Fischetti [aut, cre]
Maintainer: Tony Fischetti <tony.fischetti@gmail.com>

Diff between assertr versions 2.0.2.2 dated 2017-06-06 and 2.5 dated 2018-02-23

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 24 files changed, 437 insertions(+), 618 deletions(-)

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New package states with initial version 0.2.0
Package: states
Type: Package
Title: Create Panels of Independent States
Version: 0.2.0
Authors@R: person("Andreas", "Beger", role = c("cre", "aut"), email = "adbeger@gmail.com", comment = c(ORCID = "0000-0003-1883-3169"))
Maintainer: Andreas Beger <adbeger@gmail.com>
Description: Create panel data consisting of independent states from 1816 to the present. The package includes the Gleditsch & Ward (G&W) and Correlates of War (COW) lists of independent states, as well as helper functions for working with state panel data and standardizing other data sources to create country-year/month/etc. data.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: dplyr, lubridate
Suggests: testthat, ggplot2, stringr, knitr, rmarkdown
RoxygenNote: 6.0.1
VignetteBuilder: knitr
URL: https://github.com/andybega/states, https://andybeger.com/states
BugReports: https://github.com/andybega/states/issues
NeedsCompilation: no
Packaged: 2018-02-23 11:56:43 UTC; andybega
Author: Andreas Beger [cre, aut] (<https://orcid.org/0000-0003-1883-3169>)
Repository: CRAN
Date/Publication: 2018-02-23 19:03:00 UTC

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New package segclust2d with initial version 0.1.0
Package: segclust2d
Type: Package
Title: Bivariate Segmentation/Clustering Methods and Tools
Version: 0.1.0
Authors@R: c(person("Remi", "Patin", role = c("aut", "cre"), email = "remi.patin@normale.fr"), person("Marie-Pierre", "Etienne", role = "aut"), person("Emilie", "Lebarbier", role = "aut"), person("Simon", "Benhamou", role = "aut"))
Description: Provides two methods for segmentation and joint segmentation/clustering of bivariate time-series. Originally intended for ecological segmentation (home-range and behavioural modes) but easily applied on other series, the package also provides tools for analysing outputs from R packages 'moveHMM' and 'marcher'. The segmentation method is a bivariate extension of Lavielle's method available in 'adehabitatLT' (Lavielle, 1999 <doi:10.1016/S0304-4149(99)00023-X> and 2005 <doi:10.1016/j.sigpro.2005.01.012>). This method rely on dynamic programming for efficient segmentation. The segmentation/clustering method alternates steps of dynamic programming with an Expectation-Maximization algorithm. This is an extension of Picard et al (2007) <doi:10.1111/j.1541-0420.2006.00729.x> method (formerly available in 'cghseg' package) to the bivariate case. The full description of the method is not published yet.
License: GPL-3
LazyData: TRUE
RoxygenNote: 6.0.1
Depends: R (>= 3.3.0)
Imports: RColorBrewer (>= 1.1-2), dplyr (>= 0.5.0), plyr (>= 1.8.4), reshape2 (>= 1.4.1), ggplot2(>= 2.1.0), magrittr, Rcpp, zoo, grDevices, graphics, stats, utils, scales
Suggests: knitr, rmarkdown, testthat, dygraphs (>= 1.1.1-1), xts (>= 0.9-7), leaflet (>= 1.0.1), sp (>= 1.2-3), adehabitatLT, depmixS4, moveHMM (>= 1.2), htmltools, move, devtools
LinkingTo: Rcpp, RcppArmadillo
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2018-02-23 10:47:47 UTC; patin
Author: Remi Patin [aut, cre], Marie-Pierre Etienne [aut], Emilie Lebarbier [aut], Simon Benhamou [aut]
Maintainer: Remi Patin <remi.patin@normale.fr>
Repository: CRAN
Date/Publication: 2018-02-23 19:25:02 UTC

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Package ruler updated to version 0.1.2 with previous version 0.1.1 dated 2018-01-05

Title: Tidy Data Validation Reports
Description: Tools for creating data validation pipelines and tidy reports. This package offers a framework for exploring and validating data frame like objects using 'dplyr' grammar of data manipulation.
Author: Evgeni Chasnovski [aut, cre]
Maintainer: Evgeni Chasnovski <evgeni.chasnovski@gmail.com>

