Wed, 07 Apr 2021

New package strucchangeRcpp with initial version 1.5-3-1.0.2
Package: strucchangeRcpp
Version: 1.5-3-1.0.2
Date: 2021-03-12
Title: Testing, Monitoring, and Dating Structural Changes: C++ Version
Authors@R: c(person(given = "Dainius", family = "Masiliunas", role = c("aut", "cre"), email = "pastas4@gmail.com", comment = c(ORCID = "0000-0001-5654-1277")), person(given = "Achim", family = "Zeileis", role = c("aut"), email = "Achim.Zeileis@R-project.org", comment = c(ORCID = "0000-0003-0918-3766")), person(given = "Marius", family = "Appel", role = "aut", email = "marius.appel@uni-muenster.de"), person(given = "Friedrich", family = "Leisch", role = "aut", email = "Friedrich.Leisch@R-project.org"), person(given = "Kurt", family = "Hornik", role = "aut", email = "Kurt.Hornik@R-project.org"), person(given = "Christian", family = "Kleiber", role = "aut", email = "Christian.Kleiber@unibas.ch"), person(given = "Andrei", family = "Mirt", role = "ctb", email = "andrei.mirt@wur.nl", comment = c(ORCID = "0000-0003-3654-2090")), person(given = "Bruce", family = "Hansen", role = "ctb"), person(given = c("Edgar", "C."), family = "Merkle", role = "ctb"))
Description: A fast implementation with additional experimental features for testing, monitoring and dating structural changes in (linear) regression models. 'strucchangeRcpp' features tests/methods from the generalized fluctuation test framework as well as from the F test (Chow test) framework. This includes methods to fit, plot and test fluctuation processes (e.g. cumulative/moving sum, recursive/moving estimates) and F statistics, respectively. These methods are described in Zeileis et al. (2002) <doi:10.18637/jss.v007.i02>. Finally, the breakpoints in regression models with structural changes can be estimated together with confidence intervals, and their magnitude as well as the model fit can be evaluated using a variety of statistical measures.
LazyData: yes
LinkingTo: Rcpp, RcppArmadillo
Depends: R (>= 2.10.0), zoo, sandwich
Suggests: stats4, car, dynlm, e1071, foreach, lmtest, mvtnorm, tseries, bfast
Imports: graphics, stats, Rcpp (>= 0.12.7), utils
License: GPL-2 | GPL-3
URL: https://github.com/bfast2/strucchangeRcpp/
BugReports: https://github.com/bfast2/strucchangeRcpp/issues
NeedsCompilation: yes
Packaged: 2021-04-07 18:04:17 UTC; dainius
Author: Dainius Masiliunas [aut, cre] (<https://orcid.org/0000-0001-5654-1277>), Achim Zeileis [aut] (<https://orcid.org/0000-0003-0918-3766>), Marius Appel [aut], Friedrich Leisch [aut], Kurt Hornik [aut], Christian Kleiber [aut], Andrei Mirt [ctb] (<https://orcid.org/0000-0003-3654-2090>), Bruce Hansen [ctb], Edgar C. Merkle [ctb]
Maintainer: Dainius Masiliunas <pastas4@gmail.com>
Repository: CRAN
Date/Publication: 2021-04-07 22:40:02 UTC

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Package readsparse updated to version 0.1.2 with previous version 0.1.1-2 dated 2021-04-06

Title: Read and Write Sparse Matrices in 'SVMLight' and 'LibSVM' Formats
Description: Read and write labelled sparse matrices in text format as used by software such as 'SVMLight', 'LibSVM', 'ThunderSVM', 'LibFM', 'xLearn', 'XGBoost', 'LightGBM', and others. Supports labelled data for regression, classification (binary, multi-class, multi-label), and ranking (with 'qid' field), and can handle header metadata and comments in files.
Author: David Cortes
Maintainer: David Cortes <david.cortes.rivera@gmail.com>

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Package aqp updated to version 1.29 with previous version 1.27 dated 2021-01-26

Title: Algorithms for Quantitative Pedology
Description: The Algorithms for Quantitative Pedology (AQP) project was started in 2009 to organize a loosely-related set of concepts and source code on the topic of soil profile visualization, aggregation, and classification into this package (aqp). Over the past 8 years, the project has grown into a suite of related R packages that enhance and simplify the quantitative analysis of soil profile data. Central to the AQP project is a new vocabulary of specialized functions and data structures that can accommodate the inherent complexity of soil profile information; freeing the scientist to focus on ideas rather than boilerplate data processing tasks <doi:10.1016/j.cageo.2012.10.020>. These functions and data structures have been extensively tested and documented, applied to projects involving hundreds of thousands of soil profiles, and deeply integrated into widely used tools such as SoilWeb <https://casoilresource.lawr.ucdavis.edu/soilweb-apps/>. Components of the AQP project (aqp, soilDB, sharpshootR, soilReports packages) serve an important role in routine data analysis within the USDA-NRCS Soil Science Division. The AQP suite of R packages offer a convenient platform for bridging the gap between pedometric theory and practice.
Author: Dylan Beaudette [aut, cre], Pierre Roudier [aut, ctb], Andrew Brown [aut, ctb]
Maintainer: Dylan Beaudette <dylan.beaudette@usda.gov>

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Package PogromcyDanych updated to version 1.7 with previous version 1.5 dated 2015-03-01

Title: DataCrunchers (PogromcyDanych) is the Massive Online Open Course that Brings R and Statistics to the People
Description: The data sets used in the online course ,,PogromcyDanych''. You can process data in many ways. The course Data Crunchers will introduce you to this variety. For this reason we will work on datasets of different size (from several to several hundred thousand rows), with various level of complexity (from two to two thousand columns) and prepared in different formats (text data, quantitative data and qualitative data). All of these data sets were gathered in a single big package called PogromcyDanych to facilitate access to them. It contains all sorts of data sets such as data about offer prices of cars, results of opinion polls, information about changes in stock market indices, data about names given to newborn babies, ski jumping results or information about outcomes of breast cancer patients treatment.
Author: Przemyslaw Biecek
Maintainer: Przemyslaw Biecek <przemyslaw.biecek@gmail.com>

