Thu, 19 Nov 2020

New package pak with initial version 0.1.2.1
Package: pak
Version: 0.1.2.1
Title: Another Approach to Package Installation
Description: The goal of 'pak' is to make package installation faster and more reliable. In particular, it performs all HTTP operations in parallel, so metadata resolution and package downloads are fast. Metadata and package files are cached on the local disk as well. 'pak' has a dependency solver, so it finds version conflicts before performing the installation. This version of 'pak' supports CRAN, 'Bioconductor' and 'GitHub' packages as well.
Authors@R: c( person("Jim", "Hester", email = "james.f.hester@gmail.com", role = "aut"), person("Gábor", "Csárdi", email = "csardi.gabor@gmail.com", role = c("aut", "cre")), person("RStudio", role = "cph"))
License: GPL-3
Encoding: UTF-8
LazyData: true
ByteCompile: true
RoxygenNote: 6.1.1
Imports: assertthat, base64enc, callr (>= 3.0.0.9002), cli (>= 1.0.0), cliapp (>= 0.0.0.9002), crayon (>= 1.3.4), curl (>= 3.2), desc (>= 1.2.0), filelock (>= 1.0.2), glue (>= 1.3.0), jsonlite, lpSolve, pkgbuild (>= 1.0.2), pkgcache (>= 1.0.3), prettyunits, processx (>= 3.2.1), ps (>= 1.3.0), R6, rematch2, rprojroot (>= 1.3.2), tibble, utils
Depends: R (>= 3.2)
Suggests: covr, mockery, pingr, testthat, withr
URL: https://pak.r-lib.org/
BugReports: https://github.com/r-lib/pak/issues
NeedsCompilation: no
Packaged: 2020-11-19 10:24:38 UTC; gaborcsardi
Author: Jim Hester [aut], Gábor Csárdi [aut, cre], RStudio [cph]
Maintainer: Gábor Csárdi <csardi.gabor@gmail.com>
Repository: CRAN
Date/Publication: 2020-11-19 23:10:02 UTC

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New package mwa with initial version 0.4.3
Package: mwa
Type: Package
Title: Causal Inference in Spatiotemporal Event Data
Version: 0.4.3
Date: 2020-11-17
Author: Sebastian Schutte and Karsten Donnay
Maintainer: Sebastian Schutte <schuttesebastian@gmail.com>
Description: Implementation of Matched Wake Analysis (mwa) for studying causal relationships in spatiotemporal event data, introduced by Schutte and Donnay (2014) <doi:10.1016/j.polgeo.2014.03.001>.
License: LGPL-3
Depends: R (>= 2.6), cem (>= 1.1), rJava (>= 0.9), MASS (>= 7.0)
SystemRequirements: Java (>= 6.0)
NeedsCompilation: no
Packaged: 2020-11-17 08:48:56 UTC; donnay
Repository: CRAN
Date/Publication: 2020-11-19 23:30:02 UTC

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New package ergm.ego with initial version 0.6.1
Package: ergm.ego
Version: 0.6.1
Date: 2020-11-19
Title: Fit, Simulate and Diagnose Exponential-Family Random Graph Models to Egocentrically Sampled Network Data
Authors@R: c( person("Pavel N.", "Krivitsky", role=c("aut","cre"), email="pavel@statnet.org", comment=c(ORCID="0000-0002-9101-3362")), person("Steven M.", "Goodreau", role=c("ctb"), email="goodreau@u.washington.edu"), person("Martina", "Morris", role=c("ctb"), email="morrism@u.washington.edu"), person("Kirk", "Li", role=c("ctb"), email="kirkli@uw.edu"), person("Emily N.", "Beylerian", role=c("ctb"), email="ebey@uw.edu"), person("Michał", "Bojanowski", role=c("ctb"), email="michal2992@gmail.com", comment=c(ORCID="0000-0001-7503-852X")), person("Chad", "Klumb", role=c("ctb"), email="cklumb@gmail.com"))
Depends: ergm (>= 3.11.0), network (>= 1.15)
Imports: statnet.common (>= 4.4.0), coda (>= 0.19.2), RColorBrewer (>= 1.1.2), purrr (>= 0.3.2), tibble (>= 2.1.1), stats, methods
Suggests: testthat (>= 2.1.1), covr (>= 3.2.1)
Description: Utilities for managing egocentrically sampled network data and a wrapper around the 'ergm' package to facilitate ERGM inference and simulation from such data.
License: GPL-3 + file LICENSE
URL: https://statnet.org
BugReports: https://github.com/statnet/ergm.ego/issues
RoxygenNote: 7.1.1
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2020-11-19 11:00:54 UTC; pavel
Author: Pavel N. Krivitsky [aut, cre] (<https://orcid.org/0000-0002-9101-3362>), Steven M. Goodreau [ctb], Martina Morris [ctb], Kirk Li [ctb], Emily N. Beylerian [ctb], Michał Bojanowski [ctb] (<https://orcid.org/0000-0001-7503-852X>), Chad Klumb [ctb]
Maintainer: Pavel N. Krivitsky <pavel@statnet.org>
Repository: CRAN
Date/Publication: 2020-11-19 23:10:05 UTC

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Package treemapify updated to version 2.5.4 with previous version 2.5.3 dated 2019-01-30

Title: Draw Treemaps in 'ggplot2'
Description: Provides 'ggplot2' geoms for drawing treemaps.
Author: David Wilkins [aut, cre], Bob Rudis [ctb] (<https://orcid.org/0000-0001-5670-2640>)
Maintainer: David Wilkins <david@wilkox.org>

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Package tensorA updated to version 0.36.2 with previous version 0.36.1 dated 2018-07-29

Title: Advanced Tensor Arithmetic with Named Indices
Description: Provides convenience functions for advanced linear algebra with tensors and computation with data sets of tensors on a higher level abstraction. It includes Einstein and Riemann summing conventions, dragging, co- and contravariate indices, parallel computations on sequences of tensors.
Author: K. Gerald van den Boogaart <boogaart@uni-greifswald.de>
Maintainer: K. Gerald van den Boogaart <boogaart@math.tu-freiberg.de>

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Package BOIN updated to version 2.7.1 with previous version 2.7.0 dated 2020-09-29

Title: Bayesian Optimal INterval (BOIN) Design for Single-Agent and Drug- Combination Phase I Clinical Trials
Description: The Bayesian optimal interval (BOIN) design is a novel phase I clinical trial design for finding the maximum tolerated dose (MTD). It can be used to design both single-agent and drug-combination trials. The BOIN design is motivated by the top priority and concern of clinicians when testing a new drug, which is to effectively treat patients and minimize the chance of exposing them to subtherapeutic or overly toxic doses. The prominent advantage of the BOIN design is that it achieves simplicity and superior performance at the same time. The BOIN design is algorithm-based and can be implemented in a simple way similar to the traditional 3+3 design. The BOIN design yields an average performance that is comparable to that of the continual reassessment method (CRM, one of the best model-based designs) in terms of selecting the MTD, but has a substantially lower risk of assigning patients to subtherapeutic or overly toxic doses. For tutorial, please check Yan et al. (2020) <doi:10.18637/jss.v094.i13>.
Author: Ying Yuan and Suyu Liu
Maintainer: Ying Yuan <yyuan@mdanderson.org>

Diff between BOIN versions 2.7.0 dated 2020-09-29 and 2.7.1 dated 2020-11-19

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Package unitizer updated to version 1.4.12 with previous version 1.4.11 dated 2020-11-13

