Fri, 09 Aug 2019

Package vimp updated to version 1.1.5 with previous version 1.1.4 dated 2018-10-14

Title: Nonparametric Variable Importance
Description: Calculate point estimates of and valid confidence intervals for nonparametric variable importance measures in high and low dimensions, using flexible estimators of the underlying regression functions. For more information about the methods, please see Williamson et al. (2017) <https://biostats.bepress.com/uwbiostat/paper422/>.
Author: Brian D. Williamson [aut, cre], Noah Simon [aut], Marco Carone [aut]
Maintainer: Brian D. Williamson <brianw26@uw.edu>

Diff between vimp versions 1.1.4 dated 2018-10-14 and 1.1.5 dated 2019-08-09

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 16 files changed, 670 insertions(+), 337 deletions(-)

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Package SuperLearner updated to version 2.0-25 with previous version 2.0-24 dated 2018-08-11

Title: Super Learner Prediction
Description: Implements the super learner prediction method and contains a library of prediction algorithms to be used in the super learner.
Author: Eric Polley [aut, cre], Erin LeDell [aut], Chris Kennedy [aut], Sam Lendle [ctb], Mark van der Laan [aut, ths]
Maintainer: Eric Polley <polley.eric@mayo.edu>

Diff between SuperLearner versions 2.0-24 dated 2018-08-11 and 2.0-25 dated 2019-08-09

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New package censusxy with initial version 0.1.2
Package: censusxy
Title: Access the U.S. Census Bureau Geocoder
Version: 0.1.2
Authors@R: c( person("Christopher", "Prener", ,"chris.prener@slu.edu", c("aut", "cre"), comment = c(ORCID = "0000-0002-4310-9888")), person("Branson", "Fox", ,"branson.fox@slu.edu", c("aut"), comment = c(ORCID = "0000-0002-4361-2811")) )
Description: Provides access to the U.S. Census Bureau's API for batch geocoding American street addresses (<https://geocoding.geo.census.gov/geocoder>). The package offers a batch solution for address geocoding, as opposed to geocoding a single address at a time. It has also been developed specifically with large data sets in mind - only unique addresses are passed to the API for geocoding. If a data set exceeds 1,000 unique addresses, it will be automatically subset into appropriately sized API calls, geocoded, and then put back together so that a single object is returned.
Depends: R (>= 3.3)
License: GPL-3
URL: https://github.com/slu-openGIS/censusxy
BugReports: https://github.com/slu-openGIS/censusxy/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: dplyr, httr, readr, rlang, sf, tibble, tidyr
Suggests: covr, knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-09 15:12:52 UTC; chris
Author: Christopher Prener [aut, cre] (<https://orcid.org/0000-0002-4310-9888>), Branson Fox [aut] (<https://orcid.org/0000-0002-4361-2811>)
Maintainer: Christopher Prener <chris.prener@slu.edu>
Repository: CRAN
Date/Publication: 2019-08-09 22:10:05 UTC

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Package webmockr updated to version 0.4.0 with previous version 0.3.4 dated 2019-02-09

Title: Stubbing and Setting Expectations on 'HTTP' Requests
Description: Stubbing and setting expectations on 'HTTP' requests. Includes tools for stubbing 'HTTP' requests, including expected request conditions and response conditions. Match on 'HTTP' method, query parameters, request body, headers and more. Can be used for unit tests or outside of a testing context.
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>), rOpenSci [fnd] (https://ropensci.org)
Maintainer: Scott Chamberlain <myrmecocystus+r@gmail.com>