Diff between PogromcyDanych versions 1.5 dated 2015-03-01 and 1.7 dated 2021-04-07

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Package plu updated to version 0.2.1 with previous version 0.2.0 dated 2021-01-11

Title: Dynamically Pluralize Phrases
Description: Converts English phrases to singular or plural form based on the length of an associated vector. Contains helper functions to create natural language lists from vectors and to include the length of a vector in natural language.
Author: Alexander Rossell Hayes [aut, cre, cph] (<https://orcid.org/0000-0001-9412-0457>)
Maintainer: Alexander Rossell Hayes <alexander@rossellhayes.com>

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Package neurobase updated to version 1.32.1 with previous version 1.32.0 dated 2021-03-31

Title: 'Neuroconductor' Base Package with Helper Functions for 'nifti' Objects
Description: Base package for 'Neuroconductor', which includes many helper functions that interact with objects of class 'nifti', implemented by package 'oro.nifti', for reading/writing and also other manipulation functions.
Author: John Muschelli [aut, cre]
Maintainer: John Muschelli <muschellij2@gmail.com>

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Package rNeighborGWAS updated to version 1.2.3 with previous version 1.2.2 dated 2020-11-23

Title: Testing Neighbor Effects in Marker-Based Regressions
Description: To incorporate neighbor genotypic identity into genome-wide association studies, the package provides a set of functions for variation partitioning and association mapping. The theoretical background of the method is described in Sato et al. (2021) <doi:10.1038/s41437-020-00401-w>.
Author: Yasuhiro Sato [aut, cre] (<https://orcid.org/0000-0002-6466-723X>), Eiji Yamamoto [aut], Kentaro K. Shimizu [aut] (<https://orcid.org/0000-0002-6483-1781>), Atsushi J. Nagano [aut] (<https://orcid.org/0000-0001-7891-5049>)
Maintainer: Yasuhiro Sato <sato.yasuhiro.36c@kyoto-u.jp>

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Package SimDesign updated to version 2.3 with previous version 2.2 dated 2020-11-07

Title: Structure for Organizing Monte Carlo Simulation Designs
Description: Provides tools to help safely and efficiently organize Monte Carlo simulations in R. The package controls the structure and back-end of Monte Carlo simulations by utilizing a general generate-analyse-summarise strategy. The functions provided control common simulation issues such as re-simulating non-convergent results, support parallel back-end and MPI distributed computations, save and restore temporary files, aggregate results across independent nodes, and provide native support for debugging. For a pedagogical introduction to the package refer to Sigal and Chalmers (2016) <doi:10.1080/10691898.2016.1246953>, and for an in-depth overview of the package and its design philosophy see Chalmers and Adkins (2020) <doi:10.20982/tqmp.16.4.p248>.
Author: Phil Chalmers [aut, cre] (<https://orcid.org/0000-0001-5332-2810>), Matthew Sigal [ctb], Ogreden Oguzhan [ctb]
Maintainer: Phil Chalmers <rphilip.chalmers@gmail.com>

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Package RLumModel updated to version 0.2.8 with previous version 0.2.7 dated 2020-09-04

Title: Solving Ordinary Differential Equations to Understand Luminescence
Description: A collection of functions to simulate luminescence signals in quartz and Al2O3 based on published models.
Author: Johannes Friedrich [aut, trl, cre] (<https://orcid.org/0000-0002-0805-9547>), Sebastian Kreutzer [aut, ths] (<https://orcid.org/0000-0002-0734-2199>), Christoph Schmidt [aut, ths] (<https://orcid.org/0000-0002-2309-3209>)
Maintainer: Johannes Friedrich <johannes.friedrich@posteo.de>

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Package periscope updated to version 0.6.3 with previous version 0.6.2 dated 2021-03-22

Title: Enterprise Streamlined 'Shiny' Application Framework
Description: An enterprise-targeted scalable and UI-standardized 'shiny' framework including a variety of developer convenience functions with the goal of both streamlining robust application development while assisting with creating a consistent user experience regardless of application or developer.
Author: Constance Brett [aut, cre], Isaac Neuhaus [aut] (canvasXpress JavaScript Library Maintainer), Ger Inberg [ctb], Bristol-Meyers Squibb (BMS) [cph]
Maintainer: Constance Brett <connie@aggregate-genius.com>

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Package Gmedian updated to version 1.2.6 with previous version 1.2.5 dated 2020-03-02

Title: Geometric Median, k-Medians Clustering and Robust Median PCA
Description: Fast algorithms for robust estimation with large samples of multivariate observations. Estimation of the geometric median, robust k-Gmedian clustering, and robust PCA based on the Gmedian covariation matrix.
Author: Herve Cardot
Maintainer: Herve Cardot <herve.cardot@u-bourgogne.fr>

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Package blocksdesign updated to version 4.9 with previous version 4.8 dated 2021-02-26

Title: Nested and Crossed Block Designs for Factorial and Unstructured Treatment Sets
Description: Constructs treatment and block designs for linear treatment models with crossed or nested block factors. The treatment design can be any feasible linear model and the block design can be any feasible combination of crossed or nested block factors. The block design is a sum of one or more block factors and the block design is optimized sequentially with the levels of each successive block factor optimized conditional on all previously optimized block factors. D-optimality is used throughout except for square or rectangular lattice block designs which are constructed algebraically using mutually orthogonal Latin squares. Crossed block designs with interaction effects are optimized using a weighting scheme which allows for differential weighting of first and second-order block effects. Outputs include a table showing the allocation of treatments to blocks and tables showing the achieved D-efficiency factors for each block and treatment design. Edmondson, R.N. Multi-level Block Designs for Comparative Experiments. JABES 25, 500–522 (2020) <doi:10.1007/s13253-020-00416-0>.
Author: R. N. Edmondson.
Maintainer: Rodney Edmondson <rodney.edmondson@gmail.com>

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Package bhmbasket updated to version 0.9.2 with previous version 0.9.1 dated 2021-02-15