Title: Interactive R Unit Tests
Description: Simplifies regression tests by comparing objects produced by test code with earlier versions of those same objects. If objects are unchanged the tests pass, otherwise execution stops with error details. If in interactive mode, tests can be reviewed through the provided interactive environment.
Author: Brodie Gaslam [aut, cre]
Maintainer: Brodie Gaslam <brodie.gaslam@yahoo.com>

Diff between unitizer versions 1.4.11 dated 2020-11-13 and 1.4.12 dated 2020-11-19

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Package strand updated to version 0.2.0 with previous version 0.1.3 dated 2020-05-26

Title: A Framework for Investment Strategy Simulation
Description: Provides a framework for performing discrete (share-level) simulations of investment strategies. Simulated portfolios optimize exposure to an input signal subject to constraints such as position size and factor exposure. For background see L. Chincarini and D. Kim (2010, ISBN:978-0-07-145939-6) "Quantitative Equity Portfolio Management".
Author: Jeff Enos [cre, aut, cph], David Kane [aut], Ben Czekanski [ctb], Robert Hoover [ctb], Jack Luby [ctb], Nils Wallin [ctb]
Maintainer: Jeff Enos <jeffrey.enos@gmail.com>

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Package statGraph updated to version 0.4.0 with previous version 0.3.0 dated 2019-10-24

Title: Statistical Methods for Graphs
Description: Contains statistical methods to analyze graphs, such as graph parameter estimation, model selection based on the GIC (Graph Information Criterion), statistical tests to discriminate two or more populations of graphs (ANOGVA - Analysis of Graph Variability), correlation between graphs, and clustering of graphs. References: Takahashi et al. (2012) <doi:10.1371/journal.pone.0049949>, Futija et al. (2017) <doi:10.3389/fnins.2017.00066>, Fujita et al. (2017) <doi:10.1016/j.csda.2016.11.016>, Tang et al. (2017) <doi:10.3150/15-BEJ789>, Tang et al. (2017) <doi:10.1080/10618600.2016.1193505>, Ghoshdastidar et al. (2017) <arXiv:1705.06168>, Ghoshdastidar et al. (2017) <arXiv:1707.00833>, Cerqueira et al. (2017) <doi:10.1109/TNSE.2017.2674026>, Fraiman and Fraiman (2018) <doi:10.1038/s41598-018-23152-5>, Fujita et al. (2019) <doi:10.1093/comnet/cnz028>.
Author: Diogo R. da Costa [aut], Taiane C. Ramos [aut], Grover E. Castro Guzman [aut], Suzana S. Santos [aut], Eduardo S. Lira [aut], Andre Fujita [aut, cre]
Maintainer: Andre Fujita <andrefujita@usp.br>

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Package Rssa updated to version 1.0.3 with previous version 1.0.2 dated 2020-02-28

Title: A Collection of Methods for Singular Spectrum Analysis
Description: Methods and tools for Singular Spectrum Analysis including decomposition, forecasting and gap-filling for univariate and multivariate time series. General description of the methods with many examples can be found in the book Golyandina (2018, <doi:10.1007/978-3-662-57380-8>). See 'citation("Rssa")' for details.
Author: Anton Korobeynikov, Alex Shlemov, Konstantin Usevich, Nina Golyandina
Maintainer: Anton Korobeynikov <anton@korobeynikov.info>

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Package eurostat updated to version 3.6.84 with previous version 3.6.83 dated 2020-11-19

Title: Tools for Eurostat Open Data
Description: Tools to download data from the Eurostat database <http://ec.europa.eu/eurostat> together with search and manipulation utilities.
Author: Leo Lahti [aut, cre] (<https://orcid.org/0000-0001-5537-637X>), Janne Huovari [aut], Markus Kainu [aut], Przemyslaw Biecek [aut], Joona Lehtomaki [ctb], Francois Briatte [ctb], Oliver Reiter [ctb]
Maintainer: Leo Lahti <leo.lahti@iki.fi>

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Package driveR updated to version 0.2.0 with previous version 0.1.1 dated 2020-11-18

Title: Prioritizing Cancer Driver Genes Using Genomics Data
Description: Cancer genomes contain large numbers of somatic alterations but few genes drive tumor development. Identifying cancer driver genes is critical for precision oncology. Most of current approaches either identify driver genes based on mutational recurrence or using estimated scores predicting the functional consequences of mutations. 'driveR' is a tool for personalized or batch analysis of genomic data for driver gene prioritization by combining genomic information and prior biological knowledge. As features, 'driveR' uses coding impact metaprediction scores, non-coding impact scores, somatic copy number alteration scores, hotspot gene/double-hit gene condition, 'phenolyzer' gene scores and memberships to cancer-related KEGG pathways. It uses these features to estimate cancer-type-specific probability for each gene of being a cancer driver using the related task of a multi-task learning classification model. The method is described in detail in Ulgen E, Sezerman OU. 2020. driveR: A Novel Method for Prioritizing Cancer Driver Genes Using Somatic Genomics Data. bioRxiv <doi:10.1101/2020.11.10.376707>.
Author: Ege Ulgen [aut, cre, cph] (<https://orcid.org/0000-0003-2090-3621>)
Maintainer: Ege Ulgen <egeulgen@gmail.com>

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Package treeheatr updated to version 0.2.1 with previous version 0.1.0 dated 2020-06-17

Title: Heatmap-Integrated Decision Tree Visualizations
Description: Creates interpretable decision tree visualizations with the data represented as a heatmap at the tree's leaf nodes. 'treeheatr' utilizes the customizable 'ggparty' package for drawing decision trees.
Author: Trang Le [aut, cre] (https://trang.page/), Jason Moore [aut] (http://www.epistasisblog.org/), University of Pennsylvania [cph]
Maintainer: Trang Le <grixor@gmail.com>

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Package statar updated to version 0.7.3 with previous version 0.7.2 dated 2020-07-27

Title: Tools Inspired by 'Stata' to Manipulate Tabular Data
Description: A set of tools inspired by 'Stata' to explore data.frames ('summarize', 'tabulate', 'xtile', 'pctile', 'binscatter', elapsed quarters/month, lead/lag).
Author: Matthieu Gomez [aut, cre]
Maintainer: Matthieu Gomez <mg3901@columbia.edu>

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Package statespacer updated to version 0.4.0 with previous version 0.3.0 dated 2020-09-15

Title: State Space Modelling in 'R'
Description: A tool that makes estimating models in state space form a breeze. See "Time Series Analysis by State Space Methods" by Durbin and Koopman (2012, ISBN: 978-0-19-964117-8) for details about the algorithms implemented.
Author: Dylan Beijers [aut, cre]
Maintainer: Dylan Beijers <dylanbeijers@gmail.com>

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Package treeHMM (with last version 0.1.1) was removed from CRAN

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

2019-12-12 0.1.1
2019-10-13 0.1.0

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Package marmap updated to version 1.0.5 with previous version 1.0.4 dated 2020-05-19

Title: Import, Plot and Analyze Bathymetric and Topographic Data
Description: Import xyz data from the NOAA (National Oceanic and Atmospheric Administration, <https://www.noaa.gov>), GEBCO (General Bathymetric Chart of the Oceans, <https://www.gebco.net>) and other sources, plot xyz data to prepare publication-ready figures, analyze xyz data to extract transects, get depth / altitude based on geographical coordinates, or calculate z-constrained least-cost paths.
Author: Eric Pante, Benoit Simon-Bouhet, and Jean-Olivier Irisson
Maintainer: Benoit Simon-Bouhet <besibo@gmail.com>

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Package LatticeDesign updated to version 2.0-1 with previous version 1.0-1 dated 2018-08-17