Diff between ruler versions 0.1.1 dated 2018-01-05 and 0.1.2 dated 2018-02-23

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New package mmmgee with initial version 1.11
Package: mmmgee
Title: Simultaneous Inference for Multiple Linear Contrasts in GEE Models
Version: 1.11
Authors@R: c(person("Robin", "Ristl", email = "robin.ristl@meduniwien.ac.at", role = c("aut", "cre")), person("Lee", "McDaniel", role = "ctb",comment="Author of 'geeM' package"), person("Nick", "Henderson", role = "ctb",comment="Author of 'geeM' package"), person("Melanie", "Prague", role = "ctb",comment="Contributor to 'geeM' package"))
Imports: stats, methods, Matrix, mvtnorm
Suggests: geepack, testthat
Description: Provides global hypothesis tests, multiple testing procedures and simultaneous confidence intervals for multiple linear contrasts of regression coefficients in a single generalized estimating equation (GEE) model or across multiple GEE models. GEE models are fit by a modified version of the 'geeM' package.
Date: 2018-02-22
Author: Robin Ristl [aut, cre], Lee McDaniel [ctb] (Author of 'geeM' package), Nick Henderson [ctb] (Author of 'geeM' package), Melanie Prague [ctb] (Contributor to 'geeM' package)
Maintainer: Robin Ristl <robin.ristl@meduniwien.ac.at>
Depends: R (>= 3.0.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-02-23 13:44:52 UTC; Robin
Repository: CRAN
Date/Publication: 2018-02-23 19:19:43 UTC

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Package clespr updated to version 1.1.2 with previous version 1.0.1 dated 2018-01-16

Title: Composite Likelihood Estimation for Spatial Data
Description: Composite likelihood approach is implemented to estimating statistical models for spatial ordinal and proportional data based on Feng et al. (2014) <doi:10.1002/env.2306>. Parameter estimates are identified by maximizing composite log-likelihood functions using the limited memory BFGS optimization algorithm with bounding constraints, while standard errors are obtained by estimating the Godambe information matrix.
Author: Ting Fung (Ralph) Ma [cre, aut], Wenbo Wu [aut], Jun Zhu [aut], Xiaoping Feng [aut], Daniel Walsh [ctb], Robin Russell [ctb]
Maintainer: Ting Fung (Ralph) Ma <tingfung.ma@wisc.edu>

Diff between clespr versions 1.0.1 dated 2018-01-16 and 1.1.2 dated 2018-02-23

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Package bea.R updated to version 1.0.6 with previous version 1.0.5 dated 2018-02-23

Title: Bureau of Economic Analysis API
Description: Provides an R interface for the Bureau of Economic Analysis (BEA) API (see <http://www.bea.gov/API/bea_web_service_api_user_guide.htm> for more information) that serves two core purposes - 1. To Extract/Transform/Load data [beaGet()] from the BEA API as R-friendly formats in the user's work space [transformation done by default in beaGet() can be modified using optional parameters; see, too, bea2List(), bea2Tab()]. 2. To enable the search of descriptive meta data [beaSearch()]. Other features of the library exist mainly as intermediate methods or are in early stages of development. Important Note - You must have an API key to use this library. Register for a key at <http://www.bea.gov/API/signup/index.cfm> .
Author: Andrea Batch [aut, cre], Jeff Chen [ctb], Walt Kampas [ctb]
Maintainer: Andrea Batch <Andrea.Julca@bea.gov>

Diff between bea.R versions 1.0.5 dated 2018-02-23 and 1.0.6 dated 2018-02-23

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Package tkRplotR updated to version 0.1.1 with previous version 0.1.0 dated 2018-02-20

Title: Display Resizable Plots
Description: Display a plot in a Tk canvas.
Author: Filipe Campelo
Maintainer: Filipe Campelo <fcampelo@ci.uc.pt>