Title: Bayesian Hierarchical Models for Basket Trials
Description: Provides functions for the evaluation of basket trial designs with binary endpoints. Operating characteristics of a basket trial design are assessed by simulating trial data according to scenarios, analyzing the data with Bayesian hierarchical models (BHMs), and assessing decision probabilities on stratum and trial-level based on Go / No-go decision making. The package is build for high flexibility regarding decision rules, number of interim analyses, number of strata, and recruitment. The BHMs proposed by Berry et al. (2013) <doi:10.1177/1740774513497539> and Neuenschwander et al. (2016) <doi:10.1002/pst.1730>, as well as a model that combines both approaches are implemented. Functions are provided to implement Bayesian decision rules as for example proposed by Fisch et al. (2015) <doi:10.1177/2168479014533970>. In addition, posterior point estimates (mean/median) and credible intervals for response rates and some model parameters can be calculated. For simulated trial data, bias and mean squared errors of posterior point estimates for response rates can be provided.
Author: Stephan Wojciekowski [aut, cre]
Maintainer: Stephan Wojciekowski <stephan.wojciekowski@boehringer-ingelheim.com>

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Package npde updated to version 3.1 with previous version 3.0 dated 2021-02-25

Title: Normalised Prediction Distribution Errors for Nonlinear Mixed-Effect Models
Description: Provides routines to compute normalised prediction distribution errors, a metric designed to evaluate non-linear mixed effect models such as those used in pharmacokinetics and pharmacodynamics. Documentation about 'npde' is provided by a comprehensive user guide on the github repository (<https://github.com/ecomets/npde30/blob/main/userguide_npde_3.0.pdf>), and references concerning the methods include the papers by Brendel et al. (2006, <doi:10.1007/s11095-006-9067-5>; 2010, <doi:10.1007/s10928-009-9143-7>), Comets et al. (2008, <doi:10.1016/j.cmpb.2007.12.002> ; 2010, <http://journal-sfds.fr/article/view/45>), and Nguyen et al. (2012, <doi:10.1007/s10928-012-9264-2>). See 'citation("npde")' for details.
Author: Emmanuelle Comets [aut, cre] (<https://orcid.org/0000-0002-9150-9886>), Karl Brendel [ctb], Thi Huyen Tram Nguyen [ctb], Romain Leroux [ctb], France Mentre [ctb]
Maintainer: Emmanuelle Comets <emmanuelle.comets@inserm.fr>

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Package WhiteStripe updated to version 2.4.0 with previous version 2.3.2 dated 2019-10-01

Title: White Matter Normalization for Magnetic Resonance Images using WhiteStripe
Description: Shinohara (2014) <doi:10.1016/j.nicl.2014.08.008> introduced 'WhiteStripe', an intensity-based normalization of T1 and T2 images, where normal appearing white matter performs well, but requires segmentation. This method performs white matter mean and standard deviation estimates on data that has been rigidly-registered to the 'MNI' template and uses histogram-based methods.
Author: R. Taki Shinohara [aut], John Muschelli [aut, cre] (<https://orcid.org/0000-0001-6469-1750>)
Maintainer: John Muschelli <muschellij2@gmail.com>

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Package stevedata updated to version 0.3.1 with previous version 0.3.0 dated 2021-02-27

Title: Steve's Toy Data for Teaching About a Variety of Methodological, Social, and Political Topics
Description: This is an R package for all my toy data. Its main uses are for teaching. My students, and academics like me who teach the same topics I teach, should find this useful if their teaching workflow is also built around the R programming language. The applications are multiple but mostly cluster on topics of statistical methodology, international relations, and political economy.
Author: Steve Miller [aut, cre] (<https://orcid.org/0000-0003-4072-6263>)
Maintainer: Steve Miller <steven.v.miller@gmail.com>

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Package tidypaleo updated to version 0.1.1 with previous version 0.1.0 dated 2021-03-31

Title: Tidy Tools for Paleoenvironmental Archives
Description: Provides a set of functions with a common framework for age-depth model management, stratigraphic visualization, and common statistical transformations. The focus of the package is stratigraphic visualization, for which 'ggplot2' components are provided to reproduce the scales, geometries, facets, and theme elements commonly used in publication-quality stratigraphic diagrams. Helpers are also provided to reproduce the exploratory statistical summaries that are frequently included on stratigraphic diagrams.
Author: Dewey Dunnington [aut, cre, cph] (<https://orcid.org/0000-0002-9415-4582>)
Maintainer: Dewey Dunnington <dewey@fishandwhistle.net>

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Package rvkstat updated to version 3.0.1 with previous version 3.0.0 dated 2021-01-15

Title: R Interface to API 'vk.com'
Description: Load data from vk.com api about your communiti users and views, ads performance, post on user wall and etc. For more information see API Documentation <https://vk.com/dev/first_guide>.
Author: Alexey Seleznev
Maintainer: Alexey Seleznev <selesnow@gmail.com>

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Package RTL updated to version 0.1.6 with previous version 0.1.5 dated 2020-11-11

Title: Risk Tool Library
Description: Collection of functions and metadata to complement core packages in Finance and Commodities, including futures expiry tables and <https://www.morningstar.com/products/commodities-and-energy> API functions. See <https://github.com/risktoollib/RTL>.
Author: Philippe Cote [aut, cre], Nima Safaian [aut]
Maintainer: Philippe Cote <pcote@ualberta.ca>

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Package prcbench updated to version 1.0.1 with previous version 0.9.1 dated 2021-01-07

Title: Testing Workbench for Precision-Recall Curves
Description: A testing workbench for evaluating precision-recall curves under various conditions.
Author: Takaya Saito [aut, cre], Marc Rehmsmeier [aut]
Maintainer: Takaya Saito <takaya.saito@outlook.com>

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Package msmtools updated to version 2.0.0 with previous version 1.3 dated 2017-06-08

Title: Building Augmented Data to Run Multi-State Models with 'msm' Package
Description: A fast and general method for restructuring classical longitudinal data into augmented ones. The reason for this is to facilitate the modeling of longitudinal data under a multi-state framework using the 'msm' package.
Author: Francesco Grossetti [aut, cre] (<https://orcid.org/0000-0002-5130-7745>)
Maintainer: Francesco Grossetti <francesco.grossetti@unibocconi.it>