Title: Lattice-Based Space-Filling Designs
Description: Lattice-based space-filling designs with fill or separation distance properties including interleaved lattice-based minimax distance designs, interleaved lattice-based maximin distance designs, (sliced) rotated sphere packing designs, and densest packing-based maximum projections designs.
Author: Xu He [aut, cre]
Maintainer: Xu He <hexu@amss.ac.cn>

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Package gWQS updated to version 3.0.1 with previous version 3.0.0 dated 2020-06-23

Title: Generalized Weighted Quantile Sum Regression
Description: Fits Weighted Quantile Sum (WQS) regressions for continuous, binomial, multinomial and count outcomes.
Author: Stefano Renzetti, Paul Curtin, Allan C Just, Ghalib Bello, Chris Gennings
Maintainer: Stefano Renzetti <stefano.renzetti88@gmail.com>

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Package fairness updated to version 1.2.0 with previous version 1.1.1 dated 2020-07-26

Title: Algorithmic Fairness Metrics
Description: Offers calculation, visualization and comparison of algorithmic fairness metrics. Fair machine learning is an emerging topic with the overarching aim to critically assess whether ML algorithms reinforce existing social biases. Unfair algorithms can propagate such biases and produce predictions with a disparate impact on various sensitive groups of individuals (defined by sex, gender, ethnicity, religion, income, socioeconomic status, physical or mental disabilities). Fair algorithms possess the underlying foundation that these groups should be treated similarly or have similar prediction outcomes. The fairness R package offers the calculation and comparisons of commonly and less commonly used fairness metrics in population subgroups. These methods are described by Calders and Verwer (2010) <doi:10.1007/s10618-010-0190-x>, Chouldechova (2017) <doi:10.1089/big.2016.0047>, Feldman et al. (2015) <doi:10.1145/2783258.2783311> , Friedler et al. (2018) <doi:10.1145/3287560.3287589> and Zafar et al. (2017) <doi:10.1145/3038912.3052660>. The package also offers convenient visualizations to help understand fairness metrics.
Author: Nikita Kozodoi [aut, cre], Tibor V. Varga [aut] (<https://orcid.org/0000-0002-2383-699X>)
Maintainer: Nikita Kozodoi <n.kozodoi@icloud.com>

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Package BiodiversityR updated to version 2.12-2 with previous version 2.12-1 dated 2020-07-29

Title: Package for Community Ecology and Suitability Analysis
Description: Graphical User Interface (via the R-Commander) and utility functions (often based on the vegan package) for statistical analysis of biodiversity and ecological communities, including species accumulation curves, diversity indices, Renyi profiles, GLMs for analysis of species abundance and presence-absence, distance matrices, Mantel tests, and cluster, constrained and unconstrained ordination analysis. A book on biodiversity and community ecology analysis is available for free download from the website. In 2012, methods for (ensemble) suitability modelling and mapping were expanded in the package.
Author: Roeland Kindt [cre, aut] (<https://orcid.org/0000-0002-7672-0712>)
Maintainer: Roeland Kindt <R.KINDT@CGIAR.ORG>

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Package shiny.router updated to version 0.2.0 with previous version 0.1.1 dated 2018-09-18

Title: Basic Routing for Shiny Web Applications
Description: It is a simple router for your Shiny apps. The router allows you to create dynamic web applications with real-time User Interface and easily share url to pages within your Shiny apps.
Author: Filip Stachura [aut], Dominik Krzemiński [cre, aut], Krystian Igras [aut], Appsilon [cph]
Maintainer: Dominik Krzemiński <dominik@appsilon.com>

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Package saqgetr updated to version 0.2.1 with previous version 0.2.0 dated 2020-06-03

Title: Import Air Quality Monitoring Data in a Fast and Easy Way
Description: A collection of tools to access prepared air quality monitoring data files from web servers with ease and speed. Air quality data are sourced from open and publicly accessible repositories and can be found in these locations: <https://www.eea.europa.eu/data-and-maps/data/airbase-the-european-air-quality-database-8> and <https://discomap.eea.europa.eu/map/fme/AirQualityExport.htm>. The web server space has been provided by Ricardo Energy & Environment.
Author: Stuart K. Grange [cre, aut] (<https://orcid.org/0000-0003-4093-3596>)
Maintainer: Stuart K. Grange <stuart.grange@york.ac.uk>

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Package salso updated to version 0.2.5 with previous version 0.2.3 dated 2020-11-09

Title: Search Algorithms and Loss Functions for Bayesian Clustering
Description: The SALSO algorithm is an efficient greedy search procedure to obtain a clustering estimate based on a partition loss function. The algorithm is implemented for many loss functions, including the Binder loss and a generalization of the variation of information loss, both of which allow for unequal weights on the two types of clustering mistakes. Efficient implementations are also provided for Monte Carlo estimation of the posterior expected loss of a given clustering estimate. SALSO was first presented at the workshop "Bayesian Nonparametric Inference: Dependence Structures and their Applications" in Oaxaca, Mexico on December 6, 2017. See <https://www.birs.ca/events/2017/5-day-workshops/17w5060/schedule>.
Author: David B. Dahl [aut, cre], Devin J. Johnson [aut], Peter Müller [aut]
Maintainer: David B. Dahl <dahl@stat.byu.edu>

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Package mlflow updated to version 1.12.1 with previous version 1.12.0 dated 2020-11-12

Title: Interface to 'MLflow'
Description: R interface to 'MLflow', open source platform for the complete machine learning life cycle, see <https://mlflow.org/>. This package supports installing 'MLflow', tracking experiments, creating and running projects, and saving and serving models.
Author: Matei Zaharia [aut, cre], Javier Luraschi [aut], Kevin Kuo [aut] (<https://orcid.org/0000-0001-7803-7901>), RStudio [cph]
Maintainer: Matei Zaharia <matei@databricks.com>

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Package estimatr updated to version 0.28.0 with previous version 0.26.0 dated 2020-09-07

Title: Fast Estimators for Design-Based Inference
Description: Fast procedures for small set of commonly-used, design-appropriate estimators with robust standard errors and confidence intervals. Includes estimators for linear regression, instrumental variables regression, difference-in-means, Horvitz-Thompson estimation, and regression improving precision of experimental estimates by interacting treatment with centered pre-treatment covariates introduced by Lin (2013) <doi:10.1214/12-AOAS583>.
Author: Graeme Blair [aut, cre], Jasper Cooper [aut], Alexander Coppock [aut], Macartan Humphreys [aut], Luke Sonnet [aut], Neal Fultz [ctb], Lily Medina [ctb], Russell Lenth [ctb]
Maintainer: Graeme Blair <graeme.blair@ucla.edu>

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Package DELTD updated to version 2.6.6 with previous version 2.6.5 dated 2019-12-13

Title: Kernel Density Estimation using Lifetime Distributions
Description: A collection of asymmetrical kernels belong to lifetime distributions for kernel density estimation is presented. Mean Squared Errors (MSE) are calculated for estimated curves. For this purpose, R functions allow the distribution to be Gamma, Exponential or Weibull. For details see Chen (2000a, b), Jin and Kawczak (2003) and Salha et al. (2014) <doi:10.12988/pms.2014.4616>.
Author: Javaria Ahmad Khan, Atif Akbar.
Maintainer: Javaria Ahmad Khan <jakhan0@yahoo.com>

