Fri, 10 Jan 2020

Package sparklyr updated to version 1.1.0 with previous version 1.0.5 dated 2019-11-14

Title: R Interface to Apache Spark
Description: R interface to Apache Spark, a fast and general engine for big data processing, see <http://spark.apache.org>. This package supports connecting to local and remote Apache Spark clusters, provides a 'dplyr' compatible back-end, and provides an interface to Spark's built-in machine learning algorithms.
Author: Javier Luraschi [aut, cre], Kevin Kuo [aut] (<https://orcid.org/0000-0001-7803-7901>), Kevin Ushey [aut], JJ Allaire [aut], Samuel Macedo [ctb], RStudio [cph], The Apache Software Foundation [aut, cph]
Maintainer: Javier Luraschi <javier@rstudio.com>

Diff between sparklyr versions 1.0.5 dated 2019-11-14 and 1.1.0 dated 2020-01-10

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 sparklyr-1.1.0/sparklyr/MD5                                                     |  264 ++++------
 sparklyr-1.1.0/sparklyr/NAMESPACE                                               |    4 
 sparklyr-1.1.0/sparklyr/NEWS.md                                                 |   35 +
 sparklyr-1.1.0/sparklyr/R/config_settings.R                                     |    2 
 sparklyr-1.1.0/sparklyr/R/connection_spark.R                                    |    6 
 sparklyr-1.1.0/sparklyr/R/data_interface.R                                      |    8 
 sparklyr-1.1.0/sparklyr/R/dbi_spark_connection.R                                |    5 
 sparklyr-1.1.0/sparklyr/R/dplyr_spark_data.R                                    |    2 
 sparklyr-1.1.0/sparklyr/R/install_spark.R                                       |   11 
 sparklyr-1.1.0/sparklyr/R/install_spark_versions.R                              |   22 
 sparklyr-1.1.0/sparklyr/R/livy_connection.R                                     |   32 -
 sparklyr-1.1.0/sparklyr/R/livy_install.R                                        |   11 
 sparklyr-1.1.0/sparklyr/R/ml_clustering_bisecting_kmeans.R                      |   10 
 sparklyr-1.1.0/sparklyr/R/ml_clustering_kmeans.R                                |   22 
 sparklyr-1.1.0/sparklyr/R/ml_feature_one_hot_encoder.R                          |  131 +++-
 sparklyr-1.1.0/sparklyr/R/ml_feature_one_hot_encoder_estimator.R                |    2 
 sparklyr-1.1.0/sparklyr/R/ml_feature_quantile_discretizer.R                     |   12 
 sparklyr-1.1.0/sparklyr/R/ml_model_kmeans.R                                     |   20 
 sparklyr-1.1.0/sparklyr/R/sdf_utils.R                                           |    2 
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 sparklyr-1.1.0/sparklyr/R/spark_compile.R                                       |   20 
 sparklyr-1.1.0/sparklyr/R/spark_extensions.R                                    |   12 
 sparklyr-1.1.0/sparklyr/R/stream_data.R                                         |  146 ++++-
 sparklyr-1.1.0/sparklyr/R/tidiers_ml_linear_models.R                            |    2 
 sparklyr-1.1.0/sparklyr/R/tidiers_ml_unsupervised_models.R                      |   13 
 sparklyr-1.1.0/sparklyr/R/utils.R                                               |   26 
 sparklyr-1.1.0/sparklyr/R/worker_apply.R                                        |   18 
 sparklyr-1.1.0/sparklyr/README.md                                               |   70 +-
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 sparklyr-1.1.0/sparklyr/inst/java/sparklyr-1.6-2.10.jar                         |binary
 sparklyr-1.1.0/sparklyr/inst/java/sparklyr-2.0-2.11.jar                         |binary
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 sparklyr-1.1.0/sparklyr/java/spark-1.6.0/workerhelper.scala                     |   17 
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 sparklyr-1.1.0/sparklyr/tests/testthat/test-broom-lda.R                         |    1 
 sparklyr-1.1.0/sparklyr/tests/testthat/test-broom-multilayer_perceptron.R       |    1 
 sparklyr-1.1.0/sparklyr/tests/testthat/test-broom-naive_bayes.R                 |    1 
 sparklyr-1.1.0/sparklyr/tests/testthat/test-dplyr-lead-lag.R                    |    1 
 sparklyr-1.1.0/sparklyr/tests/testthat/test-feature-one-hot-encoder-estimator.R |    6 
 sparklyr-1.1.0/sparklyr/tests/testthat/test-invoke.R                            |    1 
 sparklyr-1.1.0/sparklyr/tests/testthat/test-kubernetes-config.R                 |    1 
 sparklyr-1.1.0/sparklyr/tests/testthat/test-ml-classification-naive-bayes.R     |    2 
 sparklyr-1.1.0/sparklyr/tests/testthat/test-ml-clustering-kmeans-ext.R          |   29 -
 sparklyr-1.1.0/sparklyr/tests/testthat/test-ml-evaluation.R                     |    1 
 sparklyr-1.1.0/sparklyr/tests/testthat/test-ml-feature-idf.R                    |    1 
 sparklyr-1.1.0/sparklyr/tests/testthat/test-ml-feature-imputer.R                |    1 
 sparklyr-1.1.0/sparklyr/tests/testthat/test-ml-feature-one-hot-encoder.R        |   53 +-
 sparklyr-1.1.0/sparklyr/tests/testthat/test-ml-feature-quantile-discretizer.R   |    2 
 sparklyr-1.1.0/sparklyr/tests/testthat/test-ml-feature-r-formula.R              |    1 
 sparklyr-1.1.0/sparklyr/tests/testthat/test-ml-feature-word2vec.R               |    1 
 sparklyr-1.1.0/sparklyr/tests/testthat/test-read-write.R                        |   59 ++
 sparklyr-1.1.0/sparklyr/tests/testthat/test-serialization.R                     |    2 
 sparklyr-1.1.0/sparklyr/tests/testthat/test-spark-apply-ext.R                   |    1 
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 123 files changed, 1260 insertions(+), 662 deletions(-)

More information about sparklyr at CRAN
Permanent link

Package pmml updated to version 2.2.0 with previous version 2.1.0 dated 2019-09-13

Title: Generate PMML for Various Models
Description: The Predictive Model Markup Language (PMML) is an XML-based language which provides a way for applications to define machine learning, statistical and data mining models and to share models between PMML compliant applications. More information about the PMML industry standard and the Data Mining Group can be found at <http://www.dmg.org>. The generated PMML can be imported into any PMML consuming application, such as Zementis Predictive Analytics products, which integrate with web services, relational database systems and deploy natively on Hadoop in conjunction with Hive, Spark or Storm, as well as allow predictive analytics to be executed for IBM z Systems mainframe applications and real-time, streaming analytics platforms. The package isofor (used for anomaly detection) can be installed with devtools::install_github("Zelazny7/isofor").
Author: Dmitriy Bolotov [aut, cre], Tridivesh Jena [aut], Graham Williams [aut], Wen-Ching Lin [aut], Michael Hahsler [aut], Hemant Ishwaran [aut], Udaya B. Kogalur [aut], Rajarshi Guha [aut], Software AG [cph]
Maintainer: Dmitriy Bolotov <dmitriy.bolotov@softwareag.com>

Diff between pmml versions 2.1.0 dated 2019-09-13 and 2.2.0 dated 2020-01-10

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 pmml-2.2.0/pmml/MD5                                                |  194 +++---
 pmml-2.2.0/pmml/NEWS.md                                            |   15 
 pmml-2.2.0/pmml/R/add_attributes.R                                 |    2 
 pmml-2.2.0/pmml/R/add_data_field_attributes.R                      |    2 
 pmml-2.2.0/pmml/R/add_data_field_children.R                        |    2 
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 100 files changed, 970 insertions(+), 475 deletions(-)

More information about pmml at CRAN
Permanent link

Package NetworkToolbox updated to version 1.3.3 with previous version 1.3.2 dated 2019-10-28

Title: Methods and Measures for Brain, Cognitive, and Psychometric Network Analysis
Description: Implements network analysis and graph theory measures used in neuroscience, cognitive science, and psychology. Methods include various filtering methods and approaches such as threshold, dependency (Kenett, Tumminello, Madi, Gur-Gershgoren, Mantegna, & Ben-Jacob, 2010 <doi:10.1371/journal.pone.0015032>), Information Filtering Networks (Barfuss, Massara, Di Matteo, & Aste, 2016 <doi:10.1103/PhysRevE.94.062306>), and Efficiency-Cost Optimization (Fallani, Latora, & Chavez, 2017 <doi:10.1371/journal.pcbi.1005305>). Brain methods include the recently developed Connectome Predictive Modeling (see references in package). Also implements several network measures including local network characteristics (e.g., centrality), community-level network characteristics (e.g., community centrality), global network characteristics (e.g., clustering coefficient), and various other measures associated with the reliability and reproducibility of network analysis.
Author: Alexander Christensen [aut, cre] (<https://orcid.org/0000-0002-9798-7037>), Guido Previde Massara [ctb] (<https://orcid.org/0000-0003-0502-2789>)
Maintainer: Alexander Christensen <alexpaulchristensen@gmail.com>

Diff between NetworkToolbox versions 1.3.2 dated 2019-10-28 and 1.3.3 dated 2020-01-10

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More information about NetworkToolbox at CRAN
Permanent link

Package ldat updated to version 0.3.0 with previous version 0.2.0 dated 2018-05-24

Title: Large Data Sets
Description: Tools for working with vectors and data sets that are too large to keep in memory. Extends the basic functionality provided in the 'lvec' package. Provides basis statistical functionality of 'lvec' objects, such as arithmetic operations and calculating means and sums. Also implements 'data.frame'-like objects storing its data in 'lvec' objects.
Author: Jan van der Laan
Maintainer: Jan van der Laan <r@eoos.dds.nl>

Diff between ldat versions 0.2.0 dated 2018-05-24 and 0.3.0 dated 2020-01-10

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More information about ldat at CRAN
Permanent link

Package zipangu updated to version 0.2.0 with previous version 0.1.0 dated 2019-12-01

Title: Japanese Utility Functions and Data
Description: Some data treated by the Japanese R user require unique operations and processing. These are caused by address, Kanji, and traditional year representations. 'zipangu' transforms specific to Japan into something more general one.
Author: Shinya Uryu [aut, cre] (<https://orcid.org/0000-0002-0493-6186>)
Maintainer: Shinya Uryu <suika1127@gmail.com>

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More information about zipangu at CRAN
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Package shinymaterial updated to version 1.0.0 with previous version 0.5.5 dated 2019-03-03

Title: Implement Material Design in Shiny Applications
Description: Allows shiny developers to incorporate UI elements based on Google's Material design. See <https://material.io/guidelines/> for more information.
Author: Eric Anderson [aut, cre], Alvin Wang [ctb, cph] (Materialize CSS library), Alan Chang [ctb, cph] (Materialize CSS library), Alex Mark [ctb, cph] (Materialize CSS library), Kevin Louie [ctb, cph] (Materialize CSS library)
Maintainer: Eric Anderson <eric.ray.anderson@gmail.com>

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More information about shinymaterial at CRAN
Permanent link

Package RxODE updated to version 0.9.1-9 with previous version 0.9.1-8 dated 2019-11-12

Title: Facilities for Simulating from ODE-Based Models
Description: Facilities for running simulations from ordinary differential equation (ODE) models, such as pharmacometrics and other compartmental models. A compilation manager translates the ODE model into C, compiles it, and dynamically loads the object code into R for improved computational efficiency. An event table object facilitates the specification of complex dosing regimens (optional) and sampling schedules. NB: The use of this package requires both C and Fortran compilers, for details on their use with R please see Section 6.3, Appendix A, and Appendix D in the "R Administration and Installation" manual. Also the code is mostly released under GPL. The VODE and LSODA are in the public domain. The information is available in the inst/COPYRIGHTS.
Author: Matthew L. Fidler [aut] (<https://orcid.org/0000-0001-8538-6691>), Melissa Hallow [aut], Wenping Wang [aut, cre], Zufar Mulyukov [ctb], Justin Wilkins [ctb] (<https://orcid.org/0000-0002-7099-9396>), Simon Frost [ctb], Goro Fuji [ctb], Morwenn [ctb], Heng Li [ctb], Yu Feng [ctb], Alan Hindmarsh [ctb], Linda Petzold [ctb], Ernst Hairer [ctb], Gerhard Wanner [ctb], J Colinge [ctb], Hadley Wickham [ctb], G Grothendieck [ctb], Robert Gentleman [ctb], Daniel C. Dillon [ctb], Ross Ihaka [ctb], Cleve Moler [ctb], Jack Dongarra [ctb], R core team [cph]
Maintainer: Wenping Wang <wwang8198@gmail.com>

Diff between RxODE versions 0.9.1-8 dated 2019-11-12 and 0.9.1-9 dated 2020-01-10

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More information about RxODE at CRAN
Permanent link

Package qrandom updated to version 1.2.2 with previous version 1.2.1 dated 2019-12-11