Diff between msmtools versions 1.3 dated 2017-06-08 and 2.0.0 dated 2021-04-07

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New package FateID with initial version 0.2.0
Package: FateID
Title: Quantification of Fate Bias in Multipotent Progenitors
Version: 0.2.0
Date: 2021-03-27
Author: Dominic Grün <dominic.gruen@gmail.com>
Maintainer: Dominic Grün <dominic.gruen@gmail.com>
Description: Application of 'FateID' allows computation and visualization of cell fate bias for multi-lineage single cell transcriptome data. Herman, J.S., Sagar, Grün D. (2018) <DOI:10.1038/nmeth.4662>.
Depends: R (>= 3.5.0)
biocViews:
Imports: graphics, grDevices, lle, locfit, matrixStats, pheatmap, princurve, randomForest, RColorBrewer, Rtsne, som, stats, umap, utils
Suggests: DESeq2, knitr, rmarkdown
VignetteBuilder: knitr
License: GPL-3
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2021-04-06 13:45:41 UTC; d.grun
Repository: CRAN
Date/Publication: 2021-04-07 13:20:13 UTC

More information about FateID at CRAN
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Package ellipticalsymmetry updated to version 0.1.2 with previous version 0.1 dated 2020-11-30

Title: Elliptical Symmetry Tests
Description: Given the omnipresence of the assumption of elliptical symmetry, it is essential to be able to test whether that assumption actually holds true or not for the data at hand. This package provides several statistical tests for elliptical symmetry that are described in Babic et al. (2021) <arXiv:2011.12560v2>.
Author: Sladana Babic [aut] (<https://orcid.org/0000-0001-8076-4665>), Marko Palangetic [aut, cre] (<https://orcid.org/0000-0002-6366-0634>), Christophe Ley [aut] (<https://orcid.org/0000-0002-2290-8437>)
Maintainer: Marko Palangetic <marko.palangetic@ugent.be>

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Package CAST updated to version 0.5.1 with previous version 0.5.0 dated 2021-02-19

Title: 'caret' Applications for Spatial-Temporal Models
Description: Supporting functionality to run 'caret' with spatial or spatial-temporal data. 'caret' is a frequently used package for model training and prediction using machine learning. This package includes functions to improve spatial-temporal modelling tasks using 'caret'. It prepares data for Leave-Location-Out and Leave-Time-Out cross-validation which are target-oriented validation strategies for spatial-temporal models. To decrease overfitting and improve model performances, the package implements a forward feature selection that selects suitable predictor variables in view to their contribution to the target-oriented performance. CAST further includes functionality to estimate the (spatial) area of applicability of prediction models by analysing the similarity between new data and training data.
Author: Hanna Meyer [cre, aut], Chris Reudenbach [ctb], Marvin Ludwig [ctb], Thomas Nauss [ctb], Edzer Pebesma [ctb]
Maintainer: Hanna Meyer <hanna.meyer@uni-muenster.de>

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New package bayesDccGarch with initial version 2.2
Package: bayesDccGarch
Version: 2.2
Date: 2021-04-01
Title: The Bayesian Dynamic Conditional Correlation GARCH Model
Description: Bayesian estimation of dynamic conditional correlation GARCH model for multivariate time series volatility (Fioruci, J.A., Ehlers, R.S. and Andrade-Filho, M.G., (2014). <doi:10.1080/02664763.2013.839635>.
Depends: R (>= 2.0), numDeriv, coda
Authors@R: c( person("Jose Augusto", "Fiorucci", email="jafiorucci@gmail.com", role=c("aut", "cre", "cph"), comment = c(ORCID = "0000-0002-1201-9089")), person("Ricardo", "Sanders Ehlers", email="ehlers@icmc.usp.br", role=c("aut", "cph"), comment = c(ORCID = "0000-0001-9034-5173")), person("Francisco", "Louzada", email="louzada@icmc.usp.br", role=c("aut", "cph"), comment = c(ORCID = "0000-0001-7815-9554")) )
Author: Jose Augusto Fiorucci [aut, cre, cph] (<https://orcid.org/0000-0002-1201-9089>), Ricardo Sanders Ehlers [aut, cph] (<https://orcid.org/0000-0001-9034-5173>), Francisco Louzada [aut, cph] (<https://orcid.org/0000-0001-7815-9554>)
Maintainer: Jose Augusto Fiorucci <jafiorucci@gmail.com>
BugReports: https://github.com/jafiorucci/bayesDccGarch/issues
License: GPL (>= 2)
URL: https://ui.adsabs.harvard.edu/abs/2014arXiv1412.2967F/abstract
NeedsCompilation: yes
Repository: CRAN
Packaged: 2021-04-06 18:33:27 UTC; jafio
Date/Publication: 2021-04-07 13:20:10 UTC

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Permanent link

Package rtsVis updated to version 0.0.2 with previous version 0.0.1 dated 2021-02-24

Title: Raster Time Series Visualization
Description: A lightweight 'R' package to visualize large raster time series, building on a fast temporal interpolation core.
Author: Johannes Mast [aut, cre] (<https://orcid.org/0000-0001-6595-5834>), Jakob Schwalb-Willmann [aut] (<https://orcid.org/0000-0003-2665-1509>)
Maintainer: Johannes Mast <johannes.mast@stud-mail.uni-wuerzburg.de>

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Package aopdata updated to version 0.2.1 with previous version 0.2.0 dated 2021-03-31

Title: Data from the 'Access to Opportunities Project (AOP)'
Description: Download data from the 'Access to Opportunities Project (AOP)'. The 'aopdata' package brings annual estimates of access to employment, health and education services by transport mode, as well as data on the spatial distribution of population, schools and health-care facilities at a fine spatial resolution for all cities included in the study. More info on the 'AOP' website <https://www.ipea.gov.br/acessooportunidades/en/>.
Author: Rafael H. M. Pereira [aut, cre] (<https://orcid.org/0000-0003-2125-7465>), Daniel Herszenhut [aut] (<https://orcid.org/0000-0001-8066-1105>), Marcus Saraiva [aut] (<https://orcid.org/0000-0001-6218-2338>), Ipea - Institue for Applied Economic Research [cph, fnd]
Maintainer: Rafael H. M. Pereira <rafa.pereira.br@gmail.com>