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 DELTD-2.6.6/DELTD/man/DELTD-package.Rd |   29 -
 DELTD-2.6.6/DELTD/man/Erlang.Rd        |   57 +
 DELTD-2.6.6/DELTD/man/Gamma.Rd         |   58 +-
 DELTD-2.6.6/DELTD/man/LogN.Rd          |only
 DELTD-2.6.6/DELTD/man/mse.Rd           |only
 DELTD-2.6.6/DELTD/man/plot.BS.Rd       |   28 
 DELTD-2.6.6/DELTD/man/plot.Beta.Rd     |only
 DELTD-2.6.6/DELTD/man/plot.Erlang.Rd   |   26 
 DELTD-2.6.6/DELTD/man/plot.Gamma.Rd    |   26 
 DELTD-2.6.6/DELTD/man/plot.LogN.Rd     |only
 23 files changed, 730 insertions(+), 565 deletions(-)

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Package BBEST updated to version 0.1-8 with previous version 0.1-7 dated 2020-10-26

Title: Bayesian Estimation of Incoherent Neutron Scattering Backgrounds
Description: We implemented a Bayesian-statistics approach for subtraction of incoherent scattering from neutron total-scattering data. In this approach, the estimated background signal associated with incoherent scattering maximizes the posterior probability, which combines the likelihood of this signal in reciprocal and real spaces with the prior that favors smooth lines. The description of the corresponding approach could be found at Gagin and Levin (2014) <DOI:10.1107/S1600576714023796>.
Author: Anton Gagin and Igor Levin with contributions from Charles R. Hogg III
Maintainer: Anton Gagin <av.gagin@gmail.com>

Diff between BBEST versions 0.1-7 dated 2020-10-26 and 0.1-8 dated 2020-11-19

 ChangeLog        |    4 ++++
 DESCRIPTION      |    8 ++++----
 MD5              |   12 ++++++------
 NEWS.md          |    6 ++++++
 R/guide.R        |    4 ++--
 R/interface.R    |    7 ++++---
 man/set.sigma.Rd |    2 +-
 7 files changed, 27 insertions(+), 16 deletions(-)

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Package anndata updated to version 0.7.5 with previous version 0.7.4 dated 2020-11-04

Title: Annotated Data
Description: An R wrapper for the Python package 'anndata'. Provides a scalable way of keeping track of data and learned annotations. Used to read from and write to the h5ad file format.
Author: Philipp Angerer [aut] (<https://orcid.org/0000-0002-0369-2888>, flying-sheep), Alex Wolf [aut] (<https://orcid.org/0000-0002-8760-7838>, falexwolf), Isaac Virshup [aut] (ivirshup), Sergei Rybakov [aut] (Koncopd), Robrecht Cannoodt [aut, ctb, cre, cph] (<https://orcid.org/0000-0003-3641-729X>, rcannood)
Maintainer: Robrecht Cannoodt <rcannood@gmail.com>

Diff between anndata versions 0.7.4 dated 2020-11-04 and 0.7.5 dated 2020-11-19

 DESCRIPTION                       |    8 
 MD5                               |   46 +-
 NAMESPACE                         |    3 
 NEWS.md                           |only
 R/AnnData.R                       |  617 +++++++++++++++++++++++---------------
 R/concat.R                        |    6 
 R/install_anndata.R               |    2 
 R/package.R                       |    3 
 R/read_csv.R                      |    8 
 R/read_excel.R                    |    8 
 R/read_h5ad.R                     |    8 
 R/read_hdf.R                      |    8 
 R/read_loom.R                     |    8 
 R/read_mtx.R                      |    8 
 R/read_text.R                     |    8 
 R/read_umi_tools.R                |    8 
 R/reticulate_conversions.R        |   46 +-
 README.md                         |   18 -
 man/AnnData.Rd                    |   42 ++
 man/AnnDataHelpers.Rd             |    3 
 man/all.equal.AnnDataR6.Rd        |only
 man/anndata-package.Rd            |    3 
 man/r-py-conversion.Rd            |    3 
 tests/testthat/helper-gen_adata.R |only
 tests/testthat/test-anndata.R     |   37 +-
 tests/testthat/test-base.R        |only
 26 files changed, 549 insertions(+), 352 deletions(-)

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New package reporter with initial version 1.0.5
Package: reporter
Type: Package
Title: Creates Statistical Reports
Version: 1.0.5
Author: David Bosak
Maintainer: David Bosak <dbosak01@gmail.com>
Description: Contains functions to create regulatory-style statistical reports. Originally designed to create tables, listings, and figures for the pharmaceutical, biotechnology, and medical device industries, these reports are generalized enough that they could be used in any industry. Generates text, rich-text, and PDF file formats. The package specializes in printing wide and long tables with automatic page wrapping and splitting. Reports can be produced with a minimum of function calls, and without relying on other table packages. The package supports titles, footnotes, page header, page footers, spanning headers, page by variables, and automatic page numbering.
License: CC BY-NC 4.0
Encoding: UTF-8
LazyData: true
Suggests: testthat, magrittr, dplyr, tidyr, readr, knitr, ggplot2, rmarkdown, gridExtra
Imports: fmtr, qlcMatrix, stringi, crayon
RoxygenNote: 7.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-11-16 23:30:04 UTC; User
Repository: CRAN
Date/Publication: 2020-11-19 11:30:03 UTC

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New package geogenr with initial version 1.0.0
Package: geogenr
Type: Package
Title: Geomultistar Generator from American Community Survey (ACS) Geodatabases
Version: 1.0.0
Authors@R: person(given = "Jose", family = "Samos", role = c("aut", "cre", "cph"), email = "jsamos@ugr.es", comment = c(ORCID = "0000-0002-4457-3439"))
Description: The American Community Survey (ACS) <https://www.census.gov/programs-surveys/acs> offers geodatabases with geographic information and associated data of interest to researchers in the area. The goal of this package is to generate geomultistar objects from those geodatabases automatically, once the focus of attention is selected. Multidimensional queries with geographic information can be easily defined on these objects.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-GB
LazyData: true
RoxygenNote: 7.1.1
Imports: dplyr, readr, tibble, tidyr, tidyselect, starschemar, generics, purrr, sf, magrittr, rlang, pander, stringr, snakecase, data.table, tm, utils, httr, geomultistar
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2020-11-16 19:05:26 UTC; jsamos
Author: Jose Samos [aut, cre, cph] (<https://orcid.org/0000-0002-4457-3439>)
Maintainer: Jose Samos <jsamos@ugr.es>
Repository: CRAN
Date/Publication: 2020-11-19 11:20:03 UTC

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New package RCytoGPS with initial version 1.0.1
Package: RCytoGPS
Version: 1.0.1
Date: 2020-11-16
Title: Using Cytogenetics Data in R
Author: Kevin R. Coombes, Dwayne Tally
Maintainer: Kevin R. Coombes <krc@silicovore.com>
Description: Defines classes and methods to process text-based cytogenetics using the CytoGPS web site, then import the results into R for further analysis and graphing.
Depends: R (>= 3.5)
Suggests: knitr, rmarkdown
Imports: methods, graphics, grDevices, rjson
VignetteBuilder: knitr
License: Apache License (== 2.0)
URL: http://oompa.r-forge.r-project.org/
NeedsCompilation: no
Packaged: 2020-11-16 14:23:01 UTC; KRC
Repository: CRAN
Date/Publication: 2020-11-19 10:30:02 UTC