Diff between tkRplotR versions 0.1.0 dated 2018-02-20 and 0.1.1 dated 2018-02-23

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New package antaresRead with initial version 2.1.0
Package: antaresRead
Type: Package
Title: Import, Manipulate and Explore the Results of an 'Antares' Simulation
Version: 2.1.0
Date: 2018-02-23
Authors@R: c( person("Jalal-Edine", "ZAWAM", , "jalal-edine.zawam@rte-france.com", role = c("aut", "cre")), person("Francois", "Guillem", , "francois.guillem@rte-france.com", role = "aut"), person("Benoit", "Thieurmel", email = "benoit.thieurmel@datastorm.fr", role = "aut"), person(given = "Titouan", family = "Robert", email = "titouan.robert@datastorm.fr", role = "aut"), person("RTE", role = "cph") )
Maintainer: Jalal-Edine ZAWAM <jalal-edine.zawam@rte-france.com>
Description: Import, manipulate and explore results generated by 'Antares', a powerful software developed by RTE (Réseau de Transport d’Électricité) to simulate and study electric power systems (more information about 'Antares' here: <https://antares.rte-france.com>).
URL: https://github.com/rte-antares-rpackage/antaresRead
BugReports: https://github.com/rte-antares-rpackage/antaresRead/issues
License: GPL (>= 2) | file LICENSE
LazyData: TRUE
Imports: data.table (>= 1.9.6), lubridate (>= 1.7.1), plyr, methods, stats, stringr, shiny
Suggests: rhdf5 (>= 2.20.0), testthat, knitr, rmarkdown, foreach, parallel, DT, htmltools
RoxygenNote: 6.0.1
VignetteBuilder: knitr
Encoding: UTF-8
biocViews: Infrastructure, DataImport
NeedsCompilation: no
Packaged: 2018-02-23 12:00:35 UTC; jalazawa
Author: Jalal-Edine ZAWAM [aut, cre], Francois Guillem [aut], Benoit Thieurmel [aut], Titouan Robert [aut], RTE [cph]
Repository: CRAN
Date/Publication: 2018-02-23 17:57:23 UTC

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New package dynamo with initial version 1.0
Package: dynamo
Type: Package
Title: Fit a Stochastic Dynamical Array Model to Array Data
Version: 1.0
Date: 2018-02-23
Author: Adam Lund
Maintainer: Adam Lund <adam.lund@math.ku.dk>
Description: An implementation of the method proposed in Lund and Hansen (2018) for fitting 3-dimensional dynamical array models. The implementation is based on the glamlasso package, see Lund et al. (2017) <doi:10.1080/10618600.2017.1279548>, for efficient design matrix free lasso regularized estimation in a generalized linear array model. The implementation uses a block relaxation scheme to fit each individual component in the model using functions from the glamlasso package.
License: GPL (>= 2)
Depends: glamlasso (>= 3.0), abind, MortalitySmooth
Imports: Rcpp (>= 0.12.12)
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2018-02-23 17:02:30 UTC; adamlund
Repository: CRAN
Date/Publication: 2018-02-23 17:28:37 UTC

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Package dwapi updated to version 0.1.3 with previous version 0.1.2 dated 2018-01-10

Title: A Client for 'data.world' REST API
Description: A set of wrapper functions for 'data.world' REST API endpoints <https://apidocs.data.world>.
Author: Rafael Pereira [aut, cre], Triet Le [aut], Bryon Jacob [aut], Scott Came [aut]
Maintainer: Rafael Pereira <rafael.pereira@data.world>