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Package akiFlagger updated to version 0.3.0 with previous version 0.2.0 dated 2021-03-14

Title: Flags Acute Kidney Injury (AKI)
Description: Flagger to detect acute kidney injury (AKI) in a patient dataset.
Author: Ishan Saran [aut, cre], Shivam Saran [aut], Rishi Saran [aut], Aditya Biswas [ctb], Sankee Mummareddy [ctb], Yu Yamamoto [ctb], Francis Perry Wilson [ctb, ths]
Maintainer: Ishan Saran <ishansaran65@gmail.com>

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Package zoolog updated to version 0.3.0 with previous version 0.2.1 dated 2021-02-17

Title: Zooarchaeological Analysis with Log-Ratios
Description: Includes functions and reference data to generate and manipulate log-ratios (also known as log size index (LSI) values) from measurements obtained on zooarchaeological material. Log ratios are used to compare the relative (rather than the absolute) dimensions of animals from archaeological contexts (Meadow 1999, ISBN: 9783896463883). zoolog is also able to seamlessly integrate data and references with heterogeneous nomenclature, which is internally managed by a zoolog thesaurus. A preliminary version of the zoolog methods was first used by Trentacoste, Nieto-Espinet, and Valenzuela-Lamas (2018) <doi:10.1371/journal.pone.0208109>.
Author: Jose M Pozo [aut, cre] (<https://orcid.org/0000-0002-0759-3510>), Silvia Valenzuela-Lamas [aut] (<https://orcid.org/0000-0001-9886-0372>), Angela Trentacoste [aut] (<https://orcid.org/0000-0001-7096-5252>), Ariadna Nieto-Espinet [aut] (<https://orcid.org/0000-0003-2567-1735>), Silvia Guimarães Chiarelli [aut] (<https://orcid.org/0000-0002-3778-3315>)
Maintainer: Jose M Pozo <josmpozo@gmail.com>

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Package viromeBrowser updated to version 1.1.0 with previous version 1.0.0 dated 2019-08-21

Title: Virome Sequencing Analysis Result Browser
Description: Experiments in which highly complex virome sequencing data is generated are difficult to visualize and unpack for a person without programming experience. After processing of the raw sequencing data by a next generation sequencing (NGS) processing pipeline the usual output consists of contiguous sequences (contigs) in fasta format and an annotation file linking the contigs to a reference sequence. The virome analysis browser app imports an annotation file, a corresponding fasta file containing the annotated contigs and a alignment file in BAM format of the sequence reads aligned to the contigs. It facilitates browsing of annotations in multiple files and allows users to select and export specific annotated sequences from the associated fasta files. Various annotation quality thresholds can be set to filter contigs from the annotation files. Further inspection of selected contigs can be done in the form of automatic open reading frame (ORF) detection. Separate contigs and/or separate ORFs can be downloaded in nucleotide or amino acid format for further analysis.
Author: David Nieuwenhuijse [aut, cre]
Maintainer: David Nieuwenhuijse <d.nieuwenhuijse@erasmusmc.nl>

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Package rayrender updated to version 0.21.2 with previous version 0.21.1 dated 2021-04-03

Title: Build and Raytrace 3D Scenes
Description: Render scenes using pathtracing. Build 3D scenes out of spheres, cubes, planes, disks, triangles, cones, curves, line segments, cylinders, ellipsoids, and 3D models in the 'Wavefront' OBJ file format or the PLY Polygon File Format. Supports several material types, textures, multicore rendering, and tone-mapping. Based on the "Ray Tracing in One Weekend" book series. Peter Shirley (2018) <https://raytracing.github.io>.
Author: Tyler Morgan-Wall [aut, cph, cre] (<https://orcid.org/0000-0002-3131-3814>), Syoyo Fujita [ctb, cph], Melissa O'Neill [ctb, cph], Vilya Harvey [ctb, cph]
Maintainer: Tyler Morgan-Wall <tylermw@gmail.com>

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Package mschart updated to version 0.2.6 with previous version 0.2.5 dated 2019-11-14

Title: Chart Generation for 'Microsoft Word' and 'Microsoft PowerPoint' Documents
Description: Create native charts for 'Microsoft PowerPoint' and 'Microsoft Word' documents. These can then be edited and annotated. Functions are provided to let users create charts, modify and format their content. The chart's underlying data is automatically saved within the 'Word' document or 'PowerPoint' presentation. It extends package 'officer' that does not contain any feature for 'Microsoft' native charts production.
Author: David Gohel [aut, cre], ArData [cph], YouGov [fnd], David Camposeco [ctb] (chart_data_smooth function)
Maintainer: David Gohel <david.gohel@ardata.fr>

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Package LibOPF updated to version 2.6.1 with previous version 2.6.0 dated 2020-04-12

Title: Design of Optimum-Path Forest Classifiers
Description: The 'LibOPF' is a framework to develop pattern recognition techniques based on optimum-path forests (OPF), João P. Papa and Alexandre X. Falcão (2008) <doi:10.1007/978-3-540-89639-5_89>, with methods for supervised learning and data clustering.
Author: Rafael Junqueira Martarelli [aut, cre], João Paulo Papa [aut], Alexandre Xavier Falcão [cph]
Maintainer: Rafael Junqueira Martarelli <rfel.jm@gmail.com>

Diff between LibOPF versions 2.6.0 dated 2020-04-12 and 2.6.1 dated 2021-04-07

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Permanent link

Package ggstar updated to version 1.0.2 with previous version 1.0.1 dated 2021-02-10

Title: Multiple Geometric Shape Point Layer for 'ggplot2'
Description: To create the multiple polygonal point layer for easily discernible shapes, we developed the package, it is like the 'geom_point' of 'ggplot2'. It can be used to draw the scatter plot.
Author: Shuangbin Xu [aut, cre] (<https://orcid.org/0000-0003-3513-5362>)
Maintainer: Shuangbin Xu <xshuangbin@163.com>