Title: True Random Numbers using the ANU Quantum Random Numbers Server
Description: The ANU Quantum Random Number Generator provided by the Australian National University generates true random numbers in real-time by measuring the quantum fluctuations of the vacuum. This package offers an interface using their API. The electromagnetic field of the vacuum exhibits random fluctuations in phase and amplitude at all frequencies. By carefully measuring these fluctuations, one is able to generate ultra-high bandwidth random numbers. The quantum Random Number Generator is based on the papers by Symul et al., (2011) <doi:10.1063/1.3597793> and Haw, et al. (2015) <doi:10.1103/PhysRevApplied.3.054004>. The package offers functions to retrieve a sequence of random integers or hexadecimals and true random samples from a normal or uniform distribution.
Author: Siegfried Köstlmeier [aut, cre] (<https://orcid.org/0000-0002-7221-6981>), Boris Steipe [ctb] (<https://orcid.org/0000-0002-1134-6758>)
Maintainer: Siegfried Köstlmeier <siegfried.koestlmeier@gmail.com>

Diff between qrandom versions 1.2.1 dated 2019-12-11 and 1.2.2 dated 2020-01-10

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 tests/testthat/test-qrandommaxint.R |    5 +----
 tests/testthat/test-qrandomnorm.R   |    6 ++----
 tests/testthat/test-qrandomunif.R   |    5 +----
 12 files changed, 56 insertions(+), 45 deletions(-)

More information about qrandom at CRAN
Permanent link

Package knnp updated to version 2.0.0 with previous version 1.0.0 dated 2018-07-01

Title: Time Series Prediction using K-Nearest Neighbors Algorithm (Parallel)
Description: Two main functionalities are provided. One of them is predicting values with k-nearest neighbors algorithm and the other is optimizing the parameters k and d of the algorithm. These are carried out in parallel using multiple threads.
Author: Daniel Bastarrica Lacalle [aut, cre], Javier Berdecio Trigueros [aut], Javier Arroyo Gallardo [aut], Albert Meco Alias [aut]
Maintainer: Daniel Bastarrica Lacalle <danibast@ucm.es>

Diff between knnp versions 1.0.0 dated 2018-07-01 and 2.0.0 dated 2020-01-10

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More information about knnp at CRAN
Permanent link

Package gRbase updated to version 1.8-5.1 with previous version 1.8-4.5 dated 2019-09-28

Title: A Package for Graphical Modelling in R
Description: The 'gRbase' package provides graphical modelling features used by e.g. the packages 'gRain', 'gRim' and 'gRc'. 'gRbase' contains data sets relevant for use in connection with graphical models (in particular all data sets used in the book Graphical Models with R (2012)). 'gRbase' implements graph algorithms including (i) maximum cardinality search (for marked and unmarked graphs). (ii) moralize. (iii) triangulate. (iv) junction tree. 'gRbase' facilitates array operations, 'gRbase' implements functions for testing for conditional independence. 'gRbase' illustrates how hierarchical log-linear models may be implemented and describes concept of graphical meta data. These features, however, are not maintained anymore and remains in 'gRbase' only because there exists a paper describing these facilities: A Common Platform for Graphical Models in R: The 'gRbase' Package, Journal of Statistical Software, Vol 14, No 17, 2005. NOTICE 'gRbase' requires that the packages graph, 'Rgraphviz' and 'RBGL' are installed from 'bioconductor'; for installation instructions please refer to the web page given below.
Author: Søren Højsgaard <sorenh@math.aau.dk>
Maintainer: Søren Højsgaard <sorenh@math.aau.dk>

Diff between gRbase versions 1.8-4.5 dated 2019-09-28 and 1.8-5.1 dated 2020-01-10

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More information about gRbase at CRAN
Permanent link

Package rdrobust updated to version 0.99.5 with previous version 0.99.4 dated 2018-09-26

Title: Robust Data-Driven Statistical Inference in Regression-Discontinuity Designs
Description: Regression-discontinuity (RD) designs are quasi-experimental research designs popular in social, behavioral and natural sciences. The RD design is usually employed to study the (local) causal effect of a treatment, intervention or policy. This package provides tools for data-driven graphical and analytical statistical inference in RD designs: rdrobust() to construct local-polynomial point estimators and robust confidence intervals for average treatment effects at the cutoff in Sharp, Fuzzy and Kink RD settings, rdbwselect() to perform bandwidth selection for the different procedures implemented, and rdplot() to conduct exploratory data analysis (RD plots).
Author: Sebastian Calonico <sebastian.calonico@columbia.edu>, Matias D. Cattaneo <cattaneo@princeton.edu>, Max H. Farrell <max.farrell@chicagobooth.edu>, Rocio Titiunik <titiunik@princeton.edu>
Maintainer: Sebastian Calonico <sebastian.calonico@columbia.edu>

Diff between rdrobust versions 0.99.4 dated 2018-09-26 and 0.99.5 dated 2020-01-10

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More information about rdrobust at CRAN
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Package mleap updated to version 1.0.0 with previous version 0.1.3 dated 2018-11-01

Title: Interface to 'MLeap'
Description: A 'sparklyr' <https://spark.rstudio.com> extension that provides an interface to 'MLeap' <https://github.com/combust/mleap>, an open source library that enables exporting and serving of 'Apache Spark' pipelines.
Author: Kevin Kuo [aut, cre] (<https://orcid.org/0000-0001-7803-7901>)
Maintainer: Kevin Kuo <kevin.kuo@rstudio.com>

Diff between mleap versions 0.1.3 dated 2018-11-01 and 1.0.0 dated 2020-01-10

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Permanent link

Package EdSurvey updated to version 2.4.0 with previous version 2.3.2 dated 2019-03-29

Title: Analysis of NCES Education Survey and Assessment Data
Description: Read in and analyze functions for education survey and assessment data from the National Center for Education Statistics (NCES) <https://nces.ed.gov/>, including National Assessment of Educational Progress (NAEP) data <https://nces.ed.gov/nationsreportcard/> and data from the International Assessment Database: Organisation for Economic Co-operation and Development (OECD) <https://www.oecd.org/>, including Programme for International Student Assessment (PISA), Teaching and Learning International Survey (TALIS), Programme for the International Assessment of Adult Competencies (PIAAC), and International Association for the Evaluation of Educational Achievement (IEA) <https://www.iea.nl/>, including Trends in International Mathematics and Science Study (TIMSS), TIMSS Advanced, Progress in International Reading Literacy Study (PIRLS), International Civic and Citizenship Study (ICCS), International Computer and Information Literacy Study (ICILS), and Civic Education Study (CivEd).
Author: Paul Bailey [aut, cre], Ahmad Emad [aut], Huade Huo [aut], Michael Lee [aut], Yuqi Liao [aut], Alex Lishinski [aut], Trang Nguyen [aut], Qingshu Xie [aut], Jiao Yu [aut], Ting Zhang [aut], Jeppe Bundsgaard [ctb], Ren C'deBaca [ctb]
Maintainer: Paul Bailey <pbailey@air.org>

Diff between EdSurvey versions 2.3.2 dated 2019-03-29 and 2.4.0 dated 2020-01-10

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New package esaddle with initial version 0.0.6
Package: esaddle
Type: Package
Title: Extended Empirical Saddlepoint Density Approximations
Version: 0.0.6
Date: 2020-01-01
Author: Matteo Fasiolo and Simon N. Wood
Maintainer: Matteo Fasiolo <matteo.fasiolo@gmail.com>
Description: Tools for fitting the Extended Empirical Saddlepoint (EES) density of Fasiolo et al. (2018) <doi:10.1214/18-EJS1433>.
License: GPL (>= 2)
URL: https://github.com/mfasiolo/esaddle
Imports: compiler, stats, graphics, parallel, plyr, doParallel, mvnfast
Suggests: knitr, testthat
LinkingTo: Rcpp, RcppArmadillo
VignetteBuilder: knitr
RoxygenNote: 7.0.2
NeedsCompilation: yes
Packaged: 2020-01-10 16:54:02 UTC; teo
Repository: CRAN
Date/Publication: 2020-01-10 22:50:02 UTC

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New package coxed with initial version 0.3.2
Package: coxed
Type: Package
Title: Duration-Based Quantities of Interest for the Cox Proportional Hazards Model
Version: 0.3.2
Depends: R (>= 3.5.0), rms, survival, mgcv
Authors@R: c( person("Kropko,", "Jonathan", email = "jkropko@virginia.edu", role = c("aut", "cre")), person("Harden,", "Jeffrey J.", email = "jeff.harden@nd.edu", role = c("aut")))
Description: Functions for generating, simulating, and visualizing expected durations and marginal changes in duration from the Cox proportional hazards model as described in Kropko and Harden (2017) <doi:10.1017/S000712341700045X> and Harden and Kropko (2018) <doi:10.1017/psrm.2018.19>.
License: GPL-2
Encoding: UTF-8
URL: https://github.com/jkropko/coxed
LazyData: true
Imports: PermAlgo, dplyr, tidyr, ggplot2, gridExtra, utils
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, bindrcpp
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-10 15:12:49 UTC; jk8sd
Author: Kropko, Jonathan [aut, cre], Harden, Jeffrey J. [aut]
Maintainer: "Kropko, Jonathan" <jkropko@virginia.edu>
Repository: CRAN
Date/Publication: 2020-01-10 23:00:03 UTC

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New package biomartr with initial version 0.9.2
Package: biomartr
Title: Genomic Data Retrieval
Version: 0.9.2
Authors@R: person("Hajk-Georg", "Drost", role = c("aut", "cre"), email = "hajk-georg.drost@tuebingen.mpg.de", comment = c(ORCID = "http://orcid.org/0000-0002-1567-306X"))
Description: Perform large scale genomic data retrieval and functional annotation retrieval. This package aims to provide users with a standardized way to automate genome, proteome, 'RNA', coding sequence ('CDS'), 'GFF', and metagenome retrieval from 'NCBI RefSeq', 'NCBI Genbank', 'ENSEMBL', 'ENSEMBLGENOMES', and 'UniProt' databases. Furthermore, an interface to the 'BioMart' database (Smedley et al. (2009) <doi:10.1186/1471-2164-10-22>) allows users to retrieve functional annotation for genomic loci. In addition, users can download entire databases such as 'NCBI RefSeq' (Pruitt et al. (2007) <doi:10.1093/nar/gkl842>), 'NCBI nr', 'NCBI nt', 'NCBI Genbank' (Benson et al. (2013) <doi:10.1093/nar/gks1195>), etc. as well as 'ENSEMBL' and 'ENSEMBLGENOMES' with only one command.
VignetteBuilder: knitr
NeedsCompilation: yes
Depends: R (>= 3.1.1)
Imports: biomaRt, Biostrings, curl, tibble, jsonlite, data.table (>= 1.9.4), dplyr (>= 0.3.0), readr (>= 0.2.2), downloader (>= 0.3), RCurl (>= 1.95-4.5), XML (>= 3.98-1.1), httr (>= 0.6.1), stringr (>= 0.6.2), purrr, R.utils, philentropy, fs (>= 1.3.1)
Suggests: knitr (>= 1.6), rmarkdown (>= 0.3.3), devtools (>= 1.6.1), testthat, seqinr, magrittr
License: GPL-2
LazyData: true
URL: https://docs.ropensci.org/biomartr, https://github.com/ropensci/biomartr
BugReports: https://github.com/ropensci/biomartr/issues
RoxygenNote: 7.0.2
Encoding: UTF-8
X-schema.org-keywords: BioMart, genomic-data-retrieval, annotation-retrieval, database-retrieval, NCBI, ENSEMBL, biological-data-retrieval
X-schema.org-applicationCategory: Data Access
X-schema.org-isPartof: "ropensci.org"
Packaged: 2020-01-10 15:28:22 UTC; hdrost
Author: Hajk-Georg Drost [aut, cre] (<https://orcid.org/0000-0002-1567-306X>)
Maintainer: Hajk-Georg Drost <hajk-georg.drost@tuebingen.mpg.de>
Repository: CRAN
Date/Publication: 2020-01-10 23:00:06 UTC

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Package zoo updated to version 1.8-7 with previous version 1.8-6 dated 2019-05-28

Title: S3 Infrastructure for Regular and Irregular Time Series (Z's Ordered Observations)
Description: An S3 class with methods for totally ordered indexed observations. It is particularly aimed at irregular time series of numeric vectors/matrices and factors. zoo's key design goals are independence of a particular index/date/time class and consistency with ts and base R by providing methods to extend standard generics.
Author: Achim Zeileis [aut, cre] (<https://orcid.org/0000-0003-0918-3766>), Gabor Grothendieck [aut], Jeffrey A. Ryan [aut], Joshua M. Ulrich [ctb], Felix Andrews [ctb]
Maintainer: Achim Zeileis <Achim.Zeileis@R-project.org>

Diff between zoo versions 1.8-6 dated 2019-05-28 and 1.8-7 dated 2020-01-10

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Package yonder updated to version 0.2.0 with previous version 0.1.2 dated 2019-11-22