Diff between dwapi versions 0.1.2 dated 2018-01-10 and 0.1.3 dated 2018-02-23

 dwapi-0.1.2/dwapi/R/create_insight_request.R                                                          |only
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 dwapi-0.1.3/dwapi/DESCRIPTION                                                                         |   16 -
 dwapi-0.1.3/dwapi/MD5                                                                                 |  127 +++++++---
 dwapi-0.1.3/dwapi/NAMESPACE                                                                           |   22 +
 dwapi-0.1.3/dwapi/NEWS.md                                                                             |   28 ++
 dwapi-0.1.3/dwapi/R/add_file.R                                                                        |    2 
 dwapi-0.1.3/dwapi/R/append_to_stream.R                                                                |only
 dwapi-0.1.3/dwapi/R/create_project.R                                                                  |only
 dwapi-0.1.3/dwapi/R/dataset_replace_request.R                                                         |    7 
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 dwapi-0.1.3/dwapi/R/delete_dataset.R                                                                  |only
 dwapi-0.1.3/dwapi/R/delete_insight.R                                                                  |only
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 dwapi-0.1.3/dwapi/R/dwapi.R                                                                           |   41 +++
 dwapi-0.1.3/dwapi/R/get_insight.R                                                                     |only
 dwapi-0.1.3/dwapi/R/get_insights.R                                                                    |only
 dwapi-0.1.3/dwapi/R/get_project.R                                                                     |only
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 dwapi-0.1.3/dwapi/R/link_dataset.R                                                                    |only
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 dwapi-0.1.3/dwapi/R/project_request.R                                                                 |only
 dwapi-0.1.3/dwapi/R/replace_dataset.R                                                                 |    2 
 dwapi-0.1.3/dwapi/R/replace_insight.R                                                                 |only
 dwapi-0.1.3/dwapi/R/replace_project.R                                                                 |only
 dwapi-0.1.3/dwapi/R/unlink_dataset.R                                                                  |only
 dwapi-0.1.3/dwapi/R/update_insight.R                                                                  |only
 dwapi-0.1.3/dwapi/R/update_project.R                                                                  |only
 dwapi-0.1.3/dwapi/R/user_info_response.R                                                              |    8 
 dwapi-0.1.3/dwapi/R/utils.R                                                                           |   44 +++
 dwapi-0.1.3/dwapi/build/reports                                                                       |only
 dwapi-0.1.3/dwapi/build/vignette.rds                                                                  |binary
 dwapi-0.1.3/dwapi/inst/doc/quickstart.R                                                               |   34 ++
 dwapi-0.1.3/dwapi/inst/doc/quickstart.Rmd                                                             |   32 --
 dwapi-0.1.3/dwapi/inst/doc/quickstart.html                                                            |   75 ++++-
 dwapi-0.1.3/dwapi/man/add_file.Rd                                                                     |    2 
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 dwapi-0.1.3/dwapi/man/append_record_to_stream.Rd                                                      |only
 dwapi-0.1.3/dwapi/man/append_values_to_stream.Rd                                                      |only
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Package brglm2 updated to version 0.1.7 with previous version 0.1.6 dated 2018-02-09

Title: Bias Reduction in Generalized Linear Models
Description: Estimation and inference from generalized linear models based on various methods for bias reduction. The 'brglmFit' fitting method can achieve reduction of estimation bias by solving either the mean bias-reducing adjusted score equations in Firth (1993) <doi:10.1093/biomet/80.1.27> and Kosmidis and Firth (2009) <doi:10.1093/biomet/asp055>, or the median bias-reduction adjusted score equations in Kenne et al. (2016) <arXiv:1604.04768>, or through the direct subtraction of an estimate of the bias of the maximum likelihood estimator from the maximum likelihood estimates as in Cordeiro and McCullagh (1991) <http://www.jstor.org/stable/2345592>. Estimation in all cases takes place via a quasi Fisher scoring algorithm, and S3 methods for the construction of of confidence intervals for the reduced-bias estimates are provided. In the special case of generalized linear models for binomial and multinomial responses, the adjusted score approaches return estimates with improved frequentist properties, that are also always finite, even in cases where the maximum likelihood estimates are infinite (e.g. complete and quasi-complete separation). 'brglm2' also provides pre-fit and post-fit methods for detecting separation and infinite maximum likelihood estimates in binomial response generalized linear models.
Author: Ioannis Kosmidis [aut, cre], Kjell Konis [ctb], Euloge Clovis Kenne Pagui [ctb], Nicola Sartori [ctb]
Maintainer: Ioannis Kosmidis <ioannis.kosmidis@warwick.ac.uk>

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Package bea.R updated to version 1.0.5 with previous version 1.0.4 dated 2017-12-07

Title: Bureau of Economic Analysis API
Description: Provides an R interface for the Bureau of Economic Analysis (BEA) API (see <http://www.bea.gov/API/bea_web_service_api_user_guide.htm> for more information) that serves two core purposes - 1. To Extract/Transform/Load data [beaGet()] from the BEA API as R-friendly formats in the user's work space [transformation done by default in beaGet() can be modified using optional parameters; see, too, bea2List(), bea2Tab()]. 2. To enable the search of descriptive meta data [beaSearch()]. Other features of the library exist mainly as intermediate methods or are in early stages of development. Important Note - You must have an API key to use this library. Register for a key at <http://www.bea.gov/API/signup/index.cfm> .
Author: Andrea Batch [aut, cre], Jeff Chen [ctb], Walt Kampas [ctb]
Maintainer: Andrea Batch <Andrea.Julca@bea.gov>