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New package TAF with initial version 4.0.0
Package: TAF
Version: 4.0.0
Date: 2021-04-06
Title: Functions to Support the ICES Transparent Assessment Framework
Authors@R: c(person("Arni", "Magnusson", role=c("aut","cre"), email="thisisarni@gmail.com"), person("Colin", "Millar", role="aut"), person("Alexandros", "Kokkalis", role="ctb"), person("Iago", "Mosqueira", role="ctb"), person("Ibrahim", "Umar", role="ctb"), person("Hjalte", "Parner", role="ctb"))
Imports: grDevices, lattice, stats, tools, utils
LazyData: yes
Description: Functions to support the ICES Transparent Assessment Framework <https://taf.ices.dk> to organize data, methods, and results used in ICES assessments. ICES is an organization facilitating international collaboration in marine science.
License: GPL-3
URL: https://taf.ices.dk
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2021-04-06 12:22:48 UTC; arnima
Author: Arni Magnusson [aut, cre], Colin Millar [aut], Alexandros Kokkalis [ctb], Iago Mosqueira [ctb], Ibrahim Umar [ctb], Hjalte Parner [ctb]
Maintainer: Arni Magnusson <thisisarni@gmail.com>
Repository: CRAN
Date/Publication: 2021-04-07 09:30:11 UTC

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Package stabm updated to version 1.2.1 with previous version 1.2.0 dated 2021-03-30

Title: Stability Measures for Feature Selection
Description: An implementation of many measures for the assessment of the stability of feature selection. Both simple measures and measures which take into account the similarities between features are available, see Bommert (2020) <doi:10.17877/DE290R-21906>.
Author: Andrea Bommert [aut, cre] (<https://orcid.org/0000-0002-1005-9351>), Michel Lang [aut] (<https://orcid.org/0000-0001-9754-0393>)
Maintainer: Andrea Bommert <bommert@statistik.tu-dortmund.de>

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Permanent link

New package SpatEntropy with initial version 2.0-1
Package: SpatEntropy
Title: Spatial Entropy Measures
Version: 2.0-1
Author: L. Altieri, D. Cocchi, G. Roli
Maintainer: Altieri Linda <linda.altieri@unibo.it>
Depends: R (>= 3.5.0), spatstat (>= 2.0-0)
Imports: spatstat.geom, spatstat.core, spatstat.linnet
Description: The heterogeneity of spatial data presenting a finite number of categories can be measured via computation of spatial entropy. Functions are available for the computation of the main entropy and spatial entropy measures in the literature. They include the traditional version of Shannon's entropy (Shannon, 1948 <doi:10.1002/j.1538-7305.1948.tb01338.x>), Batty's spatial entropy (Batty, 1974 <doi:10.1111/j.1538-4632.1974.tb01014.x>), O'Neill's entropy (O'Neill et al., 1998 <doi:10.1007/BF00162741>), Li and Reynolds' contagion index (Li and Reynolds, 1993 <doi:10.1007/BF00125347>), Karlstrom and Ceccato's entropy (Karlstrom and Ceccato, 2002 <urn:nbn:se:kth:diva-61351>), Leibovici's entropy (Leibovici, 2009 <doi:10.1007/978-3-642-03832-7_24>), Parresol and Edwards' entropy (Parresol and Edwards, 2014 <doi:10.3390/e16041842>) and Altieri's entropy (Altieri et al., 2018, <doi:10.1007/s10651-017-0383-1>). Full references for all measures can be found under the topic 'SpatEntropy'. The package is able to work with lattice and point data. The updated version works with the updated 'spatstat' package (>= 2.0-0). It also provides a more intuitive framework for all functions, including improved examples, and new data. The speed of most functions has also been substantially increased.
License: GPL-3
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2021-04-06 12:53:21 UTC; linda.altieri4
Repository: CRAN
Date/Publication: 2021-04-07 09:50:02 UTC

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Package spaMM updated to version 3.7.34 with previous version 3.7.2 dated 2021-02-26

Title: Mixed-Effect Models, Particularly Spatial Models
Description: Inference based on mixed-effect models, including generalized linear mixed models with spatial correlations, multivariate responses, and models with non-Gaussian random effects (e.g., Beta). Various approximations of likelihood or restricted likelihood are implemented, in particular Laplace approximation and h-likelihood (Lee and Nelder 2001 <doi:10.1093/biomet/88.4.987>). Both classical geostatistical models, and Markov random field models on irregular grids (as considered in the 'INLA' package, <https://www.r-inla.org>), can be fitted. Variation in residual variance (heteroscedasticity) can itself be represented by a mixed-effect model.
Author: François Rousset [aut, cre, cph] (<https://orcid.org/0000-0003-4670-0371>), Jean-Baptiste Ferdy [aut, cph], Alexandre Courtiol [aut] (<https://orcid.org/0000-0003-0637-2959>), GSL authors [ctb] (src/gsl_bessel.*)
Maintainer: François Rousset <francois.rousset@umontpellier.fr>

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Permanent link

Package redist updated to version 3.0.1 with previous version 2.0.2 dated 2020-10-13

Title: Simulation Methods for Legislative Redistricting
Description: Enables researchers to sample redistricting plans from a pre-specified target distribution using Sequential Monte Carlo and Markov Chain Monte Carlo algorithms. The package allows for the implementation of various constraints in the redistricting process such as geographic compactness and population parity requirements. Tools for analysis such as computation of various summary statistics and plotting functionality are also included. The package implements methods described in Fifield, Higgins, Imai and Tarr (2020) <doi: 10.1080/10618600.2020.1739532>, Fifield, Imai, Kawahara, and Kenny (2020) <doi: 10.1080/2330443X.2020.1791773>, and McCartan and Imai (2020) <arXiv: 2008.06131>.
Author: Christopher T. Kenny [aut, cre], Cory McCartan [aut], Ben Fifield [aut], Kosuke Imai [aut], Jun Kawahara [ctb], Alexander Tarr [ctb], Michael Higgins [ctb]
Maintainer: Christopher T. Kenny <christopherkenny@fas.harvard.edu>