Title: A Reactive Web Framework Built on 'shiny'
Description: Build 'shiny' applications with the latest Bootstrap components and design utilities. Includes refreshed reactive inputs and outputs. Use responsive layouts to design and construct applications for devices of all sizes.
Author: Nathan Teetor [aut, cre], The Bootstrap Authors [cph] (Bootstrap library), Twitter, Inc [cph] (Bootstrap library), JS Foundation [cph] (jQuery library), Federico Zivolo [ctb, cph] (popper.js library), Johann Servoire [ctb, cph] (bs-custom-file-input library)
Maintainer: Nathan Teetor <nathanteetor@gmail.com>

Diff between yonder versions 0.1.2 dated 2019-11-22 and 0.2.0 dated 2020-01-10

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Package xgxr updated to version 1.0.7 with previous version 1.0.6 dated 2019-12-09

Title: Exploratory Graphics for Pharmacometrics
Description: Supports a structured approach for exploring PKPD data <https://opensource.nibr.com/xgx>. It also contains helper functions for enabling the modeler to follow best R practices (by appending the program name, figure name location, and draft status to each plot). In addition, it enables the modeler to follow best graphical practices (by providing a theme that reduces chart ink, and by providing time-scale, log-scale, and reverse-log-transform-scale functions for more readable axes). Finally, it provides some data checking and summarizing functions for rapidly exploring pharmacokinetics and pharmacodynamics (PKPD) datasets.
Author: Andrew Stein [aut, cre], Alison Margolskee [aut], Fariba Khanshan [aut], Konstantin Krismer [aut] (<https://orcid.org/0000-0001-8994-3416>), Matthew Fidler [ctb] (<https://orcid.org/0000-0001-8538-6691>), Novartis Pharma AG [cph, fnd]
Maintainer: Andrew Stein <andy.stein@gmail.com>

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Package virtuoso updated to version 0.1.4 with previous version 0.1.3 dated 2019-04-06

Title: Interface to 'Virtuoso' using 'ODBC'
Description: Provides users with a simple and convenient mechanism to manage and query a 'Virtuoso' database using the 'DBI' (DataBase Interface) compatible 'ODBC' (Open Database Connectivity) interface. 'Virtuoso' is a high-performance "universal server," which can act as both a relational database, supporting standard Structured Query Language ('SQL') queries, while also supporting data following the Resource Description Framework ('RDF') model for Linked Data. 'RDF' data can be queried using 'SPARQL' ('SPARQL' Protocol and 'RDF' Query Language) queries, a graph-based query that supports semantic reasoning. This allows users to leverage the performance of local or remote 'Virtuoso' servers using popular 'R' packages such as 'DBI' and 'dplyr', while also providing a high-performance solution for working with large 'RDF' triplestores from 'R.' The package also provides helper routines to install, launch, and manage a 'Virtuoso' server locally on 'Mac', 'Windows' and 'Linux' platforms using the standard interactive installers from the 'R' command-line. By automatically handling these setup steps, the package can make using 'Virtuoso' considerably faster and easier for a most users to deploy in a local environment. Managing the bulk import of triples from common serializations with a single intuitive command is another key feature of this package. Bulk import performance can be tens to hundreds of times faster than the comparable imports using existing 'R' tools, including 'rdflib' and 'redland' packages.
Author: Carl Boettiger [aut, cre, cph] (<https://orcid.org/0000-0002-1642-628X>), Bryce Mecum [ctb] (<https://orcid.org/0000-0002-0381-3766>)
Maintainer: Carl Boettiger <cboettig@gmail.com>

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Package venn updated to version 1.9 with previous version 1.8 dated 2019-12-10

Title: Draw Venn Diagrams
Description: Draws and displays Venn diagrams up to 7 sets, and any Boolean union of set intersections.
Author: Adrian Dusa [aut, cre, cph]
Maintainer: Adrian Dusa <dusa.adrian@unibuc.ro>

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Package ROI.plugin.lpsolve updated to version 0.3-3 with previous version 0.3-2 dated 2018-12-20

Title: 'lp_solve' Plugin for the 'R' Optimization Infrastructure
Description: Enhances the 'R' Optimization Infrastructure ('ROI') package with the 'lp_solve' solver.
Author: Florian Schwendinger [aut, cre]
Maintainer: Florian Schwendinger <FlorianSchwendinger@gmx.at>

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Package MultiFit updated to version 1.0.1 with previous version 1.0.0 dated 2019-03-17

Title: Multiscale Fisher's Independence Test for Multivariate Dependence
Description: Test for independence of two random vectors, learn and report the dependency structure. For more information, see Gorsky and Ma (2018) <arXiv:1806.06777>.
Author: S. Gorsky, L. Ma
Maintainer: S. Gorsky <s.gorsky@duke.edu>

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Package DescToolsAddIns updated to version 1.6 with previous version 1.5 dated 2019-10-30

Title: Interactive Functions to be Used as Shortcuts in 'RStudio'
Description: 'RStudio' as of recently offers the option to define addins and assign shortcuts to them. This package contains addins for a few most frequently used functions in a data scientist's (at least mine) daily work (like str(), example(), plot(), head(), view(), Desc()). Most of these functions will use the current selection in the editor window and send the specific command to the console while instantly executing it. Assigning shortcuts to these addins will save you quite a few keystrokes.
Author: Andri Signorell
Maintainer: Andri Signorell <andri@signorell.net>

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Package powdR updated to version 1.1.0 with previous version 1.0.0 dated 2019-04-26

Title: Full Pattern Summation of X-Ray Powder Diffraction Data
Description: Full pattern summation of X-ray powder diffraction data as described in Chipera and Bish (2002) <doi:10.1107/S0021889802017405>. Derives quantitative estimates of crystalline and amorphous phase concentrations in complex mixtures.
Author: Benjamin Butler [aut, cre], Stephen Hillier [aut], Dylan Beaudette [ctb], Dennis Eberl [ctb]
Maintainer: Benjamin Butler <benjamin.butler@hutton.ac.uk>

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Package mlr updated to version 2.17.0 with previous version 2.16.0 dated 2019-11-26

Title: Machine Learning in R
Description: Interface to a large number of classification and regression techniques, including machine-readable parameter descriptions. There is also an experimental extension for survival analysis, clustering and general, example-specific cost-sensitive learning. Generic resampling, including cross-validation, bootstrapping and subsampling. Hyperparameter tuning with modern optimization techniques, for single- and multi-objective problems. Filter and wrapper methods for feature selection. Extension of basic learners with additional operations common in machine learning, also allowing for easy nested resampling. Most operations can be parallelized.
Author: Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>), Michel Lang [aut] (<https://orcid.org/0000-0001-9754-0393>), Lars Kotthoff [aut], Julia Schiffner [aut], Jakob Richter [aut], Zachary Jones [aut], Giuseppe Casalicchio [aut] (<https://orcid.org/0000-0001-5324-5966>), Mason Gallo [aut], Patrick Schratz [aut, cre] (<https://orcid.org/0000-0003-0748-6624>), Jakob Bossek [ctb] (<https://orcid.org/0000-0002-4121-4668>), Erich Studerus [ctb] (<https://orcid.org/0000-0003-4233-0182>), Leonard Judt [ctb], Tobias Kuehn [ctb], Pascal Kerschke [ctb] (<https://orcid.org/0000-0003-2862-1418>), Florian Fendt [ctb], Philipp Probst [ctb] (<https://orcid.org/0000-0001-8402-6790>), Xudong Sun [ctb] (<https://orcid.org/0000-0003-3269-2307>), Janek Thomas [ctb] (<https://orcid.org/0000-0003-4511-6245>), Bruno Vieira [ctb], Laura Beggel [ctb] (<https://orcid.org/0000-0002-8872-8535>), Quay Au [ctb] (<https://orcid.org/0000-0002-5252-8902>), Martin Binder [ctb], Florian Pfisterer [ctb], Stefan Coors [ctb], Steve Bronder [ctb], Alexander Engelhardt [ctb], Christoph Molnar [ctb], Annette Spooner [ctb]
Maintainer: Patrick Schratz <patrick.schratz@gmail.com>

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 556 files changed, 8233 insertions(+), 5612 deletions(-)

More information about mlr at CRAN
Permanent link

Package ballr updated to version 0.2.5 with previous version 0.2.4 dated 2019-10-22

Title: Access to Current and Historical Basketball Data
Description: Provides simple functions for accessing data/tables on <http://www.basketball-reference.com>.
Author: Ryan Elmore [cre, aut], Peter DeWitt [ctb]
Maintainer: Ryan Elmore <rtelmore@gmail.com>

Diff between ballr versions 0.2.4 dated 2019-10-22 and 0.2.5 dated 2020-01-10

 DESCRIPTION                   |    8 +--
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 10 files changed, 75 insertions(+), 71 deletions(-)

More information about ballr at CRAN
Permanent link

Package socialmixr updated to version 0.1.6 with previous version 0.1.5 dated 2019-09-24

Title: Social Mixing Matrices for Infectious Disease Modelling
Description: Provides methods for sampling contact matrices from diary data for use in infectious disease modelling, as discussed in Mossong et al. (2008) <doi:10.1371/journal.pmed.0050074>.
Author: Sebastian Funk [aut, cre]
Maintainer: Sebastian Funk <sebastian.funk@lshtm.ac.uk>

Diff between socialmixr versions 0.1.5 dated 2019-09-24 and 0.1.6 dated 2020-01-10

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 29 files changed, 378 insertions(+), 229 deletions(-)

More information about socialmixr at CRAN
Permanent link

New package skedastic with initial version 0.1.0
Package: skedastic
Type: Package
Title: Heteroskedasticity Diagnostics for Linear Regression Models
Version: 0.1.0
Authors@R: c(person(given = "Thomas", family = "Farrar", email = "tjfarrar@alumni.uwaterloo.ca", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-0744-6972")), person(given = "University of the Western Cape", role = "cph"))
Description: Implements numerous methods for detecting heteroskedasticity (sometimes called heteroscedasticity) in the classical linear regression model. These include the parametric and nonparametric tests of Goldfeld and Quandt (1965) <doi:10.1080/01621459.1965.10480811>, the test of Glejser (1969) <doi:10.1080/01621459.1969.10500976> as formulated by Mittelhammer, Judge and Miller (2000, ISBN: 0-521-62394-4), the BAMSET Test of Ramsey (1969) <doi:10.1111/j.2517-6161.1969.tb00796.x>, which uses the BLUS residuals derived by Theil (1965) <doi:10.1080/01621459.1965.10480851>, the test of Harvey (1976) <doi:10.2307/1913974>, the test of Breusch and Pagan (1979) <doi:10.2307/1911963> with and without the modification proposed by Koenker (1981) <doi:10.1016/0304-4076(81)90062-2>, the test of White (1980) <doi:10.2307/1912934>, the test and graphical Cook and Weisberg (1983) <doi:10.1093/biomet/70.1.1>, and the test of Li and Yao (2019) <doi:10.1016/j.ecosta.2018.01.001>. Homoskedasticity refers to the assumption of constant variance that is imposed on the model errors (disturbances); heteroskedasticity is the violation of this assumption.
RdMacros: Rdpack
Depends: R (>= 3.5.0)
Imports: stats (>= 3.5.0), utils (>= 3.5.0), Rdpack (>= 0.11.0), tibble (>= 2.1.3), broom (>= 0.5.3), magrittr (>= 1.5.0), pracma (>= 2.2.5), gmp (>= 0.5.13), Rmpfr (>= 0.7.2), matrixcalc (>= 1.0.3), lubridate (>= 1.7.4), lmtest (>= 0.9.37), car (>= 3.0.5), het.test (>= 0.1), tseries (>= 0.10.47)
Suggests:
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
URL: http://github.com/tjfarrar/skedastic
BugReports: http://github.com/tjfarrar/skedastic/issues
NeedsCompilation: no
Packaged: 2020-01-08 14:04:34 UTC; tom
Author: Thomas Farrar [aut, cre] (<https://orcid.org/0000-0003-0744-6972>), University of the Western Cape [cph]
Maintainer: Thomas Farrar <tjfarrar@alumni.uwaterloo.ca>
Repository: CRAN
Date/Publication: 2020-01-10 17:40:06 UTC

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Package separationplot updated to version 1.2 with previous version 1.1 dated 2015-03-13

Title: Separation Plots
Description: Visual representations of model fit or predictive success in the form of "separation plots." See Greenhill, Brian, Michael D. Ward, and Audrey Sacks. "The separation plot: A new visual method for evaluating the fit of binary models." American Journal of Political Science 55.4 (2011): 991-1002.
Author: Brian D. Greenhill, Michael D. Ward and Audrey Sacks
Maintainer: Brian Greenhill <bgreenhill@albany.edu>

Diff between separationplot versions 1.1 dated 2015-03-13 and 1.2 dated 2020-01-10

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Package ranger updated to version 0.12.1 with previous version 0.12.0 dated 2020-01-09