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New package matuR with initial version 0.0.1.0
Package: matuR
Title: Athlete Maturation and Biobanding
Version: 0.0.1.0
Authors@R: person(given = "Jose", family = "Fernandez", role = c("aut", "cre"), email = "jose.fernandezdv@gmail.com")
Description: Identifying maturation stages across young athletes is paramount for talent identification. Furthermore, the concept of biobanding, or grouping of athletes based on their biological development, instead of their chronological age, has been widely researched. The goal of this package is to help professionals working in the field of strength & conditioning and talent ID obtain common maturation metrics and as well as to quickly visualize this information via several plotting options. For the methods behind the computed maturation metrics implemented in this package refer to Khamis, H. J., & Roche, A. F. (1994) <https://pubmed.ncbi.nlm.nih.gov/7936860/>, Mirwald, R.L et al., (2002) <https://pubmed.ncbi.nlm.nih.gov/11932580/> and Cumming, Sean P. et al., (2017) <doi:10.1519/SSC.0000000000000281>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: dplyr, ggplot2, lubridate, tidyr, magrittr, ggrepel
RoxygenNote: 7.1.1
Depends: R (>= 2.10)
URL: https://github.com/josedv82/matuR
BugReports: https://github.com/josedv82/matuR/issues
NeedsCompilation: no
Packaged: 2020-11-16 01:13:13 UTC; jfernandez
Author: Jose Fernandez [aut, cre]
Maintainer: Jose Fernandez <jose.fernandezdv@gmail.com>
Repository: CRAN
Date/Publication: 2020-11-19 10:20:02 UTC

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New package jti with initial version 0.5.1
Package: jti
Title: Junction Tree Inference
Version: 0.5.1
Date: 2020-11-13
Authors@R: person(given = "Mads", family = "Lindskou", role = c("aut", "cre"), email = "mads@math.aau.dk")
Description: Minimal and memory efficient implementation of the junction tree algorithm using the Lauritzen-Spiegelhalter scheme; S. L. Lauritzen and D. J. Spiegelhalter (1988) <https://www.jstor.org/stable/2345762?seq=1>.
Depends: R (>= 3.5.0)
URL: https://github.com/mlindsk/jti
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: Rcpp, igraph, sparta
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 7.1.1
SystemRequirements: C++11
Suggests: tinytest
NeedsCompilation: yes
Packaged: 2020-11-15 18:16:25 UTC; mads
Author: Mads Lindskou [aut, cre]
Maintainer: Mads Lindskou <mads@math.aau.dk>
Repository: CRAN
Date/Publication: 2020-11-19 10:10:02 UTC

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New package EvidenceSynthesis with initial version 0.2.0
Package: EvidenceSynthesis
Type: Package
Title: Synthesizing Causal Evidence in a Distributed Research Network
Version: 0.2.0
Date: 2020-11-13
Authors@R: c( person("Martijn", "Schuemie", email = "schuemie@ohdsi.org", role = c("aut", "cre")), person("Marc A.", "Suchard", , "msuchard@ucla.edu", role = c("aut")), person("Observational Health Data Science and Informatics", role = c("cph")) )
Maintainer: Martijn Schuemie <schuemie@ohdsi.org>
Description: Routines for combining causal effect estimates and study diagnostics across multiple data sites in a distributed study, without sharing patient-level data. Allows for normal and non-normal approximations of the data-site likelihood of the effect parameter.
Depends: survival, R (>= 3.5.0)
Imports: ggplot2, gridExtra, meta, EmpiricalCalibration, rJava, BeastJar, Cyclops (>= 3.1.0), HDInterval, rlang, methods
Suggests: knitr, rmarkdown, testthat, sn
License: Apache License 2.0
URL: https://ohdsi.github.io/EvidenceSynthesis/, https://github.com/OHDSI/EvidenceSynthesis
BugReports: https://github.com/OHDSI/EvidenceSynthesis/issues
VignetteBuilder: knitr
RoxygenNote: 7.1.1
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2020-11-16 16:03:46 UTC; MSCHUEMI
Author: Martijn Schuemie [aut, cre], Marc A. Suchard [aut], Observational Health Data Science and Informatics [cph]
Repository: CRAN
Date/Publication: 2020-11-19 11:00:02 UTC

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New package CancerGram with initial version 1.0.0
Package: CancerGram
Type: Package
Title: Prediction of Anticancer Peptides
Version: 1.0.0
LazyData: TRUE
Date: 2020-11-16
Authors@R: c(person("Michal", "Burdukiewicz", email = "michalburdukiewicz@gmail.com", comment = c(ORCID = "0000-0001-8926-582X"), role = c("cre", "aut")), person("Katarzyna", "Sidorczuk", email = "sidorczuk.katarzyna17@gmail.com", role = c("aut"), comment = c(ORCID = "0000-0001-6576-9054")), person("Filip", "Pietluch", email = "fpietluch@gmail.com", role = c("ctb"), comment = c(ORCID = "0000-0001-6218-9804")), person("Dominik", "Rafacz", email = "dominikrafacz@gmail.com", role = c("ctb"), comment = c(ORCID = "0000-0003-0925-1909")), person("Mateusz", "Bakala", email = "matibakala@gmail.com", comment = c(ORCID = "0000-0002-3213-2484"), role = c("ctb")), person("Jadwiga", "Słowik", comment = c(ORCID = "0000-0003-3466-8933"), email = "jadwiga.slowik5@gmail.com", role = c("ctb")))
Description: Predicts anticancer peptides using random forests trained on the n-gram encoded peptides. The implemented algorithm can be accessed from both the command line and shiny-based GUI. The CancerGram model is too large for CRAN and it has to be downloaded separately from the repository: <https://github.com/BioGenies/CancerGramModel>. For more information see: Burdukiewicz et al. (2020) <doi:10.3390/pharmaceutics12111045>.
License: GPL-3
URL: https://github.com/BioGenies/CancerGram
BugReports: https://github.com/BioGenies/CancerGram/issues
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: biogram, devtools, pbapply, ranger, shiny, stringi, dplyr
Suggests: DT, ggplot2, pander, rmarkdown, shinythemes, spelling
RoxygenNote: 7.1.1
Language: en-US
NeedsCompilation: no
Packaged: 2020-11-16 14:58:36 UTC; michal
Author: Michal Burdukiewicz [cre, aut] (<https://orcid.org/0000-0001-8926-582X>), Katarzyna Sidorczuk [aut] (<https://orcid.org/0000-0001-6576-9054>), Filip Pietluch [ctb] (<https://orcid.org/0000-0001-6218-9804>), Dominik Rafacz [ctb] (<https://orcid.org/0000-0003-0925-1909>), Mateusz Bakala [ctb] (<https://orcid.org/0000-0002-3213-2484>), Jadwiga Słowik [ctb] (<https://orcid.org/0000-0003-3466-8933>)
Maintainer: Michal Burdukiewicz <michalburdukiewicz@gmail.com>
Repository: CRAN
Date/Publication: 2020-11-19 10:40:02 UTC

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New package theiaR with initial version 0.4.0
Package: theiaR
Title: Download and Manage Data from Theia
Version: 0.4.0
Authors@R: person("Xavier", "Laviron", email = "xavier@norival.dev", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-9882-3253"))
Description: Provides a simple interface to search available data provided by Theia (<https://theia.cnes.fr>), download it, and manage it. Data can be downloaded based on a search result or from a cart file downloaded from Theia website.
Language: en-US
Depends: R (>= 3.5)
Imports: askpass (>= 1.1), httr (>= 1.3), R6 (>= 2.3), raster (>= 2.6), tools (>= 3.5), XML (>= 3.86)
License: GPL (>= 3.0)
URL: https://github.com/norival/theiaR
BugReports: https://github.com/norival/theiaR/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: knitr, rmarkdown, gdalcubes
Collate: 'TheiaAuth.R' 'TheiaTile.R' 'TheiaCollection.R' 'TheiaQuery.R' 'theiaR.R' 'utils.R'
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-11-14 18:05:09 UTC; xavier
Author: Xavier Laviron [aut, cre] (<https://orcid.org/0000-0002-9882-3253>)
Maintainer: Xavier Laviron <xavier@norival.dev>
Repository: CRAN
Date/Publication: 2020-11-19 09:30:02 UTC