Diff between webmockr versions 0.3.4 dated 2019-02-09 and 0.4.0 dated 2019-08-09

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New package butcher with initial version 0.1.0
Package: butcher
Title: Model Butcher
Version: 0.1.0
Authors@R: c( person(given = "Joyce", family = "Cahoon", role = c("aut", "cre"), email = "joyceyu48@gmail.com", comment = c(ORCID = "0000-0001-7217-4702")), person(given = "Davis", family = "Vaughan", role = "aut", email = "davis@rstudio.com"), person(given = "Max", family = "Kuhn", role = "aut", email = "max@rstudio.com"), person(given = "Alex", family = "Hayes", role = "aut", email = "alexpghayes@gmail.com"))
Description: Provides a set of five S3 generics to axe components of fitted model objects and help reduce the size of model objects saved to disk.
License: MIT + file LICENSE
URL: https://tidymodels.github.io/butcher, https://github.com/tidymodels/butcher
BugReports: https://github.com/tidymodels/butcher/issues
Encoding: UTF-8
LazyData: true
Imports: purrr, rlang, lobstr (>= 1.1.1), tibble (>= 2.1.1), usethis, fs, utils, methods
RoxygenNote: 6.1.1
Suggests: clisymbols, testthat (>= 2.1.0), parsnip, knitr, rmarkdown, C50, kknn, glmnet, rpart, ranger, recipes, rsample, TH.data, ipred, survival, MASS, QSARdata, caret, flexsurv, pkgload, sparklyr, randomForest, kernlab, earth, covr, rstan, rstanarm, e1071, nnet, xgboost, dplyr, mda
Depends: R (>= 3.1)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-09 14:27:47 UTC; jcahoon
Author: Joyce Cahoon [aut, cre] (<https://orcid.org/0000-0001-7217-4702>), Davis Vaughan [aut], Max Kuhn [aut], Alex Hayes [aut]
Maintainer: Joyce Cahoon <joyceyu48@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-09 15:30:02 UTC

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Package simstudy updated to version 0.1.14 with previous version 0.1.13 dated 2019-05-16

Title: Simulation of Study Data
Description: Simulates data sets in order to explore modeling techniques or better understand data generating processes. The user specifies a set of relationships between covariates, and generates data based on these specifications. The final data sets can represent data from randomized control trials, repeated measure (longitudinal) designs, and cluster randomized trials. Missingness can be generated using various mechanisms (MCAR, MAR, NMAR).
Author: Keith Goldfeld [aut, cre]
Maintainer: Keith Goldfeld <Keith.Goldfeld@nyumc.org>

Diff between simstudy versions 0.1.13 dated 2019-05-16 and 0.1.14 dated 2019-08-09

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Package shinyML updated to version 0.1.1 with previous version 0.1.0 dated 2019-07-30

Title: Compare H20 or Spark Supervised Regression Models Using Shiny App
Description: Implementation of a shiny app to easily compare supervised regression model performances. You provide the data and configure each model parameter directly on the shiny app. Four main supervised learning algorithms can be tested either on Spark or H2O frameworks to suit your regression problem on a given time series. Implementation of these time series forecasting methods on R has been done by Shmueli and Lichtendahl (2015, ISBN:0991576632).
Author: Jean Bertin
Maintainer: Jean Bertin <jean.bertin@gadz.org>

Diff between shinyML versions 0.1.0 dated 2019-07-30 and 0.1.1 dated 2019-08-09

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Package sos4R updated to version 0.3.1 with previous version 0.3.0 dated 2019-04-13

Title: Client for OGC Sensor Observation Services
Description: A client for Sensor Observation Services (SOS, see <https://www.opengeospatial.org/standards/sos>) as specified by the Open Geospatial Consortium (OGC). With the package users can retrieve (meta)data from SOS instances and interactively create requests for near real-time observation data based on the available sensors, phenomena, observations etc. using thematic, temporal, and spatial filtering.
Author: Daniel Nuest [cre, aut] (<https://orcid.org/0000-0002-0024-5046>), Edzer Pebesma [ctb] (<https://orcid.org/0000-0001-8049-7069>), Ben Graeler [ctb] (<https://orcid.org/0000-0001-5443-4304>), Benjamin Pross [ctb], Eike Hinderk Juerrens [ctb], 52°North Initiative for Geospatial Open Source Software GmbH [cph]
Maintainer: Daniel Nuest <daniel.nuest@uni-muenster.de>