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Package NonParRolCor updated to version 0.6.0 with previous version 0.4.0 dated 2021-03-31

Title: a Non-Parametric Statistical Significance Test for Rolling Correlation
Description: Estimates and plots (as a heat map) the statistical significance of rolling window correlation coefficients, which is carried out through a non-parametric computing-intensive method. This method addresses the effects due to the multiple testing (inflation of the Type I error) when the statistical significance is estimated for the rolling window correlation coefficients. The method is based on Monte Carlo simulations by permuting one of the variables (dependent) under analysis and keeping fixed the other variable (independent). We improve the computational efficiency of this method to reduce the computation time through parallel computing. The 'NonParRolCor' package also provides examples with synthetic and real-life ecological time series to exemplify its use. Methods derived from R. Telford (2013) <https://quantpalaeo.wordpress.com/2013/01/04/> and J.M. Polanco-Martinez (2020) <doi:10.1016/j.ecoinf.2020.101163>.
Author: Josue M. Polanco-Martinez [aut, cph, cre] (<https://orcid.org/0000-0001-7164-0185>), Jose L. Lopez-Martinez [ctb] (<https://orcid.org/0000-0002-2489-7559>)
Maintainer: Josue M. Polanco-Martinez <josue.m.polanco@gmail.com>

Diff between NonParRolCor versions 0.4.0 dated 2021-03-31 and 0.6.0 dated 2021-04-07

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Package HSAUR3 updated to version 1.0-11 with previous version 1.0-10 dated 2020-09-21

Title: A Handbook of Statistical Analyses Using R (3rd Edition)
Description: Functions, data sets, analyses and examples from the third edition of the book ''A Handbook of Statistical Analyses Using R'' (Torsten Hothorn and Brian S. Everitt, Chapman & Hall/CRC, 2014). The first chapter of the book, which is entitled ''An Introduction to R'', is completely included in this package, for all other chapters, a vignette containing all data analyses is available. In addition, Sweave source code for slides of selected chapters is included in this package (see HSAUR3/inst/slides). The publishers web page is '<http://www.crcpress.com/product/isbn/9781482204582>'.
Author: Torsten Hothorn and Brian S. Everitt
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

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Package hawkesbow updated to version 1.0.1 with previous version 1.0.0 dated 2021-03-31

Title: Estimation of Hawkes Processes from Binned Observations
Description: Implements an estimation method for Hawkes processes when count data are only observed in discrete time, using a spectral approach derived from the Bartlett spectrum, see Cheysson and Lang (2020) <arXiv:2003.04314>. Some general use functions for Hawkes processes are also included: simulation of (in)homogeneous Hawkes process, maximum likelihood estimation, residual analysis, etc.
Author: Felix Cheysson [aut, cre] (<https://orcid.org/0000-0002-9095-2878>)
Maintainer: Felix Cheysson <felix@cheysson.fr>

Diff between hawkesbow versions 1.0.0 dated 2021-03-31 and 1.0.1 dated 2021-04-07

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Package dparser updated to version 1.3.1-4 with previous version 1.3.1-3 dated 2021-04-06

Title: Port of 'Dparser' Package
Description: A Scannerless GLR parser/parser generator. Note that GLR standing for "generalized LR", where L stands for "left-to-right" and R stands for "rightmost (derivation)". For more information see <https://en.wikipedia.org/wiki/GLR_parser>. This parser is based on the Tomita (1987) algorithm. (Paper can be found at <https://www.aclweb.org/anthology/P84-1073.pdf>). The original 'dparser' package documentation can be found at <http://dparser.sourceforge.net/>. This allows you to add mini-languages to R (like RxODE's ODE mini-language Wang, Hallow, and James 2015 <DOI:10.1002/psp4.12052>) or to parse other languages like 'NONMEM' to automatically translate them to R code. To use this in your code, add a LinkingTo dparser in your DESCRIPTION file and instead of using #include <dparse.h> use #include <dparser.h>. This also provides a R-based port of the make_dparser <http://dparser.sourceforge.net/d/make_dparser.cat> command called mkdparser(). Additionally you can parse an arbitrary grammar within R using the dparse() function, which works on most OSes and is mainly for grammar testing. The fastest parsing, of course, occurs at the C level, and is suggested.
Author: Matthew Fidler [aut, cre], John Plevyak [aut, cph]
Maintainer: Matthew Fidler <matthew.fidler@gmail.com>

Diff between dparser versions 1.3.1-3 dated 2021-04-06 and 1.3.1-4 dated 2021-04-07

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Package devtools updated to version 2.4.0 with previous version 2.3.2 dated 2020-09-18

Title: Tools to Make Developing R Packages Easier
Description: Collection of package development tools.
Author: Hadley Wickham [aut], Jim Hester [aut, cre], Winston Chang [aut], RStudio [cph, fnd]
Maintainer: Jim Hester <jim.hester@rstudio.com>

Diff between devtools versions 2.3.2 dated 2020-09-18 and 2.4.0 dated 2021-04-07

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Package bsts updated to version 0.9.6 with previous version 0.9.5 dated 2020-05-02

Title: Bayesian Structural Time Series
Description: Time series regression using dynamic linear models fit using MCMC. See Scott and Varian (2014) <DOI:10.1504/IJMMNO.2014.059942>, among many other sources.
Author: Steven L. Scott <steve.the.bayesian@gmail.com>
Maintainer: Steven L. Scott <steve.the.bayesian@gmail.com>

Diff between bsts versions 0.9.5 dated 2020-05-02 and 0.9.6 dated 2021-04-07

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Package AlleleShift updated to version 1.0-1 with previous version 0.9-2 dated 2021-01-29