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New package mlr3benchmark with initial version 0.1.0
Package: mlr3benchmark
Title: Analysis and Visualisation of Benchmark Experiments
Version: 0.1.0
Authors@R: c(person(given = "Sonabend", family = "Raphael", role = c("cre", "aut"), email = "raphael.sonabend.15@ucl.ac.uk", comment = c(ORCID = "0000-0001-9225-4654")), person(given = "Florian", family = "Pfisterer", role = "aut", email = "pfistererf@googlemail.com", comment = c(ORCID = "0000-0001-8867-762X")), person(given = "Michel", family = "Lang", role = "ctb", email = "michellang@gmail.com", comment = c(ORCID = "0000-0001-9754-0393")), person(given = "Bernd", family = "Bischl", role = "ctb", email = "bernd_bischl@gmx.net", comment = c(ORCID = "0000-0001-6002-6980")))
Description: Implements methods for post-hoc analysis and visualisation of benchmark experiments, for 'mlr3' and beyond.
License: LGPL-3
URL: https://mlr3benchmark.mlr-org.com, https://github.com/mlr-org/mlr3benchmark
BugReports: https://github.com/mlr-org/mlr3benchmark/issues
Depends: R (>= 3.1.0)
Imports: checkmate, data.table, ggplot2, mlr3misc, R6
Suggests: mlr3, mlr3learners, PMCMR, rpart, testthat, xgboost
Encoding: UTF-8
NeedsCompilation: no
RoxygenNote: 7.1.1
Packaged: 2020-11-14 09:22:55 UTC; raphael
Author: Sonabend Raphael [cre, aut] (<https://orcid.org/0000-0001-9225-4654>), Florian Pfisterer [aut] (<https://orcid.org/0000-0001-8867-762X>), Michel Lang [ctb] (<https://orcid.org/0000-0001-9754-0393>), Bernd Bischl [ctb] (<https://orcid.org/0000-0001-6002-6980>)
Maintainer: Sonabend Raphael <raphael.sonabend.15@ucl.ac.uk>
Repository: CRAN
Date/Publication: 2020-11-19 09:10:02 UTC

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New package metaEnsembleR with initial version 0.1.0
Package: metaEnsembleR
Type: Package
Title: Automated Intuitive Package for Meta-Ensemble Learning
Version: 0.1.0
Date: 2020-10-27
Author: Ajay Arunachalam
Maintainer: Ajay Arunachalam <ajay.arunachalam08@gmail.com>
Description: Extends the base classes and methods of 'caret' package for integration of base learners. The user can input the number of different base learners, and specify the final learner, along with the train-validation-test data partition split ratio. The predictions on the unseen new data is the resultant of the ensemble meta-learning <https://machinelearningmastery.com/stacking-ensemble-machine-learning-with-python/> of the heterogeneous learners aimed to reduce the generalization error in the predictive models. It significantly lowers the barrier for the practitioners to apply heterogeneous ensemble learning techniques in an amateur fashion to their everyday predictive problems.
License: GPL (>= 2)
Encoding: UTF-8
NeedsCompilation: no
Repository: CRAN
Imports: caret, ggplot2, graphics, e1071, gbm, randomForest
Depends: gridExtra
Suggests: knitr, R.rsp
VignetteBuilder: R.rsp
RoxygenNote: 7.1.1
Packaged: 2020-11-14 13:57:10 UTC; AASS Guest
Date/Publication: 2020-11-19 09:10:05 UTC

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New package dragracer with initial version 0.1.4
Package: dragracer
Type: Package
Title: Data Sets for RuPaul's Drag Race
Version: 0.1.4
Authors@R: person("Steve", "Miller", email = "steven.v.miller@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-4072-6263"))
Maintainer: Steve Miller <steven.v.miller@gmail.com>
Description: These are data sets for the hit TV show, RuPaul's Drag Race. Data right now include episode-level data, contestant-level data, and episode-contestant-level data. This is a work in progress, and a love letter of a kind to RuPaul's Drag Race and the performers that have appeared on the show. This may not be the most productive use of my time, but I have tenure and what are you going to do about it? I think there is at least some value in this package if it allows the show's fandom to learn more about the R programming language around its contents.
License: GPL-2
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
RoxygenNote: 7.1.1
Suggests: knitr, tidyr, tibble, dplyr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-11-14 15:23:15 UTC; steve
Author: Steve Miller [aut, cre] (<https://orcid.org/0000-0003-4072-6263>)
Repository: CRAN
Date/Publication: 2020-11-19 09:10:08 UTC

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New package covid19sf with initial version 0.1.0
Package: covid19sf
Title: The Covid19 San Francisco Dataset
Version: 0.1.0
Authors@R: person(given = "Rami", family ="Krispin", email = "rami.krispin@gmail.com", role = c("aut", "cre"))
Maintainer: Rami Krispin <rami.krispin@gmail.com>
Description: Provides a verity of summary tables of the Covid19 cases in San Francisco. Data source: San Francisco, Department of Public Health - Population Health Division <https://datasf.org/opendata/>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10)
Imports: devtools, dplyr, lubridate, magrittr, mapview, plotly, sf
Suggests: testthat, knitr, rmarkdown
RoxygenNote: 7.1.1
VignetteBuilder: knitr
URL: https://github.com/RamiKrispin/covid19sf
BugReports: https://github.com/RamiKrispin/covid19sf/issues
NeedsCompilation: no
Packaged: 2020-11-15 15:34:19 UTC; ramikrispin
Author: Rami Krispin [aut, cre]
Repository: CRAN
Date/Publication: 2020-11-19 10:00:02 UTC

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New package ahptopsis2n with initial version 0.1.0
Package: ahptopsis2n
Type: Package
Title: Hybrid Method for Multiple Criteria Decision-Making (MCDM)
Version: 0.1.0
Date: 2020-11-14
Authors@R: c(person("Raquel", "Coutinho", role=c("aut", "cre"), email="rdouradocoutinho@gmail.com"), person("Marcos", "dos Santos", role="aut", email="marcosdossantos@ime.eb.br"))
Author: Raquel Coutinho [aut, cre], Marcos dos Santos [aut]
Maintainer: Raquel Coutinho <rdouradocoutinho@gmail.com>
Description: Implementation of an hybrid MCDM method build from the AHP (Analytic Hierarchy Process) and TOPSIS-2N (Technique for Order of Preference by Similarity to Ideal Solution - with two normalizations).
License: GPL-3
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2020-11-14 18:39:59 UTC; raque
Repository: CRAN
Date/Publication: 2020-11-19 09:40:03 UTC

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New package tensorBSS with initial version 0.3.7
Package: tensorBSS
Type: Package
Title: Blind Source Separation Methods for Tensor-Valued Observations
Version: 0.3.7
Date: 2020-11-17
Author: Joni Virta, Christoph Koesner, Bing Li, Klaus Nordhausen, Hannu Oja
Maintainer: Joni Virta <joni.virta@outlook.com>
Description: Contains several utility functions for manipulating tensor-valued data (centering, multiplication from a single mode etc.) and the implementations of the following blind source separation methods for tensor-valued data: 'tPCA', 'tFOBI', 'tJADE', k-tJADE', 'tgFOBI', 'tgJADE', 'tSOBI', 'tNSS.SD', 'tNSS.JD', 'tNSS.TD.JD', 'tPP' and 'tTUCKER'.
License: GPL (>= 2)
Imports: Rcpp (>= 0.12.3), tensor, tsBSS, ICtest, ggplot2
LinkingTo: Rcpp, RcppArmadillo
Depends: JADE, R (>= 2.10), fICA
Suggests: stochvol
NeedsCompilation: yes
Packaged: 2020-11-18 07:20:03 UTC; joniv
Repository: CRAN
Date/Publication: 2020-11-19 08:20:02 UTC