Diff between sos4R versions 0.3.0 dated 2019-04-13 and 0.3.1 dated 2019-08-09

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New package scrypt with initial version 0.1.3
Package: scrypt
Type: Package
Title: Key Derivation Functions for R Based on Scrypt
Version: 0.1.3
Authors@R: c( person("Bob", "Jansen", email = "bobjansen@gmail.com", role = c("ctb", "cre")), person("Andy", "Kipp", email = "andy@rstudio.com", role = c("aut")), person("Colin", "Percival", role = c("aut", "cph")), person(family = "RStudio", role = "cph") )
Copyright: RStudio, Inc.; Colin Percival
Maintainer: Bob Jansen <bobjansen@gmail.com>
Description: Functions for working with the scrypt key derivation functions originally described by Colin Percival <https://www.tarsnap.com/scrypt/scrypt.pdf> and in Percival and Josefsson (2016) <doi:10.17487/RFC7914>. Scrypt is a password-based key derivation function created by Colin Percival. The algorithm was specifically designed to make it costly to perform large-scale custom hardware attacks by requiring large amounts of memory.
License: FreeBSD
Depends: R (>= 3.0.0)
URL: https://github.com/rstudio/rscrypt
Imports: Rcpp (>= 0.10.6)
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2019-07-21 16:15:29 UTC; brj
Author: Bob Jansen [ctb, cre], Andy Kipp [aut], Colin Percival [aut, cph], RStudio [cph]
Repository: CRAN
Date/Publication: 2019-08-09 13:30:08 UTC

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New package interimApp with initial version 0.0.1
Package: interimApp
Title: App for Scheduling Interim Analyses in Clinical Trials
Version: 0.0.1
Author: Bastian Becker, Katharina Mueller, Hermann Kulmann
Maintainer: Bastian Becker <bastian.becker@bayer.com>
Description: Allows an interactive assessment of the timing of interim analyses. The algorithm simulates both the recruitment and treatment/event phase of a clinical trial based on the package 'interim'.
License: GPL
Encoding: UTF-8
LazyData: true
Depends: interim, shiny, shinyBS
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2019-08-08 14:12:19 UTC; EUFIB
Repository: CRAN
Date/Publication: 2019-08-09 13:40:02 UTC

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Package xml2 updated to version 1.2.2 with previous version 1.2.1 dated 2019-07-29

Title: Parse XML
Description: Work with XML files using a simple, consistent interface. Built on top of the 'libxml2' C library.
Author: Hadley Wickham [aut], Jim Hester [aut, cre], Jeroen Ooms [aut], RStudio [cph], R Foundation [ctb] (Copy of R-project homepage cached as example)
Maintainer: Jim Hester <jim.hester@rstudio.com>

Diff between xml2 versions 1.2.1 dated 2019-07-29 and 1.2.2 dated 2019-08-09

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 MD5                        |   19 ++++++++++---------
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 11 files changed, 71 insertions(+), 30 deletions(-)

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New package tabulog with initial version 0.1.1
Package: tabulog
Type: Package
Title: Parsing Semi-Structured Log Files into Tabular Format
Version: 0.1.1
Author: Austin Nar
Maintainer: Austin Nar <austin.nar@gmail.com>
Description: Convert semi-structured log files (such as 'Apache' access.log files) into a tabular format (data.frame) using a standard template system.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: yaml
Suggests: lubridate, knitr, readr
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-08 23:26:40 UTC; nar
Repository: CRAN
Date/Publication: 2019-08-09 13:00:02 UTC

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Package Rtts (with last version 0.3.3) was removed from CRAN

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

2015-11-07 0.3.3
2015-09-01 0.3.2
2015-06-03 0.3.1
2015-05-26 0.2.5

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Package muHVT (with last version 0.2.1) was removed from CRAN

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

2018-08-17 0.2.1
2018-07-09 0.2.0
2018-05-14 0.1.0

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Package gripp (with last version 0.2.19) was removed from CRAN