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Package RcmdrMisc updated to version 1.0-8 with previous version 1.0-7 dated 2018-01-03

Title: R Commander Miscellaneous Functions
Description: Various statistical, graphics, and data-management functions used by the Rcmdr package in the R Commander GUI for R.
Author: John Fox [aut, cre], Robert Muenchen [ctb], Dan Putler [ctb]
Maintainer: John Fox <jfox@mcmaster.ca>

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Package Rcmdr updated to version 2.4-2 with previous version 2.4-1 dated 2017-10-20

Title: R Commander
Description: A platform-independent basic-statistics GUI (graphical user interface) for R, based on the tcltk package.
Author: John Fox [aut, cre], Milan Bouchet-Valat [aut], Liviu Andronic [ctb], Michael Ash [ctb], Theophilius Boye [ctb], Stefano Calza [ctb], Andy Chang [ctb], Philippe Grosjean [ctb], Richard Heiberger [ctb], Kosar Karimi Pour [ctb], G. Jay Kerns [ctb], Renaud Lancelot [ctb], Matthieu Lesnoff [ctb], Uwe Ligges [ctb], Samir Messad [ctb], Martin Maechler [ctb], Robert Muenchen [ctb], Duncan Murdoch [ctb], Erich Neuwirth [ctb], Dan Putler [ctb], Brian Ripley [ctb], Miroslav Ristic [ctb], Peter Wolf [ctb], Kevin Wright [ctb]
Maintainer: John Fox <jfox@mcmaster.ca>

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Package PropCIs updated to version 0.3-0 with previous version 0.2-5 dated 2014-04-15

Title: Various Confidence Interval Methods for Proportions
Description: Computes two-sample confidence intervals for single, paired and independent proportions.
Author: Ralph Scherer
Maintainer: Ralph Scherer <shearer.ra76@gmail.com>

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Package mlt updated to version 0.2-2 with previous version 0.2-1 dated 2017-12-12

Title: Most Likely Transformations
Description: Likelihood-based estimation of conditional transformation models via the most likely transformation approach described in Hothorn et al. (2018) <DOI:10.1111/sjos.12291>.
Author: Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>)
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

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Package dnet updated to version 1.1.3 with previous version 1.1.2 dated 2018-01-19

Title: Integrative Analysis of Omics Data in Terms of Network, Evolution and Ontology
Description: The focus of the dnet by Fang and Gough (2014) <doi:10.1186/s13073-014-0064-8> is to make sense of omics data (such as gene expression and mutations) from different angles including: integration with molecular networks, enrichments using ontologies, and relevance to gene evolutionary ages. Integration is achieved to identify a gene subnetwork from the whole gene network whose nodes/genes are labelled with informative data (such as the significant levels of differential expression or survival risks). To help make sense of identified gene networks, enrichment analysis is also supported using a wide variety of pre-compiled ontologies and phylostratific gene age information in major organisms including: human, mouse, rat, chicken, C.elegans, fruit fly, zebrafish and arabidopsis. Add-on functionalities are supports for calculating semantic similarity between ontology terms (and between genes) and for calculating network affinity based on random walk; both can be done via high-performance parallel computing.
Author: Hai Fang and Julian Gough
Maintainer: Hai Fang <hfang@well.ox.ac.uk>

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Package neat updated to version 1.1.3 with previous version 1.1.2 dated 2018-02-09

Title: Efficient Network Enrichment Analysis Test
Description: Includes functions and examples to compute NEAT, the Network Enrichment Analysis Test described in Signorelli et al. (2016, <DOI:10.1186/s12859-016-1203-6>).
Author: Mirko Signorelli, Veronica Vinciotti and Ernst C. Wit
Maintainer: Mirko Signorelli <m.signorelli@lumc.nl>

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Package huxtable updated to version 3.0.0 with previous version 2.0.2 dated 2018-02-13