Title: A Fast Implementation of Random Forests
Description: A fast implementation of Random Forests, particularly suited for high dimensional data. Ensembles of classification, regression, survival and probability prediction trees are supported. Data from genome-wide association studies can be analyzed efficiently. In addition to data frames, datasets of class 'gwaa.data' (R package 'GenABEL') and 'dgCMatrix' (R package 'Matrix') can be directly analyzed.
Author: Marvin N. Wright [aut, cre], Stefan Wager [ctb], Philipp Probst [ctb]
Maintainer: Marvin N. Wright <cran@wrig.de>

Diff between ranger versions 0.12.0 dated 2020-01-09 and 0.12.1 dated 2020-01-10

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Package multcomp updated to version 1.4-12 with previous version 1.4-11 dated 2019-12-10

Title: Simultaneous Inference in General Parametric Models
Description: Simultaneous tests and confidence intervals for general linear hypotheses in parametric models, including linear, generalized linear, linear mixed effects, and survival models. The package includes demos reproducing analyzes presented in the book "Multiple Comparisons Using R" (Bretz, Hothorn, Westfall, 2010, CRC Press).
Author: Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>), Frank Bretz [aut], Peter Westfall [aut], Richard M. Heiberger [ctb], Andre Schuetzenmeister [ctb], Susan Scheibe [ctb]
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

Diff between multcomp versions 1.4-11 dated 2019-12-10 and 1.4-12 dated 2020-01-10

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Package mlt updated to version 1.1-1 with previous version 1.0-7 dated 2019-10-06

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>

Diff between mlt versions 1.0-7 dated 2019-10-06 and 1.1-1 dated 2020-01-10

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New package MLMOI with initial version 0.1.1
Package: MLMOI
Type: Package
Title: Estimating Frequencies, Prevalence and Multiplicity of Infection
Version: 0.1.1
Authors@R: c(person("Meraj", "Hashemi", role = c("cre", "aut", "com"), email = "mhashemi@hs-mittweida.de"), person("Kristan", "Schneider", role = c("aut", "ths"), email = "kristan.schneider@hs-mittweida.de"))
Maintainer: Meraj Hashemi <mhashemi@hs-mittweida.de>
Description: The implemented methods reach out to scientists that seek to estimate multiplicity of infection (MOI) and lineage (allele) frequencies and prevalences at molecular markers using the maximum-likelihood method described in Schneider (2018) <doi:10.1371/journal.pone.0194148>, and Schneider and Escalante (2014) <doi:10.1371/journal.pone.0097899>. Users can import data from Excel files in various formats, and perform maximum-likelihood estimation on the imported data by the package's moimle() function.
Depends: R (>= 3.3.0)
Imports: XLConnect (>= 0.2-15), rJava (>= 0.9-10), Rdpack (>= 0.10-1), Rmpfr (>= 0.7-1),
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
RdMacros: Rdpack
NeedsCompilation: no
Packaged: 2020-01-08 11:35:01 UTC; Meraj
Author: Meraj Hashemi [cre, aut, com], Kristan Schneider [aut, ths]
Repository: CRAN
Date/Publication: 2020-01-10 17:30:02 UTC

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Package Minirand updated to version 0.1.2 with previous version 0.1.1 dated 2019-10-26

Title: Minimization Randomization
Description: Randomization schedules are generated in the schemes with k (k>=2) treatment groups and any allocation ratios by minimization algorithms.
Author: Man Jin [aut, cre], Adam Polis [aut], Jonathan Hartzel [aut]
Maintainer: Man Jin <mj2149@gmail.com>

Diff between Minirand versions 0.1.1 dated 2019-10-26 and 0.1.2 dated 2020-01-10

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New package ldaPrototype with initial version 0.1.1
Package: ldaPrototype
Type: Package
Title: Prototype of Multiple Latent Dirichlet Allocation Runs
Version: 0.1.1
Date: 2020-01-08
Authors@R: person("Jonas", "Rieger", email="jonas.rieger@tu-dortmund.de", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-0007-4478"))
Description: Determine a Prototype from a number of runs of Latent Dirichlet Allocation (LDA) measuring its similarities with S-CLOP: A procedure to select the LDA run with highest mean pairwise similarity, which is measured by S-CLOP (Similarity of multiple sets by Clustering with Local Pruning), to all other runs. LDA runs are specified by its assignments leading to estimators for distribution parameters. Repeated runs lead to different results, which we encounter by choosing the most representative LDA run as prototype.
URL: https://github.com/JonasRieger/ldaPrototype, https://doi.org/10.5281/zenodo.3597978
BugReports: https://github.com/JonasRieger/ldaPrototype/issues
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: checkmate (>= 1.8.5), colorspace (>= 1.4-1), data.table (>= 1.11.2), dendextend, fs (>= 1.2.0), lda (>= 1.4.2), progress (>= 1.1.1), stats, utils
Suggests: batchtools (>= 0.9.11), future, parallelMap, RColorBrewer (>= 1.1-2), testthat, tosca
RoxygenNote: 7.0.2
LazyData: true
NeedsCompilation: no
Packaged: 2020-01-08 16:29:17 UTC; rieger
Author: Jonas Rieger [aut, cre] (<https://orcid.org/0000-0002-0007-4478>)
Maintainer: Jonas Rieger <jonas.rieger@tu-dortmund.de>
Repository: CRAN
Date/Publication: 2020-01-10 17:40:09 UTC

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Package hdf5r updated to version 1.3.1 with previous version 1.3.0 dated 2019-10-06

Title: Interface to the 'HDF5' Binary Data Format
Description: 'HDF5' is a data model, library and file format for storing and managing large amounts of data. This package provides a nearly feature complete, object oriented wrapper for the 'HDF5' API <https://support.hdfgroup.org/HDF5/doc/RM/RM_H5Front.html> using R6 classes. Additionally, functionality is added so that 'HDF5' objects behave very similar to their corresponding R counterparts.
Author: Holger Hoefling [aut, cre], Mario Annau [aut], Novartis Institute for BioMedical Research (NIBR) [cph]
Maintainer: Holger Hoefling <hhoeflin@gmail.com>

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New package dmdScheme with initial version 1.0.0
Package: dmdScheme
Title: Domain Specific MetaData Scheme
Description: Forms the core for developing own domain specific metadata schemes. It contains the basic functionality needed for all metadata schemes based on the 'dmdScheme'. See R.M. Krug and O.L. Petchey (2019) <DOI:10.5281/zenodo.3581970>.
Version: 1.0.0
Date: 2019-12-17
Authors@R: c(person(given = "Rainer M.", family = "Krug", role = c("aut", "cre"), email = "Rainer.Krug@uzh.ch", comment = c(ORCID = "0000-0002-7490-0066")), person(given = "Owen L.", family = "Petchey", role = "ctb", email = "Owen.Petchey@uzh.ch", comment = c(ORCID = "0000-0002-7724-1633")))
URL: https://exp-micro-ecol-hub.github.io/dmdScheme/, https://github.com/Exp-Micro-Ecol-Hub/dmdScheme
BugReports: https://github.com/rkrug/dmdScheme/issues
Depends: R (>= 3.5.0)
Imports: tools, methods, utils, magrittr (>= 1.5), dplyr (>= 0.1.8), tibble (>= 2.1.1), readxl (>= 1.2.0), xml2, rlang (>= 0.3.1), rmarkdown, knitr, digest (>= 0.6), openxlsx, writexl, rappdirs, yaml
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
StagedInstall: true
RoxygenNote: 6.1.1
Suggests: covr (>= 3.2.1), testthat (>= 2.0.1), here (>= 0.1), kableExtra (>= 0.9.0), shiny
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-08 10:11:18 UTC; rainerkrug
Author: Rainer M. Krug [aut, cre] (<https://orcid.org/0000-0002-7490-0066>), Owen L. Petchey [ctb] (<https://orcid.org/0000-0002-7724-1633>)
Maintainer: Rainer M. Krug <Rainer.Krug@uzh.ch>
Repository: CRAN
Date/Publication: 2020-01-10 17:20:03 UTC

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Package Cubist updated to version 0.2.3 with previous version 0.2.2 dated 2018-05-21

Title: Rule- And Instance-Based Regression Modeling
Description: Regression modeling using rules with added instance-based corrections.
Author: Max Kuhn [aut, cre], Steve Weston [ctb], Chris Keefer [ctb], Nathan Coulter [ctb], Ross Quinlan [aut] (Author of imported C code), Rulequest Research Pty Ltd. [cph] (Copyright holder of imported C code)
Maintainer: Max Kuhn <mxkuhn@gmail.com>

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Package NLMR (with last version 0.4.2) was removed from CRAN

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

2019-02-27 0.4.2
2019-01-28 0.4.1
2018-11-16 0.4
2018-10-02 0.3.2
2018-09-28 0.3.1
2018-04-03 0.3.0
2018-02-16 0.2.1
2018-01-09 0.2
2017-11-30 0.1.0

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Package coxed (with last version 0.3.0) was removed from CRAN

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

2019-08-01 0.3.0
2019-04-12 0.2.4
2018-08-23 0.2.0
2018-06-14 0.1.1

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Package joineRML (with last version 0.4.2) was removed from CRAN

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

2018-05-28 0.4.2
2018-01-21 0.4.1
2017-11-11 0.4.0
2017-07-23 0.3.0
2017-05-01 0.2.2
2017-04-25 0.2.1
2017-03-27 0.2.0
2016-12-30 0.1.1
2016-12-27 0.1.0

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Package cape (with last version 2.0.2) was removed from CRAN

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

2016-06-13 2.0.2
2016-04-06 2.0.1
2016-03-29 2.0
2014-09-26 1.3
2013-08-03 1.2
2013-06-05 1.1
2013-04-04 1.0

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Package V8 updated to version 3.0 with previous version 2.3 dated 2019-07-02

Title: Embedded JavaScript and WebAssembly Engine for R
Description: An R interface to V8: Google's open source JavaScript and WebAssembly engine. This package can be compiled either with V8 version 6 and up, a NodeJS shared library, or the legacy 3.14/3.15 branch of V8.
Author: Jeroen Ooms [aut, cre] (<https://orcid.org/0000-0002-4035-0289>)
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

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Package taxlist updated to version 0.1.7 with previous version 0.1.6 dated 2019-01-21

Title: Handling Taxonomic Lists
Description: Handling taxonomic lists through objects of class 'taxlist'. This package provides functions to import species lists from 'Turboveg' (<https://www.synbiosys.alterra.nl/turboveg>) and the possibility to create backups from resulting R-objects. Also quick displays are implemented as summary-methods.
Author: Miguel Alvarez [aut, cre] (<https://orcid.org/0000-0003-1500-1834>), Zachary Foster [ctb] (<https://orcid.org/0000-0002-5075-0948>)
Maintainer: Miguel Alvarez <kamapu78@gmail.com>

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Package SWIM updated to version 0.2.0 with previous version 0.1.0 dated 2019-07-19

Title: Scenario Weights for Importance Measurement
Description: An efficient sensitivity analysis for stochastic models based on Monte Carlo samples. Provides weights on simulated scenarios from a stochastic model, such that stressed random variables fulfil given probabilistic constraints (e.g. specified values for risk measures), under the new scenario weights. Scenario weights are selected by constrained minimisation of the relative entropy to the baseline model. The 'SWIM' package is based on Pesenti S.M, Millossovich P., Tsanakas A. (2019) "Reverse Sensitivity Testing: What does it take to break the model", <doi:10.1016/j.ejor.2018.10.003>.
Author: Silvana M. Pesenti [aut, cre], Alberto Bettini [aut], Pietro Millossovich [aut], Andreas Tsanakas [aut]
Maintainer: Silvana M. Pesenti <swimpackage@gmail.com>

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Package SimJoint updated to version 0.3.4 with previous version 0.2.2 dated 2019-08-07

Title: Simulate Joint Distribution
Description: Simulate multivariate correlated data given nonparametric marginals and their covariance structure characterized by a Pearson or Spearman correlation matrix. The simulator engages the problem from a purely computational perspective. It assumes no statistical models such as copulas or parametric distributions, and can approximate the target correlations regardless of theoretical feasibility. The algorithm integrates and advances the Iman-Conover (1982) approach <doi:10.1080/03610918208812265> and the Ruscio-Kaczetow iteration (2008) <doi:10.1080/00273170802285693>. Package functions are carefully implemented in C++ for squeezing computing speed, suitable for large input in a manycore environment. Precision of the approximation and computing speed both outperform various CRAN packages to date by substantial margins. Benchmarks are detailed in function examples. A simple heuristic algorithm is additionally designed to optimize the joint distribution in the post-simulation stage. This heuristic demonstrated not only strong capability of cost reduction, but also good potential of achieving the same level of precision of approximation without the enhanced Iman-Conover-Ruscio-Kaczetow. The package contains a copy of Permuted Congruential Generator from <http://www.pcg-random.org>.
Author: Charlie Wusuo Liu
Maintainer: Charlie Wusuo Liu <liuwusuo@gmail.com>

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Package Radviz updated to version 0.8.1 with previous version 0.8.0 dated 2019-12-18