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

2019-07-26 0.2.19
2019-07-24 0.1.19

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New package spatstat.Knet with initial version 1.11-2
Package: spatstat.Knet
Type: Package
Title: Extension to 'spatstat' for Large Datasets on a Linear Network
Version: 1.11-2
Date: 2019-08-09
Depends: R (>= 3.3.0), spatstat (>= 1.60-0)
Imports: spatstat.utils, Matrix
Authors@R: c(person(given="Suman", family="Rakshit", role = c("aut", "cph"), email = "suman.rakshit@curtin.edu.au", comment=c(ORCID="0000-0003-0052-128X")), person(given="Adrian", family="Baddeley", role = c("cre", "cph"), email = "Adrian.Baddeley@curtin.edu.au", comment = c(ORCID="0000-0001-9499-8382")))
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>
Description: Extension to the 'spatstat' package, for analysing large datasets of spatial points on a network. Provides a memory-efficient algorithm for computing the geometrically-corrected K function, described in S. Rakshit, A. Baddeley and G. Nair (2019) <doi:10.18637/jss.v090.i01>
License: GPL (>= 2)
NeedsCompilation: yes
ByteCompile: true
Packaged: 2019-08-09 07:15:42 UTC; adrian
Author: Suman Rakshit [aut, cph] (<https://orcid.org/0000-0003-0052-128X>), Adrian Baddeley [cre, cph] (<https://orcid.org/0000-0001-9499-8382>)
Repository: CRAN
Date/Publication: 2019-08-09 11:40:02 UTC

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New package VOSONDash with initial version 0.4.4
Package: VOSONDash
Version: 0.4.4
Title: User Interface for Collecting and Analysing Social Networks
Description: A 'Shiny' application for the interactive visualisation and analysis of networks that also provides a web interface for collecting social media data using 'vosonSML'.
Type: Package
Imports: shiny (>= 1.3.2), magrittr, igraph (>= 1.2.2), rtweet (>= 0.6.8), vosonSML (>= 0.27.0), RColorBrewer, tm, wordcloud, syuzhet, httr, utils, graphics, lattice, httpuv
Depends: R (>= 3.2.0)
Encoding: UTF-8
Author: Bryan Gertzel, Robert Ackland
Maintainer: Bryan Gertzel <bryan.gertzel@anu.edu.au>
License: GPL (>= 3)
RoxygenNote: 6.1.1
NeedsCompilation: no
URL: https://github.com/vosonlab/VOSONDash
BugReports: https://github.com/vosonlab/VOSONDash/issues
Packaged: 2019-08-08 13:01:10 UTC; blue
Repository: CRAN
Date/Publication: 2019-08-09 10:20:03 UTC

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New package valetr with initial version 0.1.0
Package: valetr
Version: 0.1.0
Title: Interface to Bank of Canada's 'Valet' API
Authors@R: person("José", "de Mello", role=c("aut", "cre"), email="zedemellonetto@gmail.com")
Depends: R (>= 3.1.0)
Imports: jsonlite (>= 0.9), curl
Suggests: knitr, rmarkdown, data.table, ggplot2
VignetteBuilder: knitr
Maintainer: José de Mello <zedemellonetto@gmail.com>
Description: Interface to Bank of Canada's 'Valet' API (<https://www.bankofcanada.ca/valet/docs>). Please read the API terms and conditions: <https://www.bankofcanada.ca/terms/>.
License: GPL-3
URL: https://github.com/jdemello/valetr
BugReports: https://github.com/jdemello/valetr/issues
Encoding: UTF-8
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-08 14:38:30 UTC; jdemello
Author: José de Mello [aut, cre]
Repository: CRAN
Date/Publication: 2019-08-09 10:50:02 UTC

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New package thurstonianIRT with initial version 0.9.0
Package: thurstonianIRT
Encoding: UTF-8
Type: Package
Title: Thurstonian IRT Models
Version: 0.9.0
Date: 2019-08-07
Authors@R: c(person("Paul-Christian", "Bürkner", email = "paul.buerkner@gmail.com", role = c("aut", "cre")), person("Trustees of Columbia University", role = "cph"))
Description: Fit Thurstonian Item Response Theory (IRT) models in R. This package supports fitting Thurstonian IRT models and its extensions using 'Stan', 'lavaan', or 'Mplus' for the model estimation. Functionality for extracting results and simulating data is provided as well. References: Brown & Maydeu-Olivares (2011) <doi:10.1177/0013164410375112>; Bürkner et al. (2019) <doi:10.1177/0013164419832063>.
License: GPL (>= 3)
LazyData: true
ByteCompile: true
Depends: R (>= 3.2.0), Rcpp (>= 0.12.16), methods
Imports: rstan (>= 2.17.3), rstantools (>= 1.5.0), lavaan (>= 0.6-1), MplusAutomation, dplyr (>= 0.6.0), tibble (>= 1.3.1), tidyr, magrittr, mvtnorm, utils, stats, rlang
Suggests: testthat (>= 0.9.1),
LinkingTo: StanHeaders (>= 2.17.2), rstan (>= 2.17.3), BH (>= 1.66.0-1), Rcpp (>= 0.12.16), RcppEigen (>= 0.3.3.4.0)
SystemRequirements: GNU make
URL: https://github.com/paul-buerkner/thurstonianIRT
BugReports: https://github.com/paul-buerkner/thurstonianIRT/issues
NeedsCompilation: yes
RoxygenNote: 6.1.1
Packaged: 2019-08-08 14:24:48 UTC; paulb
Author: Paul-Christian Bürkner [aut, cre], Trustees of Columbia University [cph]
Maintainer: Paul-Christian Bürkner <paul.buerkner@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-09 10:40:02 UTC