Title: Easily Create and Style Tables for LaTeX, HTML and Other Formats
Description: Like 'xtable', creates styled tables. Export to HTML, LaTeX, 'Word', 'Excel', 'PowerPoint' and other formats. Simple, modern interface to manipulate borders, size, position, captions, colours, text styles and number formatting. Includes a 'huxreg' function for creation of regression tables, and 'quick_*' one-liners to print data to a new document.
Author: David Hugh-Jones [aut, cre]
Maintainer: David Hugh-Jones <davidhughjones@gmail.com>

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Package bsplinePsd updated to version 0.2.0 with previous version 0.1.0 dated 2017-07-18

Title: Bayesian Nonparametric Spectral Density Estimation Using B-Spline Priors
Description: Implementation of a Metropolis-within-Gibbs MCMC algorithm to flexibly estimate the spectral density of a stationary time series. The algorithm updates a nonparametric B-spline prior using the Whittle likelihood to produce pseudo-posterior samples and is based on the work presented in Edwards, M.C., Meyer, R. and Christensen, N., Statistics and Computing (2018). <doi.org/10.1007/s11222-017-9796-9>.
Author: Matthew C. Edwards [aut, cre], Renate Meyer [aut], Nelson Christensen [aut]
Maintainer: Matthew C. Edwards <matt.edwards@auckland.ac.nz>

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Package basefun updated to version 0.0-40 with previous version 0.0-39 dated 2017-12-18

Title: Infrastructure for Computing with Basis Functions
Description: Some very simple infrastructure for basis functions.
Author: Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>)
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

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Package variables updated to version 0.0-31 with previous version 0.0-30 dated 2016-02-19

Title: Variable Descriptions
Description: Abstract descriptions of (yet) unobserved variables.
Author: Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>)
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

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New package NlinTS with initial version 1.0
Package: NlinTS
Type: Package
Title: Non Linear Time Series Analysis
Version: 1.0
Date: 2018-02-22
Authors@R: c(person("Youssef", "Hmamouche", role = c("aut", "cre"), email = "hmamoucheyussef@gmail.com"), person("Sylvain", "Barthelemy", role = c("cph"), email = "sylbarth@gmail.com"))
Maintainer: Youssef Hmamouche <hmamoucheyussef@gmail.com>
Description: The main functionalities of this package are about time series forecasting and causality detection. In particular, it provides a neural network Vector Auto-Regressive, the classical Granger causality test C.W.J.Granger (1980) <doi:10.1016/0165-1889(80)90069-X>, and a non-linear version of it.
License: GNU General Public License
Depends: Rcpp
Imports: methods, timeSeries
LinkingTo: Rcpp
SystemRequirements: C++11
NeedsCompilation: yes
RoxygenNote: 6.0.1
Packaged: 2018-02-23 11:03:47 UTC; youssef
Author: Youssef Hmamouche [aut, cre], Sylvain Barthelemy [cph]
Repository: CRAN
Date/Publication: 2018-02-23 11:24:53 UTC

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New package dnr with initial version 0.3.2
Package: dnr
Title: Simulate Dynamic Networks using Exponential Random Graph Models (ERGM) Family
Version: 0.3.2
Authors@R: c(person("Abhirup", "Mallik", email = "malli066@umn.edu", role = c("aut", "cre")), person("Zack", "Almquist", email = "almquist@umn.edu", role = c("aut")))
Description: Functions are provided to fit temporal lag models to dynamic networks. The models are build on top of exponential random graph models (ERGM) framework. There are functions for simulating or forecasting networks for future time points. Stable Multiple Time Step Simulation/Prediction from Lagged Dynamic Network Regression Models. Mallik, Almquist (2017, under review).
Depends: R (>= 3.2.0), network, ergm
License: GPL-3
LazyData: yes
Imports: sna, igraph, arm, glmnet
Suggests: testthat, knitr
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-02-23 10:20:27 UTC; avi
Author: Abhirup Mallik [aut, cre], Zack Almquist [aut]
Maintainer: Abhirup Mallik <malli066@umn.edu>
Repository: CRAN
Date/Publication: 2018-02-23 11:20:58 UTC

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Package multfisher updated to version 1.1 with previous version 1.0 dated 2017-04-27