Title: Project Multidimensional Data in 2D Space
Description: An implementation of the radviz projection in R. It enables the visualization of multidimensional data while maintaining the relation to the original dimensions. This package provides functions to create and plot radviz projections, and a number of summary plots that enable comparison and analysis. For reference see Ankerst *et al.* (1996) (<http://citeseer.ist.psu.edu/viewdoc/summary?doi=10.1.1.68.1811>) for original implementation, see Di Caro *et al* 2012 (<http://link.springer.com/chapter/10.1007/978-3-642-13672-6_13>) for the original method for dimensional anchor arrangements.
Author: Yann Abraham [aut, cre]
Maintainer: Yann Abraham <yann.abraham@gmail.com>

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Package PRSim updated to version 1.2-1 with previous version 1.2 dated 2019-12-02

Title: Stochastic Simulation of Streamflow Time Series using Phase Randomization
Description: Provides a simulation framework to simulate streamflow time series with similar main characteristics as observed data. These characteristics include the distribution of daily streamflow values and their temporal correlation as expressed by short- and long-range dependence. The approach is based on the randomization of the phases of the Fourier transform or the phases of the wavelet transform. The function prsim() is applicable to single site simulation and uses the Fourier transform. The function prsim.wave() extends the approach to multiple sites and is based on the complex wavelet transform. We further use the flexible four-parameter Kappa distribution, which allows for the extrapolation to yet unobserved low and high flows. Alternatively, the empirical or any other distribution can be used. A detailed description of the simulation approach for single sites and an application example can be found in <https://www.hydrol-earth-syst-sci-discuss.net/hess-2019-142/>.
Author: Manuela Brunner [aut, cre] (<https://orcid.org/0000-0001-8824-877X>), Reinhard Furrer [aut] (<https://orcid.org/0000-0002-6319-2332>)
Maintainer: Manuela Brunner <manuela.i.brunner@gmail.com>

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Package nph updated to version 2.0 with previous version 1.9 dated 2019-08-23

Title: Planning and Analysing Survival Studies under Non-Proportional Hazards
Description: Piecewise constant hazard functions are used to flexibly model survival distributions with non-proportional hazards and to simulate data from the specified distributions. Also, a function to calculate weighted log-rank tests for the comparison of two hazard functions is included. Finally, a function to calculate a test using the maximum of a set of test statistics from weighted log-rank tests is provided. This test utilizes the asymptotic multivariate normal joint distribution of the separate test statistics. The correlation is estimated from the data.
Author: Robin Ristl [aut, cre], Nicolas Ballarini [ctb]
Maintainer: Robin Ristl <robin.ristl@meduniwien.ac.at>

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Package keypress updated to version 1.2.0 with previous version 1.1.1 dated 2017-03-02

Title: Wait for a Key Press in a Terminal
Description: Wait for a single key press at the 'R' prompt. This works in terminals, but does not currently work in the 'Windows' 'GUI', the 'OS X' 'GUI' ('R.app'), in 'Emacs' 'ESS', in an 'Emacs' shell buffer or in 'R Studio'. In these cases 'keypress' stops with an error message.
Author: Gábor Csárdi [aut, cre], Jon Griffiths [aut]
Maintainer: Gábor Csárdi <csardi.gabor@gmail.com>

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Package greenclust updated to version 1.1.0 with previous version 1.0.0 dated 2019-07-18

Title: Combine Categories Using Greenacre's Method
Description: Implements a method of iteratively collapsing the rows of a contingency table, two at a time, by selecting the pair of categories whose combination yields a new table with the smallest loss of chi-squared, as described by Greenacre, M.J. (1988) <doi:10.1007/BF01901670>. The result is compatible with the class of object returned by the 'stats' package's hclust() function and can be used similarly (plotted as a dendrogram, cut, etc.). Additional functions are provided for automatic cutting and diagnostic plotting.
Author: Jeff Jetton [aut, cre]
Maintainer: Jeff Jetton <jeff.jetton@gmail.com>

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Package bnpsd updated to version 1.2.1 with previous version 1.1.1 dated 2019-05-15

Title: Simulate Genotypes from the BN-PSD Admixture Model
Description: The Pritchard-Stephens-Donnelly (PSD) admixture model has k intermediate subpopulations from which n individuals draw their alleles dictated by their individual-specific admixture proportions. The BN-PSD model additionally imposes the Balding-Nichols (BN) allele frequency model to the intermediate populations, which therefore evolved independently from a common ancestral population T with subpopulation-specific FST (Wright's fixation index) parameters. The BN-PSD model can be used to yield complex population structures. Method described in Ochoa and Storey (2016) <doi:10.1101/083923>.
Author: Alejandro Ochoa [aut, cre] (<https://orcid.org/0000-0003-4928-3403>), John D. Storey [aut] (<https://orcid.org/0000-0001-5992-402X>)
Maintainer: Alejandro Ochoa <alejandro.ochoa@duke.edu>

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Package batchtools updated to version 0.9.12 with previous version 0.9.11 dated 2018-08-16

Title: Tools for Computation on Batch Systems
Description: As a successor of the packages 'BatchJobs' and 'BatchExperiments', this package provides a parallel implementation of the Map function for high performance computing systems managed by schedulers 'IBM Spectrum LSF' (<https://www.ibm.com/us-en/marketplace/hpc-workload-management>), 'OpenLava' (<http://www.openlava.org/>), 'Univa Grid Engine'/'Oracle Grid Engine' (<http://www.univa.com/>), 'Slurm' (<http://slurm.schedmd.com/>), 'TORQUE/PBS' (<https://adaptivecomputing.com/cherry-services/torque-resource-manager/>), or 'Docker Swarm' (<https://docs.docker.com/swarm/>). A multicore and socket mode allow the parallelization on a local machines, and multiple machines can be hooked up via SSH to create a makeshift cluster. Moreover, the package provides an abstraction mechanism to define large-scale computer experiments in a well-organized and reproducible way.
Author: Michel Lang [cre, aut] (<https://orcid.org/0000-0001-9754-0393>), Bernd Bischl [aut], Dirk Surmann [ctb] (<https://orcid.org/0000-0003-0873-137X>)
Maintainer: Michel Lang <michellang@gmail.com>

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Package basicspace updated to version 0.24 with previous version 0.20 dated 2018-02-12

Title: Recovering a Basic Space from Issue Scales
Description: Conducts Aldrich-McKelvey and Blackbox Scaling (Poole et al 2016) <doi:10.18637/jss.v069.i07> to recover latent dimensions of judgment.
Author: Keith Poole <ktpoole@uga.edu>, Howard Rosenthal <hr31@nyu.edu>, Jeffrey Lewis <jblewis@ucla.edu>, James Lo <lojames@usc.edu> and Royce Carroll <rcarroll@rice.edu>
Maintainer: James Lo <lojames@usc.edu>

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Package meteorits updated to version 0.1.1 with previous version 0.1.0 dated 2019-10-07

Title: Mixture-of-Experts Modeling for Complex Non-Normal Distributions
Description: Provides a unified mixture-of-experts (ME) modeling and estimation framework with several original and flexible ME models to model, cluster and classify heterogeneous data in many complex situations where the data are distributed according to non-normal, possibly skewed distributions, and when they might be corrupted by atypical observations. Mixtures-of-Experts models for complex and non-normal distributions ('meteorits') are originally introduced and written in 'Matlab' by Faicel Chamroukhi. The references are mainly the following ones. The references are mainly the following ones. Chamroukhi F., Same A., Govaert, G. and Aknin P. (2009) <doi:10.1016/j.neunet.2009.06.040>. Chamroukhi F. (2010) <https://chamroukhi.com/FChamroukhi-PhD.pdf>. Chamroukhi F. (2015) <arXiv:1506.06707>. Chamroukhi F. (2015) <https://chamroukhi.com/FChamroukhi-HDR.pdf>. Chamroukhi F. (2016) <doi:10.1109/IJCNN.2016.7727580>. Chamroukhi F. (2016) <doi:10.1016/j.neunet.2016.03.002>. Chamroukhi F. (2017) <doi:10.1016/j.neucom.2017.05.044>.
Author: Faicel Chamroukhi [aut] (<https://orcid.org/0000-0002-5894-3103>), Florian Lecocq [aut, trl, cre] (R port), Marius Bartcus [aut, trl] (R port)
Maintainer: Florian Lecocq <florian.lecocq@outlook.com>

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Package IOHanalyzer updated to version 0.1.3 with previous version 0.1.1 dated 2019-05-29

Title: Data Analysis Part of 'IOHprofiler'
Description: The data analysis module for the Iterative Optimization Heuristics Profiler ('IOHprofiler'). This module provides statistical analysis methods for the benchmark data generated by optimization heuristics, which can be visualized through a web-based interface. The benchmark data is usually generated by the experimentation module, called 'IOHexperimenter'. 'IOHanalyzer' also supports the widely used 'COCO' (Comparing Continuous Optimisers) data format for benchmarking.
Author: Hao Wang [cre, aut], Diederick Vermetten [aut], Carola Doerr [aut], Thomas Bäck [aut]
Maintainer: Hao Wang <h.wang@liacs.leidenuniv.nl>

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Package idiogramFISH updated to version 1.12.1 with previous version 1.11.1 dated 2019-12-12

Title: Idiograms with Marks and Karyotype Indices
Description: Plot idiograms of several karyotypes having a set of data.frames for chromosome data and optionally mark data. Supports micrometers and Mb. Marks can have square or dot form, its legend (label) can be drawn inline or to the right of karyotypes. It is possible to calculate chromosome indices by Levan et al. (1964) <doi:10.1111/j.1601-5223.1964.tb01953.x>, karyotype indices of Watanabe et al. (1999) <doi:10.1007/PL00013869> and Romero-Zarco (1986) <doi:10.2307/1221906> and classify chromosomes by morphology Guerra (1986) and Levan et al. (1964).
Author: Fernando Roa [aut, cre], Mariana PC Telles [ctb]
Maintainer: Fernando Roa <froao@unal.edu.co>

Diff between idiogramFISH versions 1.11.1 dated 2019-12-12 and 1.12.1 dated 2020-01-10

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Package ordinalNet updated to version 2.7 with previous version 2.6 dated 2019-02-21

Title: Penalized Ordinal Regression
Description: Fits ordinal regression models with elastic net penalty. Supported model families include cumulative probability, stopping ratio, continuation ratio, and adjacent category. These families are a subset of vector glm's which belong to a model class we call the elementwise link multinomial-ordinal (ELMO) class. Each family in this class links a vector of covariates to a vector of class probabilities. Each of these families has a parallel form, which is appropriate for ordinal response data, as well as a nonparallel form that is appropriate for an unordered categorical response, or as a more flexible model for ordinal data. The parallel model has a single set of coefficients, whereas the nonparallel model has a set of coefficients for each response category except the baseline category. It is also possible to fit a model with both parallel and nonparallel terms, which we call the semi-parallel model. The semi-parallel model has the flexibility of the nonparallel model, but the elastic net penalty shrinks it toward the parallel model. For details, refer to Wurm, Hanlon, and Rathouz (2017) <arXiv:1706.05003>.
Author: Michael Wurm [aut, cre], Paul Rathouz [aut], Bret Hanlon [aut]
Maintainer: Michael Wurm <wurm@uwalumni.com>

Diff between ordinalNet versions 2.6 dated 2019-02-21 and 2.7 dated 2020-01-10

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Package ezcox updated to version 0.4.0 with previous version 0.3.0 dated 2019-12-06

Title: Easily Process a Batch of Cox Models
Description: A tool to operate a batch of univariate or multivariate Cox models and return tidy result.
Author: Shixiang Wang [aut, cre] (<https://orcid.org/0000-0001-9855-7357>)
Maintainer: Shixiang Wang <w_shixiang@163.com>

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Package SPAtest updated to version 3.0.2 with previous version 3.0.0 dated 2018-06-06

Title: Score Test and Meta-Analysis Based on Saddlepoint Approximation
Description: Performs score test using saddlepoint approximation to estimate the null distribution. Also prepares summary statistics for meta-analysis and performs meta-analysis to combine multiple association results. For the latest version, please check <https://github.com/leeshawn/SPAtest>.
Author: Rounak Dey, Seunggeun Lee
Maintainer: Rounak Dey <deyrnk@umich.edu>

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Package MSEtool updated to version 1.4.3 with previous version 1.4.1 dated 2019-12-03

Title: Management Strategy Evaluation Toolkit
Description: Simulation tools for management strategy evaluation are provided for the 'DLMtool' operating model to inform data-rich fisheries. 'MSEtool' provides complementary assessment models of varying complexity with standardized reporting, diagnostic tools for evaluating assessment models within closed-loop simulation, and helper functions for building more complex operating models and management procedures.
Author: Quang Huynh [aut], Tom Carruthers [aut, cre], Adrian Hordyk [aut], Chris Grandin [ctb] (iSCAM functions)
Maintainer: Tom Carruthers <t.carruthers@oceans.ubc.ca>

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Package youtubecaption updated to version 0.1.3 with previous version 0.1.2 dated 2019-10-28