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New package protag with initial version 1.0.0
Package: protag
Title: Search Tagged Peptides & Draw Highlighted Mass Spectra
Version: 1.0.0
Authors@R: person(given = "Bo", family = "Yuan", role = c("aut", "cre"), email = "yuanbo.faith@gmail.com")
Description: In a typical protein labelling procedure, proteins are chemically tagged with a functional group, usually at specific sites, then digested into peptides, which are then analyzed using matrix-assisted laser desorption ionization - time of flight mass spectrometry (MALDI-TOF MS) to generate peptide fingerprint. Relative to the control, peptides that are heavier by the mass of the labelling group are informative for sequence determination. Searching for peptides with such mass shifts, however, can be difficult. This package, designed to tackle this inconvenience, takes as input the mass list of two or multiple MALDI-TOF MS mass lists, and makes pairwise comparisons between the labeled groups vs. control, and restores centroid mass spectra with highlighted peaks of interest for easier visual examination. Particularly, peaks differentiated by the mass of the labelling group are defined as a “pair”, those with equal masses as a “match”, and all the other peaks as a “mismatch”.For more bioanalytical background information, refer to following publications: Jingjing Deng (2015) <doi:10.1007/978-1-4939-2550-6_19>; Elizabeth Chang (2016) <doi:10.7171/jbt.16-2702-002>.
Depends: R (>= 2.10)
Imports: ggplot2, dplyr, RColorBrewer, grDevices
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-08-08 00:17:47 UTC; Boyuan
Author: Bo Yuan [aut, cre]
Maintainer: Bo Yuan <yuanbo.faith@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-09 10:10:02 UTC

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New package PPMR with initial version 1.0
Package: PPMR
Title: Probabilistic Two Sample Mendelian Randomization
Type: Package
Version: 1.0
Authors@R: c( person(given = "Zhongshang", family = "Yuan", role = c("aut")), person(given = "Xiang", family = "Zhou", role = c("aut"), email = "xzhousph@umich.edu"), person(given = "Michael", family = "Kleinsasser", role = c("cre"), email = "mkleinsa@umich.edu"))
Description: Efficient statistical inference of two-sample MR (Mendelian Randomization) analysis. It can account for the correlated instruments and the horizontal pleiotropy, and can provide the accurate estimates of both causal effect and horizontal pleiotropy effect as well as the two corresponding p-values. There are two main functions in the 'PPMR' package. One is PMR_individual() for individual level data, the other is PMR_summary() for summary data.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: Rcpp (>= 1.0.0)
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 6.1.1.9000
NeedsCompilation: yes
BugReports: https://github.com/umich-biostatistics/PPMR/issues
Packaged: 2019-08-08 13:46:00 UTC; mkleinsa
Author: Zhongshang Yuan [aut], Xiang Zhou [aut], Michael Kleinsasser [cre]
Maintainer: Michael Kleinsasser <mkleinsa@umich.edu>
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2019-08-09 10:20:07 UTC