Title: Optimal Exact Tests for Multiple Binary Endpoints
Description: Calculates exact hypothesis tests to compare a treatment and a reference group with respect to multiple binary endpoints. The tested null hypothesis is an identical multidimensional distribution of successes and failures in both groups. The alternative hypothesis is a larger success proportion in the treatment group in at least one endpoint. The tests are based on the multivariate permutation distribution of subjects between the two groups. For this permutation distribution, rejection regions are calculated that satisfy one of different possible optimization criteria. In particular, regions with maximal exhaustion of the nominal significance level, maximal power under a specified alternative or maximal number of elements can be found. Optimization is achieved by a branch-and-bound algorithm. By application of the closed testing principle, the global hypothesis tests are extended to multiple testing procedures.
Author: Robin Ristl [aut, cre]
Maintainer: Robin Ristl <robin.ristl@meduniwien.ac.at>

Diff between multfisher versions 1.0 dated 2017-04-27 and 1.1 dated 2018-02-23

 multfisher-1.0/multfisher/R/multBinExact_2-3.R    |only
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Package TreeBUGS updated to version 1.3.1 with previous version 1.3.0 dated 2018-02-05

Title: Hierarchical Multinomial Processing Tree Modeling
Description: User-friendly analysis of hierarchical multinomial processing tree (MPT) models that are often used in cognitive psychology. Implements the latent-trait MPT approach (Klauer, 2010) <DOI:10.1007/s11336-009-9141-0> and the beta-MPT approach (Smith & Batchelder, 2010) <DOI:10.1016/j.jmp.2009.06.007> to model heterogeneity of participants. MPT models are conveniently specified by an .eqn-file as used by other MPT software and data are provided by a .csv-file or directly in R. Models are either fitted by calling JAGS or by an MPT-tailored Gibbs sampler in C++ (only for nonhierarchical and beta MPT models). Provides tests of heterogeneity and MPT-tailored summaries and plotting functions.
Author: Daniel W. Heck [aut, cre], Nina R. Arnold [aut, dtc], Denis Arnold [aut], Alexander Ly [ctb]
Maintainer: Daniel W. Heck <heck@uni-mannheim.de>

Diff between TreeBUGS versions 1.3.0 dated 2018-02-05 and 1.3.1 dated 2018-02-23

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New package supernova with initial version 1.0
Package: supernova
Type: Package
Title: Judd & McClelland Formatting for ANOVA Output
Version: 1.0
Date: 2018-02-09
Authors@R: c(person("Jim", "Stigler", email = "jstigler@gmail.com", role = c("cre", "aut")), person("Jeff", "Chrabaszcz", role = "aut"))
LazyData: yes
Description: Produces ANOVA tables in the format used by Judd, McClelland, and Ryan (2017, ISBN:978-1138819832) in their introductory textbook, Data Analysis. This includes proportional reduction in error and formatting to improve ease the transition between the book and R.
License: GPL-3
Suggests: ggformula, mosaic, Lock5Data, Lock5withR, okcupiddata, fivethirtyeight
RoxygenNote: 6.0.1
URL: https://github.com/UCLATALL/supernova
BugReports: https://github.com/UCLATALL/supernova/issues
NeedsCompilation: no
Packaged: 2018-02-22 12:03:43 UTC; jchrszcz
Author: Jim Stigler [cre, aut], Jeff Chrabaszcz [aut]
Maintainer: Jim Stigler <jstigler@gmail.com>
Repository: CRAN
Date/Publication: 2018-02-23 09:21:53 UTC

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Package SPUTNIK updated to version 1.0.1 with previous version 1.0.0 dated 2018-02-19

Title: SPatially aUTomatic deNoising for Ims toolKit
Description: A set of tools for the peak filtering of mass spectrometry imaging data (MSI or IMS) based on spatial distribution of signal. Given a region-of-interest (ROI), representing the spatial region where the informative signal is expected to be localized, a series of filters determine which peak signals are characterized by an implausible spatial distribution. The filters reduce the dataset dimensionality and increase its information vs noise ratio, improving the quality of the unsupervised analysis results, reducing data dimensionality and simplifying the chemical interpretation.
Author: Paolo Inglese [aut, cre], Goncalo Correia [aut, ctb]
Maintainer: Paolo Inglese <p.inglese14@imperial.ac.uk>