Title: Downloading YouTube Subtitle Transcription in a Tidy Tibble Data Frame
Description: Although there exist some R packages tailored for YouTube API (e.g., 'tuber'), downloading YouTube video subtitle (i.e., caption) in a tidy form has never been a low-hanging fruit. Using 'youtube-transcript-api Python package' under the hood, this R package provides users with a convenient way of parsing and converting a desired YouTube caption into a handy 'tibble' data_frame object. Furthermore, users can easily save a desired YouTube caption data as a tidy Excel file without advanced programming background knowledge.
Author: JooYoung Seo [aut, cre] (<https://orcid.org/0000-0002-4064-6012>), Soyoung Choi [aut] (<https://orcid.org/0000-0002-0998-3352>)
Maintainer: JooYoung Seo <jooyoung@psu.edu>

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Package wppExplorer updated to version 2.3-3 with previous version 2.3-2 dated 2019-10-10

Title: Explorer of World Population Prospects
Description: Explore data in the 'wpp2019' (or 2017, 2015, ...) package using a 'shiny' interface.
Author: Hana Sevcikova <hanas@uw.edu>
Maintainer: Hana Sevcikova <hanas@uw.edu>

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Package tsDyn updated to version 10-1.1 with previous version 0.9-48.1 dated 2019-05-26

Title: Nonlinear Time Series Models with Regime Switching
Description: Implements nonlinear autoregressive (AR) time series models. For univariate series, a non-parametric approach is available through additive nonlinear AR. Parametric modeling and testing for regime switching dynamics is available when the transition is either direct (TAR: threshold AR) or smooth (STAR: smooth transition AR, LSTAR). For multivariate series, one can estimate a range of TVAR or threshold cointegration TVECM models with two or three regimes. Tests can be conducted for TVAR as well as for TVECM (Hansen and Seo 2002 and Seo 2006).
Author: Antonio Fabio Di Narzo [aut], Jose Luis Aznarte [ctb], Matthieu Stigler [aut], Ho Tsung-wu [cre]
Maintainer: Ho Tsung-wu <tsungwu@ntnu.edu.tw>

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Package SurvLong updated to version 1.1 with previous version 1.0 dated 2015-02-22

Title: Analysis of Proportional Hazards Model with Sparse Longitudinal Covariates
Description: Provides kernel weighting methods for estimation of proportional hazards models with intermittently observed longitudinal covariates. Cao H., Churpek M. M., Zeng D., and Fine J. P. (2015) <doi:10.1080/01621459.2014.957289>.
Author: Hongyuan Cao, Mathew M. Churpek, Donglin Zeng, Jason P. Fine, and Shannon T. Holloway
Maintainer: Shannon T. Holloway <sthollow@ncsu.edu>

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Package RonFHIR updated to version 0.4.0 with previous version 0.3.1 dated 2018-11-25

Title: Read and Search Interface to the 'HL7 FHIR' REST API
Description: R on FHIR is an easy to use wrapper around the 'HL7 FHIR' REST API (STU 3 and R4). It provides tools to easily read and search resources on a FHIR server and brings the results into the R environment. R on FHIR is based on the FhirClient of the official 'HL7 FHIR .NET API', also made by Firely.
Author: Sander Laverman [aut, cre], Firely B.V. [aut, cph]
Maintainer: Sander Laverman <sander@fire.ly>

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Package ptmixed updated to version 0.4.2 with previous version 0.4.1 dated 2019-10-23

Title: Poisson-Tweedie Generalized Linear Mixed Model
Description: Fits Poisson-Tweedie generalized linear mixed model. Likelihood approximation based on adaptive Gauss Hermite quadrature rule.
Author: Mirko Signorelli [aut, cre], Pietro Spitali [aut], Roula Tsonaka [aut]
Maintainer: Mirko Signorelli <m.signorelli@lumc.nl>

Diff between ptmixed versions 0.4.1 dated 2019-10-23 and 0.4.2 dated 2020-01-10

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New package PopGenome with initial version 2.7.2
Package: PopGenome
Type: Package
Title: An Efficient Swiss Army Knife for Population Genomic Analyses
Version: 2.7.2
Date: 2019-12-30
Authors@R: c( person("Bastian", "Pfeifer", role = c("aut", "cre"), email = "bastianxpfeifer@gmail.com"), person("Ulrich", "Wittelsbuerger", role = "ctb"), person("Heng", "Li", role = "ctb"), person("Bob", "Handsaker", role = "ctb") )
Depends: R (>= 2.14.2), ff
Imports: methods
Suggests: parallel, bigmemory, BASIX, WhopGenome, BlockFeST
Description: Provides efficient tools for population genomics data analysis, able to process individual loci, large sets of loci, or whole genomes. PopGenome <DOI:10.1093/molbev/msu136> not only implements a wide range of population genetics statistics, but also facilitates the easy implementation of new algorithms by other researchers. PopGenome is optimized for speed via the seamless integration of C code.
License: GPL-3
LazyLoad: yes
Copyright: inst/COPYRIGHTS
SystemRequirements: zlib headers and library.
Repository: CRAN
NeedsCompilation: yes
Packaged: 2020-01-10 09:15:58 UTC; bastian
Author: Bastian Pfeifer [aut, cre], Ulrich Wittelsbuerger [ctb], Heng Li [ctb], Bob Handsaker [ctb]
Maintainer: Bastian Pfeifer <bastianxpfeifer@gmail.com>
Date/Publication: 2020-01-10 12:40:03 UTC

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Package pins updated to version 0.3.1 with previous version 0.3.0 dated 2019-11-26

Title: Pin, Discover and Share Resources
Description: Pin remote resources into a local cache to work offline, improve speed and avoid recomputing; discover and share resources in local folders, 'GitHub', 'Kaggle' or 'RStudio Connect'. Resources can be anything from 'CSV', 'JSON', or image files to arbitrary R objects.
Author: Javier Luraschi [aut, cre], RStudio [cph]
Maintainer: Javier Luraschi <javier@rstudio.com>

Diff between pins versions 0.3.0 dated 2019-11-26 and 0.3.1 dated 2020-01-10

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Package lpSolveAPI updated to version 5.5.2.0-17.6 with previous version 5.5.2.0-17.4 dated 2019-08-08

Title: R Interface to 'lp_solve' Version 5.5.2.0
Description: The lpSolveAPI package provides an R interface to 'lp_solve', a Mixed Integer Linear Programming (MILP) solver with support for pure linear, (mixed) integer/binary, semi-continuous and special ordered sets (SOS) models.
Author: lp_solve <http://lpsolve.sourceforge.net/> [aut], Kjell Konis [aut], Florian Schwendinger [aut, cre]
Maintainer: Florian Schwendinger <FlorianSchwendinger@gmx.at>

Diff between lpSolveAPI versions 5.5.2.0-17.4 dated 2019-08-08 and 5.5.2.0-17.6 dated 2020-01-10

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Package iterpc updated to version 0.4.2 with previous version 0.4.1 dated 2018-08-08

Title: Efficient Iterator for Permutations and Combinations
Description: Iterator for generating permutations and combinations. They can be either drawn with or without replacement, or with distinct/ non-distinct items (multiset). The generated sequences are in lexicographical order (dictionary order). The algorithms to generate permutations and combinations are memory efficient. These iterative algorithms enable users to process all sequences without putting all results in the memory at the same time. The algorithms are written in C/C++ for faster performance. Note: 'iterpc' is no longer being maintained. Users are recommended to switch to 'arrangements'.
Author: Randy Lai [aut, cre]
Maintainer: Randy Lai <randy.cs.lai@gmail.com>

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Package ExPanDaR updated to version 0.5.0 with previous version 0.4.0 dated 2019-04-06

Title: Explore Your Data Interactively
Description: Provides a shiny-based front end (the 'ExPanD' app) and a set of functions for exploratory data analysis. Run as a web-based app, 'ExPanD' enables users to assess the robustness of empirical evidence without providing them access to the underlying data. You can export a notebook containing the analysis of 'ExPanD' and/or use the functions of the package to support your exploratory data analysis workflow. Refer to the vignettes of the package for more information on how to use 'ExPanD' and/or the functions of this package.
Author: Joachim Gassen [aut, cre] (<https://orcid.org/0000-0003-4364-2911>)
Maintainer: Joachim Gassen <gassen@wiwi.hu-berlin.de>

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Package camtrapR updated to version 1.2.3 with previous version 1.2.2 dated 2020-01-07

Title: Camera Trap Data Management and Preparation of Occupancy and Spatial Capture-Recapture Analyses
Description: Management of and data extraction from camera trap photographs in wildlife studies. The package provides a workflow for storing and sorting camera trap photos, tabulates records of species and individuals, and creates detection/non-detection matrices for occupancy and spatial capture-recapture analyses with great flexibility. In addition, it provides simple mapping functions (number of species, number of independent species detections by station including GIS export) and can visualise species activity data.
Author: Juergen Niedballa [aut, cre], Alexandre Courtiol [aut], Rahel Sollmann [aut], John Mathai [ctb], Seth Timothy Wong [ctb], An The Truong Nguyen [ctb], Azlan bin Mohamed [ctb], Andrew Tilker [ctb], Andreas Wilting [ctb, ths]
Maintainer: Juergen Niedballa <camtrapr@gmail.com>

Diff between camtrapR versions 1.2.2 dated 2020-01-07 and 1.2.3 dated 2020-01-10

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New package varTestnlme with initial version 0.1.0
Package: varTestnlme
Type: Package
Title: Variance Components Testing for Linear and Nonlinear Mixed Effects Models
Version: 0.1.0
Authors@R: c( person("Charlotte","Baey", ,"charlotte.baey@univ-lille.fr", role = c("aut", "cre"), comment = c(ORCID= "0000-0002-1413-1058") ), person("Estelle","Kuhn", ,"estelle.kuhn@inra.fr", role = c("aut")) )
URL: http://github.com/baeyc/varTestnlme/
BugReports: http://github.com/baeyc/varTestnlme/issues
Maintainer: Charlotte Baey <charlotte.baey@univ-lille.fr>
Description: An implementation of the Likelihood ratio Test (LRT) for testing that, in a (non)linear mixed effects model, the variances of a subset of the random effects are equal to zero. There is no restriction on the subset of variances that can be tested: for example, it is possible to test that all the variances are equal to zero. Note that the implemented test is asymptotic. This package should be used on model fits from packages 'nlme', 'lmer', and 'saemix'. Charlotte Baey, Paul-Henry Cournède and Estelle Kuhn (2019) <doi:10.1016/j.csda.2019.01.014>.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: mvtnorm, alabama, Matrix, merDeriv, matrixcalc, anocva, corpcor, quadprog, lme4, nlme, saemix, msm, foreach, methods, doParallel, parallel
RoxygenNote: 7.0.2
Suggests: knitr, rmarkdown, ggplot2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-01-07 10:45:08 UTC; charlotte
Author: Charlotte Baey [aut, cre] (<https://orcid.org/0000-0002-1413-1058>), Estelle Kuhn [aut]
Repository: CRAN
Date/Publication: 2020-01-10 11:30:02 UTC

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Package statmod updated to version 1.4.33 with previous version 1.4.32 dated 2019-05-29

Title: Statistical Modeling
Description: A collection of algorithms and functions to aid statistical modeling. Includes limiting dilution analysis (aka ELDA), growth curve comparisons, mixed linear models, heteroscedastic regression, inverse-Gaussian probability calculations, Gauss quadrature and a secure convergence algorithm for nonlinear models. Also includes advanced generalized linear model functions including Tweedie and Digamma distributional families and a secure convergence algorithm.
Author: Gordon Smyth [cre, aut], Yifang Hu [ctb], Peter Dunn [ctb], Belinda Phipson [ctb], Yunshun Chen [ctb]
Maintainer: Gordon Smyth <smyth@wehi.edu.au>

Diff between statmod versions 1.4.32 dated 2019-05-29 and 1.4.33 dated 2020-01-10

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Package soilassessment updated to version 0.1.1 with previous version 0.1.0 dated 2019-10-25

Title: Assessment Models for Agriculture Soil Conditions and Crop Suitability
Description: Soil assessment builds information for improved decision in soil management. It analyzes soil conditions with regard to agriculture crop suitability requirements [such as those given by FAO <http://ecocrop.fao.org/ecocrop/srv/en/home>] soil fertility classes, soil erosion models and soil salinity classification. Suitability requirements are for crops grouped into cereal crops, nuts, legumes, fruits, vegetables, industrial crops, and root crops.
Author: Christian Thine Omuto
Maintainer: Christian Thine Omuto <thineomuto@yahoo.com>

Diff between soilassessment versions 0.1.0 dated 2019-10-25 and 0.1.1 dated 2020-01-10

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Package qrNLMM updated to version 2.0 with previous version 1.4 dated 2017-03-21

Title: Quantile Regression for Nonlinear Mixed-Effects Models
Description: Quantile regression (QR) for Nonlinear Mixed-Effects Models via the asymmetric Laplace distribution (ALD). It uses the Stochastic Approximation of the EM (SAEM) algorithm for deriving exact maximum likelihood estimates and full inference results for the fixed-effects and variance components. It also provides graphical summaries for assessing the algorithm convergence and fitting results.
Author: Christian E. Galarza <cgalarza88@gmail.com> and Victor H. Lachos <hlachos@ime.unicamp.br>
Maintainer: Christian E. Galarza <cgalarza88@gmail.com>