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New package grainscape with initial version 0.4.0
Package: grainscape
Type: Package
Title: Landscape Connectivity, Habitat, and Protected Area Networks
Description: Given a landscape resistance surface, creates grains of connectivity (Galpern et al. (2012) <doi:10.1111/j.1365-294X.2012.05677.x>) and minimum planar graph (Fall et al. (2007) <doi:10.1007/s10021-007-9038-7>) models that can be used to calculate effective distances for landscape connectivity at multiple scales.
URL: https://achubaty.github.io/grainscape, https://github.com/achubaty/grainscape
Version: 0.4.0
Date: 2019-08-06
Authors@R: c( person("Paul", "Galpern", email = "pgalpern@gmail.com", role = c("aut", "cph")), person("Sam", "Doctolero", email = "sam.doctolero@gmail.com", role = "aut"), person("Alex M", "Chubaty", email = "alex.chubaty@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-7146-8135")) )
License: GPL (>= 2)
Imports: ggplot2, graphics, grDevices, igraph, methods, sp, raster, Rcpp (>= 0.12.11.4), rgdal, utils
LinkingTo: Rcpp
Suggests: cowplot, ggthemes, hunspell, knitr, parallel, rgeos, rmarkdown, spelling, testthat
VignetteBuilder: knitr, rmarkdown
BugReports: https://github.com/achubaty/grainscape/issues
ByteCompile: yes
Collate: 'grainscape-package.R' 'classes.R' 'GOC.R' 'MPG.R' 'RcppExports.R' 'grain.R' 'corridor.R' 'deprecated.R' 'distance.R' 'export.R' 'extract.R' 'ggGS.R' 'graphdf.R' 'habitatConnectivityEngine.R' 'patchFilter.R' 'plot.R' 'point.R' 'theme_grainscape.R' 'threshold.R' 'zzz.R'
Encoding: UTF-8
Language: en-CA
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-08-08 14:13:50 UTC; achubaty
Author: Paul Galpern [aut, cph], Sam Doctolero [aut], Alex M Chubaty [aut, cre] (<https://orcid.org/0000-0001-7146-8135>)
Maintainer: Alex M Chubaty <alex.chubaty@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-09 10:30:02 UTC

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Package ggforce updated to version 0.3.0 with previous version 0.2.2 dated 2019-04-23

Title: Accelerating 'ggplot2'
Description: The aim of 'ggplot2' is to aid in visual data investigations. This focus has led to a lack of facilities for composing specialised plots. 'ggforce' aims to be a collection of mainly new stats and geoms that fills this gap. All additional functionality is aimed to come through the official extension system so using 'ggforce' should be a stable experience.
Author: Thomas Lin Pedersen [cre, aut] (<https://orcid.org/0000-0002-5147-4711>), RStudio [cph]
Maintainer: Thomas Lin Pedersen <thomasp85@gmail.com>

Diff between ggforce versions 0.2.2 dated 2019-04-23 and 0.3.0 dated 2019-08-09

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New package cyanoFilter with initial version 0.1.1
Package: cyanoFilter
Title: Cyanobacteria Population Identification for Flow Cytometry
Version: 0.1.1
Authors@R: c(person("Oluwafemi", "Olusoji", email = "oluwafemi.olusoji@uhasselt.be", role = c("aut", "cre")), person("Aerts", "Marc", email = "marc.aerts@uhasselt.be", role = "ctb"), person("Delaender", "Frederik", email = "frederik.delaender@unamur.be", role = "ctb"), person("Neyens", "Thomas", email = "thomas.neyens@uhasselt.be", role = "ctb"), person("Spaak", "jurg", email = "jurg.spaak@unamur.be", role = "aut"))
Maintainer: Oluwafemi Olusoji <oluwafemi.olusoji@uhasselt.be>
Description: An approach to filter out and/or identify two synechococcus type cyanobacteria cells from all particles measured via flow cytometry. It combines known characteristics of these two cyanobacteria strains (BS4 and BS5) alongside gating techniques developed by Mehrnoush, M. et al. (2015) <doi:10.1093/bioinformatics/btu677> in the 'flowDensity' package to identify and separate these cyanobacteria cells from other cell types. Aside the gating techniques in the 'flowDensity' package, an EM style clustering technique is also developed to identify these cyanobacteria cell populations.
URL: https://github.com/fomotis/cyanoFilter
BugReports: https://github.com/fomotis/cyanoFilter/issues
Depends: R(>= 3.4), Biobase(>= 2.40.0)
Imports: flowCore(>= 1.42.3), flowDensity (>= 1.10.0), graphics(>= 3.6.0), grDevices(>= 3.6.0), methods(>= 3.5.1), RColorBrewer(>= 1.1-2), Rdpack(>= 0.11-0), stats(>= 3.6.0), stringr(>= 1.3.1), utils(>= 3.6.0)
RdMacros: Rdpack
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: dplyr, magrittr, knitr, rmarkdown, tidyr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-08 13:35:48 UTC; lucp9544
Author: Oluwafemi Olusoji [aut, cre], Aerts Marc [ctb], Delaender Frederik [ctb], Neyens Thomas [ctb], Spaak jurg [aut]
Repository: CRAN
Date/Publication: 2019-08-09 10:30:06 UTC