Diff between SPUTNIK versions 1.0.0 dated 2018-02-19 and 1.0.1 dated 2018-02-23

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Package intamapInteractive updated to version 1.1-12 with previous version 1.1-10 dated 2013-08-21

Title: Interactive Add-on Functionality for 'intamap'
Description: Includes additional functionality for spatial interpolation in the intamap package, such as bias correction and network optimization.
Author: Edzer Pebesma <edzer.pebesma@uni-muenster.de>, Jon Skoien <jon.skoien@gmail.com> with contributions from Olivier Baume, A.Chorti, D.T. Hristopulos, S.J. Melles, G. Spiliopoulos
Maintainer: Jon Skoien <jon.skoien@gmail.com>

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New package causalweight with initial version 0.1.0
Package: causalweight
Type: Package
Title: Causal Inference Based on Weighting Estimators
Version: 0.1.0
Author: Hugo Bodory and Martin Huber
Maintainer: Hugo Bodory <hugo.bodory@unifr.ch>
Description: Various estimation methods for causal inference based on inverse probability weighting. Specifically, the package includes methods for estimating average treatment effects as well as direct and indirect effects in causal mediation analysis. The models refer to the studies of Frölich (2007) <doi:10.1016/j.jeconom.2006.06.004>, Huber (2012) <doi:10.3102/1076998611411917>, Huber (2014) <doi:10.1080/07474938.2013.806197>, Huber (2014) <doi:10.1002/jae.2341>, and Frölich and Huber (2017) <doi:10.1111/rssb.12232>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Collate: 'functions.R' 'medweight.R' 'treatweight.R' 'lateweight.R' 'medlateweight.R'
RoxygenNote: 6.0.1
Depends: mvtnorm, np
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-02-22 21:50:29 UTC; HSG-Spezial
Repository: CRAN
Date/Publication: 2018-02-23 09:12:00 UTC

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Package MASS updated to version 7.3-49 with previous version 7.3-48 dated 2017-12-24

Title: Support Functions and Datasets for Venables and Ripley's MASS
Description: Functions and datasets to support Venables and Ripley, "Modern Applied Statistics with S" (4th edition, 2002).
Author: Brian Ripley [aut, cre, cph], Bill Venables [ctb], Douglas M. Bates [ctb], Kurt Hornik [trl] (partial port ca 1998), Albrecht Gebhardt [trl] (partial port ca 1998), David Firth [ctb]
Maintainer: Brian Ripley <ripley@stats.ox.ac.uk>

Diff between MASS versions 7.3-48 dated 2017-12-24 and 7.3-49 dated 2018-02-23

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Package CPBayes updated to version 0.3.0 with previous version 0.2.0 dated 2017-04-06

Title: Bayesian Meta Analysis for Studying Cross-Phenotype Genetic Associations
Description: A Bayesian meta-analysis method for studying cross-phenotype genetic associations. It uses summary-level data across multiple phenotypes to simultaneously measure the evidence of aggregate-level pleiotropic association and estimate an optimal subset of traits associated with the risk locus. CPBayes is based on a spike and slab prior and is implemented by Markov chain Monte Carlo technique Gibbs sampling.
Author: Arunabha Majumdar <statgen.arunabha@gmail.com> [aut, cre], Tanushree Haldar <tanushree.haldar@gmail.com> [aut], John Witte [ctb]
Maintainer: Arunabha Majumdar <statgen.arunabha@gmail.com>

Diff between CPBayes versions 0.2.0 dated 2017-04-06 and 0.3.0 dated 2018-02-23

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Package rpart updated to version 4.1-13 with previous version 4.1-12 dated 2018-01-10

Title: Recursive Partitioning and Regression Trees
Description: Recursive partitioning for classification, regression and survival trees. An implementation of most of the functionality of the 1984 book by Breiman, Friedman, Olshen and Stone.
Author: Terry Therneau [aut], Beth Atkinson [aut, cre], Brian Ripley [trl] (producer of the initial R port, maintainer 1999-2017)
Maintainer: Beth Atkinson <atkinson@mayo.edu>

Diff between rpart versions 4.1-12 dated 2018-01-10 and 4.1-13 dated 2018-02-23

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