Diff between qrNLMM versions 1.4 dated 2017-03-21 and 2.0 dated 2020-01-10

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Package qrLMM updated to version 2.0 with previous version 1.3 dated 2017-03-21

Title: Quantile Regression for Linear Mixed-Effects Models
Description: Quantile regression (QR) for Linear Mixed-Effects Models via the asymmetric Laplace distribution (ALD). It uses the Stochastic Approximation of the EM (SAEM) algorithm for deriving exact maximum likelihood estimates and full inference results for the fixed-effects and variance components. It also provides graphical summaries for assessing the algorithm convergence and fitting results.
Author: Christian E. Galarza <cgalarza88@gmail.com> and Victor H. Lachos <hlachos@ime.unicamp.br>
Maintainer: Christian E. Galarza <cgalarza88@gmail.com>

Diff between qrLMM versions 1.3 dated 2017-03-21 and 2.0 dated 2020-01-10

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Package portalr updated to version 0.3.0 with previous version 0.2.7 dated 2019-10-04

Title: Create Useful Summaries of the Portal Data
Description: Download and generate summaries for the rodent, plant, ant, and weather data from the Portal Project. Portal is a long-term (and ongoing) experimental monitoring site in the Chihuahua desert. The raw data files can be found at <https://github.com/weecology/portaldata>.
Author: Glenda M. Yenni [aut, cre] (<https://orcid.org/0000-0001-6969-1848>), Hao Ye [aut] (<https://orcid.org/0000-0002-8630-1458>), Erica M. Christensen [aut] (<https://orcid.org/0000-0002-5635-2502>), Juniper L. Simonis [aut] (<https://orcid.org/0000-0001-9798-0460>), Ellen K. Bledsoe [aut] (<https://orcid.org/0000-0002-3629-7235>), Renata M. Diaz [aut] (<https://orcid.org/0000-0003-0803-4734>), Shawn D. Taylor [aut] (<https://orcid.org/0000-0002-6178-6903>), Ethan P, White [aut] (<https://orcid.org/0000-0001-6728-7745>), S.K. Morgan Ernest [aut] (<https://orcid.org/0000-0002-6026-8530>)
Maintainer: Glenda M. Yenni <glenda@weecology.org>

Diff between portalr versions 0.2.7 dated 2019-10-04 and 0.3.0 dated 2020-01-10

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Package mRMRe updated to version 2.1.0 with previous version 2.0.9 dated 2019-02-14

Title: "Parallelized Minimum Redundancy, Maximum Relevance (mRMR) Ensemble Feature Selection"
Description: "Computes mutual information matrices from continuous, categorical and survival variables, as well as feature selection with minimum redundancy, maximum relevance (mRMR) and a new ensemble mRMR technique with DOI: N De Jay et al. (2013) <doi:10.1093/bioinformatics/btt383>."
Author: Nicolas De Jay, Simon Papillon-Cavanagh, Catharina Olsen, Gianluca Bontempi, Benjamin Haibe-Kains
Maintainer: Benjamin Haibe-Kains <benjamin.haibe.kains@utoronto.ca>

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Package vcfR updated to version 1.9.0 with previous version 1.8.0 dated 2018-04-17

Title: Manipulate and Visualize VCF Data
Description: Facilitates easy manipulation of variant call format (VCF) data. Functions are provided to rapidly read from and write to VCF files. Once VCF data is read into R a parser function extracts matrices of data. This information can then be used for quality control or other purposes. Additional functions provide visualization of genomic data. Once processing is complete data may be written to a VCF file (*.vcf.gz). It also may be converted into other popular R objects (e.g., genlight, DNAbin). VcfR provides a link between VCF data and familiar R software.
Author: Brian J. Knaus [cre, aut] (<https://orcid.org/0000-0003-1665-4343>), Niklaus J. Grunwald [aut] (<https://orcid.org/0000-0003-1656-7602>), Eric C. Anderson [ctb], David J. Winter [ctb], Zhian N. Kamvar [ctb] (<https://orcid.org/0000-0003-1458-7108>), Javier F. Tabima [ctb] (<https://orcid.org/0000-0002-3603-2691>)
Maintainer: Brian J. Knaus <briank.lists@gmail.com>

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Package sgof updated to version 2.3.2 with previous version 2.3.1 dated 2020-01-07

Title: Multiple Hypothesis Testing
Description: Seven different methods for multiple testing problems. The SGoF-type methods (see for example, Carvajal Rodríguez et al., 2009 <doi:10.1186/1471-2105-10-209>; de Uña Álvarez, 2012 <doi:10.1515/1544-6115.1812>; Castro Conde et al., 2015 <doi:10.1177/0962280215597580>) and the BH and BY false discovery rate controlling procedures.
Author: Irene Castro Conde and Jacobo de Una Alvarez
Maintainer: Irene Castro Conde <irene.castro@uvigo.es>

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Package ramsvm updated to version 2.1 with previous version 2.0 dated 2016-01-22

Title: Reinforced Angle-Based Multicategory Support Vector Machines
Description: Provides a solution path for Reinforced Angle-based Multicategory Support Vector Machines, with linear learning, polynomial learning, and Gaussian kernel learning. C. Zhang, Y. Liu, J. Wang and H. Zhu. (2016) <doi:10.1080/10618600.2015.1043010>.
Author: Chong Zhang, Yufeng Liu, and Shannon Holloway
Maintainer: Shannon Holloway <sthollow@ncsu.edu>

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Package pointblank updated to version 0.3.0 with previous version 0.2.1 dated 2019-09-12

Title: Validation of Local and Remote Data Tables
Description: Validate data in data frames, 'tibble' objects, and in database tables (e.g., 'PostgreSQL' and 'MySQL'). Validation pipelines can be made using easily-readable, consecutive validation steps. Upon execution of the validation plan, several reporting options are available. User-defined thresholds for failure rates allow for the determination of appropriate reporting actions.
Author: Richard Iannone [aut, cre] (<https://orcid.org/0000-0003-3925-190X>)
Maintainer: Richard Iannone <riannone@me.com>

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Package myTAI updated to version 0.9.2 with previous version 0.9.1 dated 2019-03-10

Title: Evolutionary Transcriptomics
Description: Investigate the evolution of biological processes by capturing evolutionary signatures in transcriptomes (Drost et al. (2017) <doi:10.1093/bioinformatics/btx835>). The aim of this tool is to provide a transcriptome analysis environment for answering questions regarding the evolution of biological processes (Drost et al. (2016) <doi:10.1101/051565>).
Author: Hajk-Georg Drost [aut, cre] (<https://orcid.org/0000-0002-1567-306X>)
Maintainer: Hajk-Georg Drost <hajk-georg.drost@tuebingen.mpg.de>

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Package morpheus updated to version 1.0-0 with previous version 0.2-0 dated 2018-06-14

Title: Estimate Parameters of Mixtures of Logistic Regressions
Description: Mixture of logistic regressions parameters (H)estimation with (U)spectral methods. The main methods take d-dimensional inputs and a vector of binary outputs, and return parameters according to the GLMs mixture model (General Linear Model). For more details see chapter 3 in the PhD thesis of Mor-Absa Loum: <http://www.theses.fr/s156435>, available here <https://tel.archives-ouvertes.fr/tel-01877796/document>.
Author: Benjamin Auder <Benjamin.Auder@u-psud.fr> [aut,cre], Mor-Absa Loum <Mor-Absa.Loum@u-psud.fr> [aut]
Maintainer: Benjamin Auder <Benjamin.Auder@u-psud.fr>

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Package fastpos updated to version 0.2.0 with previous version 0.1.0 dated 2019-12-13

Title: Finds the Critical Sequential Point of Stability for a Pearson Correlation
Description: Finds the critical sample size ("critical point of stability") for a correlation to stabilize in Schoenbrodt and Perugini's definition of sequential stability (see <doi:10.1016/j.jrp.2013.05.009>).
Author: Johannes Titz [aut, cre, cph]
Maintainer: Johannes Titz <johannes.titz@gmail.com>

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Package depmix updated to version 0.9.16 with previous version 0.9.15 dated 2018-12-08

Title: Dependent Mixture Models
Description: Fits (multigroup) mixtures of latent or hidden Markov models on mixed categorical and continuous (timeseries) data. The 'Rdonlp2' package can optionally be used for optimization of the log-likelihood and is available from R-forge. See Visser et al. (2009, <DOI:10.1007/978-0-387-95922-1_13>) for examples and applications.
Author: Ingmar Visser <i.visser@uva.nl>
Maintainer: Ingmar Visser <i.visser@uva.nl>

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Package castor updated to version 1.5.5 with previous version 1.5.4 dated 2020-01-08

Title: Efficient Phylogenetics on Large Trees
Description: Efficient phylogenetic analyses on massive phylogenies comprising up to millions of tips. Functions include pruning, rerooting, calculation of most-recent common ancestors, calculating distances from the tree root and calculating pairwise distances. Calculation of phylogenetic signal and mean trait depth (trait conservatism), ancestral state reconstruction and hidden character prediction of discrete characters, simulating and fitting models of trait evolution, fitting and simulating diversification models, dating trees, comparing trees, and reading/writing trees in Newick format. Citation: Louca, Stilianos and Doebeli, Michael (2017) <doi:10.1093/bioinformatics/btx701>.
Author: Stilianos Louca
Maintainer: Stilianos Louca <louca@zoology.ubc.ca>

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Package sobir updated to version 0.1.2 with previous version 0.1.1 dated 2019-11-08

Title: Significance of Boundaries
Description: Separates significant boundary constraints in a dataset from illusions. A modified permutation test is applied using the no-data zone areas above the top-left, top-right, bottom-right and bottom-left boundary lines as test statistics. The observed no-data zone areas are compared to the distribution of the random permutations to calculate a p-value for each boundary line. An article detailing the methodologies and rationale is currently in preparation.
Author: Ruan de Wet and Dirk Snyman
Maintainer: Ruan de Wet <ruan.de.wet@c4es.co.za>

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Package ruimtehol updated to version 0.2.3 with previous version 0.2.1 dated 2019-05-31

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>

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Package stmgp updated to version 1.0.3 with previous version 1.0.2 dated 2019-09-25

Title: Rapid and Accurate Genetic Prediction Modeling for Genome-Wide Association or Whole-Genome Sequencing Study Data
Description: Rapidly build accurate genetic prediction models for genome-wide association or whole-genome sequencing study data by smooth-threshold multivariate genetic prediction (STMGP) method. Variable selection is performed using marginal association test p-values with an optimal p-value cutoff selected by Cp-type criterion. Quantitative and binary traits are modeled respectively via linear and logistic regression models. A function that works through PLINK software (Purcell et al. 2007 <DOI:10.1086/519795>, Chang et al. 2015 <DOI:10.1186/s13742-015-0047-8>) <https://www.cog-genomics.org/plink2> is provided. Covariates can be included in regression model.
Author: Masao Ueki
Maintainer: Masao Ueki <uekimrsd@nifty.com>

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Package pmxTools updated to version 1.0 with previous version 0.1.3 dated 2019-10-28

Title: Pharmacometric and Pharmacokinetic Toolkit
Description: Pharmacometric tools for common data analytical tasks; closed-form solutions for calculating concentrations at given times after dosing based on compartmental PK models (1-compartment, 2-compartment and 3-compartment, covering infusions, zero- and first-order absorption, and lag times, after single doses and at steady state, per Bertrand & Mentre (2008) <http://lixoft.com/wp-content/uploads/2016/03/PKPDlibrary.pdf>); parametric simulation from NONMEM-generated parameter estimates and other output; and parsing, tabulating and plotting results generated by Perl-speaks-NONMEM (PsN).
Author: Justin Wilkins [aut, cre] (<https://orcid.org/0000-0002-7099-9396>), Bill Denney [aut] (<https://orcid.org/0000-0002-5759-428X>), Rik Schoemaker [aut], Leonid Gibiansky [ctb], Andrew Hooker [ctb], E. Niclas Jonsson [ctb], Mats O. Karlsson [ctb], John Johnson [ctb]
Maintainer: Justin Wilkins <justin.wilkins@occams.com>

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Package weathercan (with last version 0.3.2) was removed from CRAN

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

2020-01-08 0.3.2
2019-09-29 0.3.1
2019-09-25 0.3.0
2018-10-08 0.2.8
2018-07-05 0.2.7

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Package BANOVA updated to version 1.1.5 with previous version 1.1.4 dated 2019-08-24