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New package survRatio with initial version 0.1
Package: survRatio
Type: Package
Title: Estimating, Comparing and Visualising Time to Event Data
Version: 0.1
Authors@R: c( person("Jalali", "Amirhossein", email = "amir.jalali@ucc.ie", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-7227-8261")), person("Roshan", "Davood", role = "aut", comment = c(ORCID = "0000-0002-6553-640X")), person("Moghaddam", "Shirin", role = "aut", comment = c(ORCID = "0000-0002-9965-1510")), person("Newell", "John", role = "aut", comment = c(ORCID = "0000-0001-7685-6655")))
Description: The 'survRatio', provides numerical and graphical summaries for time to event data. In this release functions are provided to estimate and compare estimated survivor functions, the ratio of survivor functions and the difference of survivor functions in independent and paired time to event problems. Time intervals where the survival prospects may differ are identified using pointwise confidence bands. See "Survival ratio plots with permutation envelopes in survival data problems" by Newell J, et al. (2006) <doi:10.1016/j.compbiomed.2005.03.005>.
License: GPL-3
Depends: survival (>= 2.38-3), ggplot2 (> 2.1.0)
Imports: stats, methods, gridExtra, ggpubr
Suggests: knitr, rmarkdown, markdown
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1.9000
NeedsCompilation: no
Packaged: 2020-11-13 23:36:42 UTC; UCD
Author: Jalali Amirhossein [aut, cre] (<https://orcid.org/0000-0001-7227-8261>), Roshan Davood [aut] (<https://orcid.org/0000-0002-6553-640X>), Moghaddam Shirin [aut] (<https://orcid.org/0000-0002-9965-1510>), Newell John [aut] (<https://orcid.org/0000-0001-7685-6655>)
Maintainer: Jalali Amirhossein <amir.jalali@ucc.ie>
Repository: CRAN
Date/Publication: 2020-11-19 08:50:02 UTC

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New package RavenR with initial version 2.0.1
Package: RavenR
Type: Package
Title: Raven Hydrological Modelling Framework R Support and Analysis
Version: 2.0.1
Date: 2020-11-08
Authors@R: c( person("Robert", "Chlumsky", email = "rchlumsk@uwaterloo.ca", role = c("cre","aut")), person("James", "Craig", email = "jrcraig@uwaterloo.ca", role = "ctb"), person("Genevieve", "Brown", email = "genevieve.wbrown@gmail.com", role = "ctb"), person("Leland", "Scantlebury", email = "lscantlebury@uwaterloo.ca", role = "ctb"), person("Sarah", "Grass", email = "sgrass@nhcweb.com", role = "ctb"), person("Simon", "Lin", email = "simon.lin@uwaterloo.ca", role = "ctb"))
Description: Utilities for processing input and output files associated with the Raven Hydrological Modelling Framework. Includes various plotting functions, model diagnostics, reading output files into xts format, and support for writing Raven input files (rvt, rvh, rvc, etc.).
Note: Package is in active development; please report errors and suggestions to rchlumsk@uwaterloo.ca.
Depends: R (>= 4.0.0)
Imports: colorspace, cowplot, deldir, dplyr, dygraphs, gdata, ggplot2, grDevices, graphics, igraph, lubridate, magrittr, methods, ncdf4, purrr, reshape2, rgdal, rgeos, scales, sf, sp, stats, utils, xts, zoo
Suggests: devtools, magick, knitr, weathercan, tidyhydat
URL: https://github.com/rchlumsk/RavenR
License: GPL-3
Encoding: UTF-8
LazyData: TRUE
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-11-13 22:53:53 UTC; rchlumsk
Author: Robert Chlumsky [cre, aut], James Craig [ctb], Genevieve Brown [ctb], Leland Scantlebury [ctb], Sarah Grass [ctb], Simon Lin [ctb]
Maintainer: Robert Chlumsky <rchlumsk@uwaterloo.ca>
Repository: CRAN
Date/Publication: 2020-11-19 08:50:05 UTC

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New package qCBA with initial version 0.5.1
Package: qCBA
Title: Quantitative Classification by Association Rules
Version: 0.5.1
Date: 2020-11-18
Author: Tomas Kliegr
Maintainer: Tomas Kliegr <kliegr@gmail.com>
Description: CBA postprocessing algorithm that creates smaller models for datasets containing quantitative (numerical) attributes. Article describing QCBA is published in Tomas Kliegr (2017) <arXiv:1711.10166>. The package can also postprocess results of the SBRL package, which is no longer in CRAN, but can be obtained from <https://github.com/cran/sbrl>.
Depends: R (>= 2.7.0), arules (>= 1.6-6), rJava (>= 0.5-0), arc (>= 1.2), methods
Suggests: arulesCBA (>= 1.2.0), rCBA (>= 0.3.0), stringr
SystemRequirements: Java (>= 8)
URL: https://github.com/kliegr/QCBA
BugReports: https://github.com/kliegr/QCBA/issues
License: GPL-3
RoxygenNote: 7.0.2
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2020-11-18 10:44:02 UTC; tomas
Repository: CRAN
Date/Publication: 2020-11-19 08:30:03 UTC

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New package PortalHacienda with initial version 0.1.6
Package: PortalHacienda
Type: Package
Title: Acceder Con R a Los Datos Del Portal De Hacienda
Version: 0.1.6
Authors@R: person("Fernando", "Garcia Diaz", email = "fmgarciadiaz78@gmail.com", role = c("aut", "cre"))
Description: Obtener listado de datos, acceder y extender series del Portal de Datos de Hacienda.Las proyecciones se realizan con 'forecast', Hyndman RJ, Khandakar Y (2008) <doi:10.18637/jss.v027.i03>. Search, download and forecast time-series from the Ministry of Economy of Argentina. Forecasts are built with the 'forecast' package, Hyndman RJ, Khandakar Y (2008) <doi:10.18637/jss.v027.i03>.
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/fmgarciadiaz/PortalHacienda-CRAN
Imports: dplyr (>= 0.8.5), forecast (>= 8.12), timetk (>= 2.0), lubridate (>= 1.7.8), xts (>= 0.12-0), httr, tibble (>= 3.0.1), magrittr (>= 1.5), zoo (>= 1.8-8), curl, purrr
RoxygenNote: 7.1.1
Depends: R (>= 3.6.0)
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-11-19 01:20:51 UTC; fmgarciadiaz
Author: Fernando Garcia Diaz [aut, cre]
Maintainer: Fernando Garcia Diaz <fmgarciadiaz78@gmail.com>
Repository: CRAN
Date/Publication: 2020-11-19 08:20:14 UTC

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New package ordinalClust with initial version 1.3.5
Package: ordinalClust
Type: Package
Title: Ordinal Data Clustering, Co-Clustering and Classification
Version: 1.3.5
Date: 2020-10-26
Author: Margot Selosse, Julien Jacques, Christophe Biernacki
Maintainer: Margot Selosse <margot.selosse@gmail.com>
Description: Ordinal data classification, clustering and co-clustering using model-based approach with the BOS distribution for ordinal data (Christophe Biernacki and Julien Jacques (2016) <doi:10.1007/s11222-015-9585-2>).
License: GPL (>= 2)
Imports: Rcpp (>= 0.12.11), methods
LinkingTo: Rcpp, RcppProgress, RcppArmadillo, BH
Suggests: knitr, rmarkdown, caret, ggplot2
VignetteBuilder: knitr
LazyData: true
SystemRequirements: C++11
Depends: R (>= 3.3)
NeedsCompilation: yes
Packaged: 2020-11-03 13:18:36 UTC; margot
Repository: CRAN
Date/Publication: 2020-11-19 08:20:07 UTC