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New package BESTree with initial version 0.5.2
Package: BESTree
Type: Package
Title: Branch-Exclusive Splits Trees
Version: 0.5.2
Authors@R: person("Beaulac", "Cedric", email = "cedric@utstat.toronto.edu", role = c("aut", "cre"))
Description: Decision tree algorithm with a major feature added. Allows for users to define an ordering on the partitioning process. Resulting in Branch-Exclusive Splits Trees (BEST). Cedric Beaulac and Jeffrey S. Rosentahl (2019) <arXiv:1804.10168>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: plyr, compiler, utils, stats
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, testthat
Depends: R (>= 2.10)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-08 16:22:38 UTC; The Beast
Author: Beaulac Cedric [aut, cre]
Maintainer: Beaulac Cedric <cedric@utstat.toronto.edu>
Repository: CRAN
Date/Publication: 2019-08-09 11:00:02 UTC

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Package FrF2 updated to version 2.0 with previous version 1.7-3 dated 2019-05-03

Title: Fractional Factorial Designs with 2-Level Factors
Description: Regular and non-regular Fractional Factorial 2-level designs can be created. Furthermore, analysis tools for Fractional Factorial designs with 2-level factors are offered (main effects and interaction plots for all factors simultaneously, cube plot for looking at the simultaneous effects of three factors, full or half normal plot, alias structure in a more readable format than with the built-in function alias).
Author: Ulrike Groemping
Maintainer: Ulrike Groemping <groemping@beuth-hochschule.de>

Diff between FrF2 versions 1.7-3 dated 2019-05-03 and 2.0 dated 2019-08-09

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Package tidytree updated to version 0.2.6 with previous version 0.2.5 dated 2019-07-22

Title: A Tidy Tool for Phylogenetic Tree Data Manipulation
Description: Phylogenetic tree generally contains multiple components including node, edge, branch and associated data. 'tidytree' provides an approach to convert tree object to tidy data frame as well as provides tidy interfaces to manipulate tree data.
Author: Guangchuang Yu [aut, cre, cph] (<https://orcid.org/0000-0002-6485-8781>), Bradley Jones [ctb], Zebulun Arendsee [ctb]
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>

Diff between tidytree versions 0.2.5 dated 2019-07-22 and 0.2.6 dated 2019-08-09

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Package greta updated to version 0.3.1 with previous version 0.3.0 dated 2018-10-30

Title: Simple and Scalable Statistical Modelling in R
Description: Write statistical models in R and fit them by MCMC and optimisation on CPUs and GPUs, using Google 'TensorFlow'. greta lets you write your own model like in BUGS, JAGS and Stan, except that you write models right in R, it scales well to massive datasets, and it’s easy to extend and build on. See the website for more information, including tutorials, examples, package documentation, and the greta forum.
Author: Nick Golding [aut, cre] (<https://orcid.org/0000-0001-8916-5570>), Simon Dirmeier [ctb], Adam Fleischhacker [ctb], Shirin Glander [ctb], Martin Ingram [ctb], Lee Hazel [ctb], Tiphaine Martin [ctb], Matt Mulvahill [ctb], Michael Quinn [ctb], David Smith [ctb], Paul Teetor [ctb], Jian Yen [ctb]
Maintainer: Nick Golding <nick.golding.research@gmail.com>

Diff between greta versions 0.3.0 dated 2018-10-30 and 0.3.1 dated 2019-08-09

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