Title: Hierarchical Bayesian ANOVA Models
Description: It covers several Bayesian Analysis of Variance (BANOVA) models used in analysis of experimental designs in which both within- and between- subjects factors are manipulated. They can be applied to data that are common in the behavioral and social sciences. The package includes: Hierarchical Bayes ANOVA models with normal response, t response, Binomial (Bernoulli) response, Poisson response, ordered multinomial response and multinomial response variables. All models accommodate unobserved heterogeneity by including a normal distribution of the parameters across individuals. Outputs of the package include tables of sums of squares, effect sizes and p-values, and tables of predictions, which are easily interpretable for behavioral and social researchers. The floodlight analysis and mediation analysis based on these models are also provided. BANOVA uses 'Stan' and 'JAGS' as the computational platform.
Author: Chen Dong, Michel Wedel
Maintainer: Chen Dong <cdong@math.umd.edu>

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Package wellknown updated to version 0.6.0 with previous version 0.5.0 dated 2018-03-29

Title: Convert Between 'WKT' and 'GeoJSON'
Description: Convert 'WKT' to 'GeoJSON' and 'GeoJSON' to 'WKT'. Functions included for converting between 'GeoJSON' to 'WKT', creating both 'GeoJSON' features, and non-features, creating 'WKT' from R objects (e.g., lists, data.frames, vectors), and linting 'WKT'.
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>)
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

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Package viewshed3d updated to version 3.0.0 with previous version 2.0.0 dated 2019-05-30

Title: Compute Viewshed in 3D Point Clouds of Ecosystems
Description: A set of tools to compute viewshed in 3D from Terrestrial Laser Scanner data and prepare the data prior to visibility estimation.
Author: Bastien Lecigne [aut, cre] (<https://orcid.org/0000-0002-1496-202X>), Jan Eitel [aut]
Maintainer: Bastien Lecigne <lecignebastien@gmail.com>

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Package trust updated to version 0.1-8 with previous version 0.1-7 dated 2015-07-04

Title: Trust Region Optimization
Description: Does local optimization using two derivatives and trust regions. Guaranteed to converge to local minimum of objective function.
Author: Charles J. Geyer <charlie@stat.umn.edu>.
Maintainer: Charles J. Geyer <charlie@stat.umn.edu>

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Package statsExpressions updated to version 0.2.0 with previous version 0.1.3 dated 2019-12-18

Title: Expressions with Statistical Details
Description: Statistical processing backend for 'ggstatsplot', this package creates expressions with details from statistical tests. Currently, it supports only the most common types of statistical tests: parametric, nonparametric, robust, and bayesian versions of t-test/anova, correlation analyses, contingency table analysis.
Author: Indrajeet Patil [cre, aut, ctb] (<https://orcid.org/0000-0003-1995-6531>), Chuck Powell [ctb] (<https://orcid.org/0000-0002-3606-2188>)
Maintainer: Indrajeet Patil <patilindrajeet.science@gmail.com>

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Package sjmisc updated to version 2.8.3 with previous version 2.8.2 dated 2019-09-24

Title: Data and Variable Transformation Functions
Description: Collection of miscellaneous utility functions, supporting data transformation tasks like recoding, dichotomizing or grouping variables, setting and replacing missing values. The data transformation functions also support labelled data, and all integrate seamlessly into a 'tidyverse'-workflow.
Author: Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>), Iago Giné-Vázquez [ctb], Alexander Bartel [ctb] (<https://orcid.org/0000-0002-1280-6138>)
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

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Package Rttf2pt1 updated to version 1.3.8 with previous version 1.3.7 dated 2018-06-29

Title: 'ttf2pt1' Program
Description: Contains the program 'ttf2pt1', for use with the 'extrafont' package. This product includes software developed by the 'TTF2PT1' Project and its contributors.
Author: Winston Chang, Andrew Weeks, Frank M. Siegert, Mark Heath, Thomas Henlick, Sergey Babkin, Turgut Uyar, Rihardas Hepas, Szalay Tamas, Johan Vromans, Petr Titera, Lei Wang, Chen Xiangyang, Zvezdan Petkovic, Rigel, I. Lee Hetherington
Maintainer: Winston Chang <winston@stdout.org>

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Package odbc updated to version 1.2.2 with previous version 1.2.1 dated 2019-12-05

Title: Connect to ODBC Compatible Databases (using the DBI Interface)
Description: A DBI-compatible interface to ODBC databases.
Author: Jim Hester [aut, cre], Hadley Wickham [aut], lexicalunit [cph] (nanodbc library), Google Inc. [cph] (cctz library), RStudio [cph, fnd]
Maintainer: Jim Hester <jim.hester@rstudio.com>

Diff between odbc versions 1.2.1 dated 2019-12-05 and 1.2.2 dated 2020-01-10

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Package mpath updated to version 0.3-21 with previous version 0.3-20 dated 2019-11-10

Title: Regularized Linear Models
Description: Algorithms optimize penalized models. Currently the models include penalized Poisson, negative binomial, zero-inflated Poisson, zero-inflated negative binomial regression models and robust models. The penalties include least absolute shrinkage and selection operator (LASSO), smoothly clipped absolute deviation (SCAD), minimax concave penalty (MCP), and each possibly combining with L_2 penalty. See Wang et al. (2014) <doi:10.1002/sim.6314>, Wang et al. (2015) <doi:10.1002/bimj.201400143>, Wang et al. (2016) <doi:10.1177/0962280214530608>, Wang (2019) <arXiv:1912.11119>.
Author: Zhu Wang, with contributions from Achim Zeileis, Simon Jackman, Brian Ripley, Trevor Hastie, Rob Tibshirani, Balasubramanian Narasimhan, Gil Chu and Patrick Breheny
Maintainer: Zhu Wang <wangz1@uthscsa.edu>

Diff between mpath versions 0.3-20 dated 2019-11-10 and 0.3-21 dated 2020-01-10

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Package maxLik updated to version 1.3-8 with previous version 1.3-6 dated 2019-05-19

Title: Maximum Likelihood Estimation and Related Tools
Description: Functions for Maximum Likelihood (ML) estimation and non-linear optimization, and related tools. It includes a unified way to call different optimizers, and classes and methods to handle the results from the ML viewpoint. It also includes a number of convenience tools for testing and developing your own models.
Author: Ott Toomet <otoomet@gmail.com>, Arne Henningsen <arne.henningsen@gmail.com>, with contributions from Spencer Graves and Yves Croissant
Maintainer: Ott Toomet <otoomet@gmail.com>

Diff between maxLik versions 1.3-6 dated 2019-05-19 and 1.3-8 dated 2020-01-10

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Package markovchain updated to version 0.8.2 with previous version 0.8.1 dated 2019-12-16

Title: Easy Handling Discrete Time Markov Chains
Description: Functions and S4 methods to create and manage discrete time Markov chains more easily. In addition functions to perform statistical (fitting and drawing random variates) and probabilistic (analysis of their structural proprieties) analysis are provided.
Author: Giorgio Alfredo Spedicato [aut, cre] (<https://orcid.org/0000-0002-0315-8888>), Tae Seung Kang [aut], Sai Bhargav Yalamanchi [aut], Mildenberger Thoralf [ctb] (<https://orcid.org/0000-0001-7242-1873>), Deepak Yadav [aut], Ignacio Cordón [aut] (<https://orcid.org/0000-0002-3152-0231>), Vandit Jain [ctb], Toni Giorgino [ctb] (<https://orcid.org/0000-0001-6449-0596>)
Maintainer: Giorgio Alfredo Spedicato <spedicato_giorgio@yahoo.it>

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Package LINselect updated to version 1.1.3 with previous version 1.1.2 dated 2020-01-09

Title: Selection of Linear Estimators
Description: Estimate the mean of a Gaussian vector, by choosing among a large collection of estimators, following the method developed by Y. Baraud, C. Giraud and S. Huet (2014) <doi:10.1214/13-AIHP539>. In particular it solves the problem of variable selection by choosing the best predictor among predictors emanating from different methods as lasso, elastic-net, adaptive lasso, pls, randomForest. Moreover, it can be applied for choosing the tuning parameter in a Gauss-lasso procedure.
Author: Yannick Baraud, Christophe Giraud, Sylvie Huet
Maintainer: Benjamin Auder <benjamin.auder@universite-paris-saclay.fr>

Diff between LINselect versions 1.1.2 dated 2020-01-09 and 1.1.3 dated 2020-01-10

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Package GGMselect updated to version 0.1-12.4 with previous version 0.1-12.3 dated 2020-01-09

Title: Gaussian Graphs Models Selection
Description: Graph estimation in Gaussian Graphical Models, following the method developed by C. Giraud, S. Huet and N. Verzelen (2012) <doi:10.1515/1544-6115.1625>. The main functions return the adjacency matrix of an undirected graph estimated from a data matrix.
Author: Annie Bouvier, Christophe Giraud, Sylvie Huet, Verzelen N.
Maintainer: Benjamin Auder <benjamin.auder@universite-paris-saclay.fr>

Diff between GGMselect versions 0.1-12.3 dated 2020-01-09 and 0.1-12.4 dated 2020-01-10

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Package enrichwith updated to version 0.3.1 with previous version 0.3 dated 2019-10-14

Title: Methods to Enrich R Objects with Extra Components
Description: Provides the "enrich" method to enrich list-like R objects with new, relevant components. The current version has methods for enriching objects of class 'family', 'link-glm', 'lm', 'glm' and 'betareg'. The resulting objects preserve their class, so all methods associated with them still apply. The package also provides the 'enriched_glm' function that has the same interface as 'glm' but results in objects of class 'enriched_glm'. In addition to the usual components in a `glm` object, 'enriched_glm' objects carry an object-specific simulate method and functions to compute the scores, the observed and expected information matrix, the first-order bias, as well as model densities, probabilities, and quantiles at arbitrary parameter values. The package can also be used to produce customizable source code templates for the structured implementation of methods to compute new components and enrich arbitrary objects.
Author: Ioannis Kosmidis [aut, cre]
Maintainer: Ioannis Kosmidis <ioannis.kosmidis@warwick.ac.uk>

Diff between enrichwith versions 0.3 dated 2019-10-14 and 0.3.1 dated 2020-01-10

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Package CompRandFld updated to version 1.0.3-6 with previous version 1.0.3-5 dated 2018-06-08

Title: Composite-Likelihood Based Analysis of Random Fields
Description: A set of procedures for the analysis of Random Fields using likelihood and non-standard likelihood methods is provided. Spatial analysis often involves dealing with large dataset. Therefore even simple studies may be too computationally demanding. Composite likelihood inference is emerging as a useful tool for mitigating such computational problems. This methodology shows satisfactory results when compared with other techniques such as the tapering method. Moreover, composite likelihood (and related quantities) have some useful properties similar to those of the standard likelihood. Adapts the methodologies derived in Padoan and Bevilacqua (2015) <doi:10.18637/jss.v063.i09>, Padoan et al. (2010) <doi:10.1198/jasa.2009.tm08577>, Davison et al. (2012) <doi:10.1214/11-STS376>, Bevilacqua et al. (2012) <doi:10.1080/01621459.2011.646928>. It also refers to the works of Bevilacqua et al. (2010) <doi:10.1007/s11222-009-9121-3>, Bevilacqua and Gaetan (2013) <doi:10.1007/s11222-014-9460-6>, Cooley et al. (2006) <doi:10.1007/0-387-36062-X_17>, Cressie (1993) <doi:10.1002/9781119115151>, Gaetan and Guyon (2010) <doi:10.1007/978-0-387-92257-7>, Gneiting (2002) <doi:10.1198/016214502760047113>, Gneiting et al. (2007) <https://www.stat.washington.edu/sites/default/files/files/reports/2005/tr475.pdf>, Heagerty and Zeger (1998) <doi:10.1080/01621459.1998.10474097>, Harville (1977) <doi:10.2307/2286796>, Kaufman et al. (2008) <doi:10.1198/016214508000000959>, Shaby and Ruppert (2012) <doi:10.1080/10618600.2012.680819>, Varin and Vidoni (2005) <doi:10.1093/biomet/92.3.519>, Patrick et al. <doi:10.1080/01621459.1998.10473771>, de Haan and Pereira (2006) <doi:10.1214/009053605000000886>, Kabluchko (2010) <doi:10.1007/s10687-010-0110-x>, Kabluchko et al. (2009) <doi:10.1214/09-AOP455>, Schlather (2002) <doi:10.1023/A:1020977924878>, Carlstein (1986) <doi:10.1214/aos/1176350057>, Heagerty and Lumley (2000) <doi:10.2307/2669538>, Lee and Lahiri (2002) <doi:10.1111/1467-9868.00364>, Li et al. (2007) <doi:10.1198/016214507000000202>, de Haan and Ferreira (2006) <doi:10.1007/0-387-34471-3> Smith (1987) <doi:10.1093/biomet/72.1.67>, Chandler and Bate (2007) <doi:10.1093/biomet/asm015>, Rotnitzky and Jewell (1990) <doi:10.1093/biomet/77.3.485>.
Author: Simone Padoan [cre, aut], Boris Beranger [aut], Moreno Bevilacqua [aut], Alan Genz [ctb] (Author of included MVNDST fragment)
Maintainer: Simone Padoan <simone.padoan@unibocconi.it>

Diff between CompRandFld versions 1.0.3-5 dated 2018-06-08 and 1.0.3-6 dated 2020-01-10

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