More information about ordinalClust at CRAN
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Package obfuscatoR updated to version 0.2.1 with previous version 0.2.0 dated 2019-08-01

Title: Obfuscation Game Designs
Description: When people make decisions, they may do so using a wide variety of decision rules. The package allows users to easily create obfuscation games to test the obfuscation hypothesis. It provides an easy to use interface and multiple options designed to vary the difficulty of the game and tailor it to the user's needs. For more detail: Chorus et al., 2021, Obfuscation maximization-based decision-making: Theory, methodology and first empirical evidence, Mathematical Social Sciences, 109, 28-44.
Author: Erlend Dancke Sandorf [aut, cre], Caspar Chorus [aut], Sander van Cranenburgh [aut]
Maintainer: Erlend Dancke Sandorf <erlend.dancke.sandorf@nmbu.no>

Diff between obfuscatoR versions 0.2.0 dated 2019-08-01 and 0.2.1 dated 2020-11-19

 DESCRIPTION                             |   24 
 MD5                                     |   87 -
 NAMESPACE                               |   24 
 NEWS.md                                 |   20 
 R/calc_entropy.R                        |  354 ++---
 R/calc_payouts.R                        |  264 ++--
 R/check_design_opt.R                    |   98 -
 R/construct_ra_mat.R                    |  270 ++--
 R/extract_attr.R                        |   62 -
 R/generate_designs.R                    |   88 -
 R/misc.R                                |   36 
 R/obfuscatoR.R                          |   28 
 R/on_attach.R                           |   69 -
 R/print_methods.R                       |  318 ++---
 R/save_design.R                         |  100 -
 build/vignette.rds                      |binary
 inst/CITATION                           |only
 inst/doc/vignette-obfuscatoR.R          |  237 +---
 inst/doc/vignette-obfuscatoR.Rmd        |  706 +++++------
 inst/doc/vignette-obfuscatoR.html       | 1893 ++++++++++++++++----------------
 man/calc_entropy.Rd                     |   62 -
 man/calc_payout_dm.Rd                   |   50 
 man/calc_payout_obs.Rd                  |   48 
 man/calc_pr_aj_rk.Rd                    |   40 
 man/calc_pr_guess.Rd                    |   52 
 man/calc_pr_rk_aj.Rd                    |   50 
 man/calculate_entropy.Rd                |   82 -
 man/calculate_payouts.Rd                |   75 -
 man/check_design_opt.Rd                 |   84 -
 man/construct_design.Rd                 |   46 
 man/dot-onAttach.Rd                     |   38 
 man/extract_attr.Rd                     |   62 -
 man/generate_designs.Rd                 |   58 
 man/last.Rd                             |   44 
 man/obfuscatoR.Rd                       |   27 
 man/print_design.Rd                     |   62 -
 man/print_entropy.Rd                    |   68 -
 man/print_payout.Rd                     |   38 
 man/save_design.Rd                      |   46 
 tests/testthat.R                        |    8 
 tests/testthat/test_calc_entropy.R      |   30 
 tests/testthat/test_calculate_entropy.R |   94 -
 tests/testthat/test_payouts.R           |   86 -
 vignettes/ref.bib                       |   37 
 vignettes/vignette-obfuscatoR.Rmd       |  706 +++++------
 45 files changed, 3331 insertions(+), 3340 deletions(-)

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New package gbeta with initial version 0.1.0
Package: gbeta
Type: Package
Title: Generalized Beta and Beta Prime Distributions
Version: 0.1.0
Author: Stéphane Laurent
Maintainer: Stéphane Laurent <laurent_step@outlook.fr>
Description: Density, distribution function, quantile function, and random generation for the generalized Beta and Beta prime distributions. The family of generalized Beta distributions is conjugate for the Bayesian binomial model, and the generalized Beta prime distribution is the posterior distribution of the relative risk in the Bayesian 'two Poisson samples' model when a Gamma prior is assigned to the Poisson rate of the reference group and a Beta prime prior is assigned to the relative risk. References: Laurent (2012) <doi:10.1214/11-BJPS139>, Hamza & Vallois (2016) <doi:10.1016/j.spl.2016.03.014>, Chen & Novick (1984) <doi:10.3102/10769986009002163>.
License: GPL (>= 2)
Imports: Rcpp (>= 1.0.5), gsl, Runuran
LinkingTo: Rcpp, RcppNumerical, RcppEigen
Encoding: UTF-8
RoxygenNote: 7.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/stla/gbeta
BugReports: https://github.com/stla/gbeta/issues
NeedsCompilation: yes
Packaged: 2020-11-14 09:00:22 UTC; stla
Repository: CRAN
Date/Publication: 2020-11-19 09:00:02 UTC

More information about gbeta at CRAN
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New package eurostat with initial version 3.6.83
Package: eurostat
Type: Package
Title: Tools for Eurostat Open Data
Date: 2020-11-17
Version: 3.6.83
Encoding: UTF-8
Authors@R: c( person("Leo", "Lahti", email = "leo.lahti@iki.fi", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-5537-637X")), person("Janne", "Huovari", role = "aut"), person("Markus", "Kainu", role = "aut"), person("Przemyslaw" , "Biecek", role = "aut"), person("Joona", "Lehtomaki", role = "ctb"), person("Francois", "Briatte", role = "ctb"), person("Oliver", "Reiter", role = "ctb"))
Maintainer: Leo Lahti <leo.lahti@iki.fi>
MailingList: rOpenGov <ropengov-forum@googlegroups.com>
Description: Tools to download data from the Eurostat database <http://ec.europa.eu/eurostat> together with search and manipulation utilities.
License: BSD_2_clause + file LICENSE
Depends: methods, R (>= 3.1.0)
Imports: broom, classInt, countrycode, curl, dplyr, httr, jsonlite, lubridate, RColorBrewer, readr, RefManageR, sf, sp, stringi, stringr, tibble, tidyr, tidyselect
Suggests: Cairo, ggplot2, knitr, mapproj, plotrix, markdown, rmarkdown, roxygen2, rsdmx, rvest, testthat, tmap, usethis
LazyData: true
URL: https://ropengov.github.io/eurostat/
BugReports: https://github.com/ropengov/eurostat/issues
VignetteBuilder: knitr
NeedsCompilation: no
Repository: CRAN
RoxygenNote: 7.1.1
Packaged: 2020-11-18 10:07:05 UTC; lei
Author: Leo Lahti [aut, cre] (<https://orcid.org/0000-0001-5537-637X>), Janne Huovari [aut], Markus Kainu [aut], Przemyslaw Biecek [aut], Joona Lehtomaki [ctb], Francois Briatte [ctb], Oliver Reiter [ctb]
Date/Publication: 2020-11-19 08:30:06 UTC

More information about eurostat at CRAN
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Package braidReports (with last version 0.5.3) was removed from CRAN

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

2016-04-08 0.5.3
2016-03-23 0.5.2

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Package campfin (with last version 1.0.3) was removed from CRAN

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

2020-11-09 1.0.3
2020-11-06 1.0.2
2020-11-05 1.0.1

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Package PDE (with last version 1.1.1) was removed from CRAN

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

2020-11-05 1.1.1
2020-11-04 1.1.0
2020-10-30 1.0.1
2020-10-30 1.0.2
2020-10-29 1.0.0

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Package RxODE (with last version 0.9.2-1) was removed from CRAN

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

2020-10-15 0.9.2-1

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