Title: Predict and Visualize Population-Level Changes in Allele Frequencies in Response to Climate Change
Description: Methods (Kindt, R. 2021. <doi:10.1101/2021.01.15.426775>) are provided of calibrating and predicting shifts in allele frequencies through redundancy analysis ('vegan::rda()') and generalized additive models ('mgcv::gam()'). Visualization functions for predicted changes in allele frequencies include 'shift.dot.ggplot()', 'shift.pie.ggplot()', 'shift.moon.ggplot()', 'shift.waffle.ggplot()' and 'shift.surf.ggplot()' that are made with input data sets that are prepared by helper functions for each visualization method. Examples in the documentation show how to prepare animated climate change graphics through a time series with the 'gganimate' package. Function 'amova.rda()' shows how Analysis of Molecular Variance can be directly conducted with the results from redundancy analysis.
Author: Roeland Kindt [cre, aut] (<https://orcid.org/0000-0002-7672-0712>)
Maintainer: Roeland Kindt <R.KINDT@CGIAR.ORG>

Diff between AlleleShift versions 0.9-2 dated 2021-01-29 and 1.0-1 dated 2021-04-07

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New package svplots with initial version 0.1.0
Package: svplots
Title: Sample Variance Plots (Sv-Plots)
Version: 0.1.0
Author: Uditha Amarananda Wijesuriya <u.wijesuriya@usi.edu>
Maintainer: Uditha Amarananda Wijesuriya <u.wijesuriya@usi.edu>
Description: Two versions of sample variance plots, Sv-plot1 and Sv-plot2, will be provided illustrating the squared deviations from sample variance. Besides indicating the contribution of squared deviations for the sample variability, these plots are capable of detecting characteristics of the distribution such as symmetry, skewness and outliers. A remarkable graphical method based on Sv-plot2 can determine the decision on testing hypotheses over one or two population means. In sum, Sv-plots will be appealing visualization tools. Complete description of this methodology can be found in the article, Wijesuriya (2020) <doi:10.1080/03610918.2020.1851716>.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.0.2)
Imports: ggplot2
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, stats
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-04-06 15:55:07 UTC; uwijesuriy
Repository: CRAN
Date/Publication: 2021-04-07 08:40:02 UTC

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New package SNSchart with initial version 1.4.0
Package: SNSchart
Title: Sequential Normal Scores in Statistical Process Management
Version: 1.4.0
Authors@R: c(person("Victor", "Tercero", email = "victor.tercero@tec.mx", role=c("aut")), person("Luis", "Benavides", email = "luisbv@tec.mx", role = c("aut", "cre")), person("Jorge", "Merlo", email = "jorgemerlo24@gmail.com", role = c("ctb")))
Author: Victor Tercero [aut], Luis Benavides [aut, cre], Jorge Merlo [ctb]
Maintainer: Luis Benavides <luisbv@tec.mx>
Description: The methods discussed in this package are new non-parametric methods based on sequential normal scores 'SNS' (Conover et al (2017) <doi:10.1080/07474946.2017.1360091>), designed for sequences of observations, usually time series data, which may occur singly or in batches, and may be univariate or multivariate. These methods are designed to detect changes in the process, which may occur as changes in location (mean or median), changes in scale (standard deviation, or variance), or other changes of interest in the distribution of the observations, over the time observed. They usually apply to large data sets, so computations need to be simple enough to be done in a reasonable time on a computer, and easily updated as each new observation (or batch of observations) becomes available. Some examples and more detail in 'SNS' is presented in the work by Conover et al (2019) <arXiv:1901.04443>.
Depends: R (>= 2.10)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: parallel, stats, MASS
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-04-05 18:22:03 UTC; L03099908
Repository: CRAN
Date/Publication: 2021-04-07 08:40:15 UTC

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New package rnpn with initial version 1.2.1
Package: rnpn
Title: Interface to the National 'Phenology' Network 'API'
Description: Programmatic interface to the Web Service methods provided by the National 'Phenology' Network (<https://usanpn.org/>), which includes data on various life history events that occur at specific times.
Version: 1.2.1
License: MIT + file LICENSE
Authors@R: c( person("Lee", "Marsh", role = c("aut", "cre"), email = "lee@usanpn.org"), person("Scott", "Chamberlain", role = "aut"), person("Alyssa", "Rosemartin", role= "aut", email = "alyssa@usanpn.org"), person("Kevin", "Wong", role = "aut", email = "kevin@usanpn.org") )
Depends: R (>= 3.5.0)
Imports: httr (>= 1.1.0), jsonlite (>= 0.9.19), data.table (>= 1.9.6), sp (>= 1.1-0), tibble, curl, raster, rgdal, plyr, XML, magrittr
Suggests: ggplot2, testthat, covr, knitr, markdown, rmarkdown, RColorBrewer, vcr
VignetteBuilder: knitr
URL: https://docs.ropensci.org/rnpn/ (website) https://github.com/ropensci/rnpn/ (devel)
NeedsCompilation: no
Packaged: 2021-04-05 21:26:24 UTC; Lee
Author: Lee Marsh [aut, cre], Scott Chamberlain [aut], Alyssa Rosemartin [aut], Kevin Wong [aut]
Maintainer: Lee Marsh <lee@usanpn.org>
Repository: CRAN
Date/Publication: 2021-04-07 08:50:03 UTC

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New package Rediscover with initial version 0.1.0
Package: Rediscover
Title: Identify Mutually Exclusive Mutations
Version: 0.1.0
Authors@R: c(person("Juan A. Ferrer-Bonsoms", "Developer", role = c("aut", "cre"), email = "jafhernandez@tecnun.es"), person("Laura Jareno", "Developer", role = "aut"), person("Angel Rubio", "User", role = c("aut","ctb"), email = "arubio@tecnun.es"))
Description: An optimized method for identifying mutually exclusive genomic events. Its main contribution is a statistical analysis based on the Poisson-Binomial distribution that takes into account that some samples are more mutated than others. See [Canisius, Sander, John WM Martens, and Lodewyk FA Wessels. (2016) "A novel independence test for somatic alterations in cancer shows that biology drives mutual exclusivity but chance explains most co-occurrence." Genome biology 17.1 : 1-17. <doi:10.1186/s13059-016-1114-x>]. The mutations matrices are sparce matrices. The method developed takes advantage of the advantages of this type of matrix to save time and computing resources.
Depends: R (>= 4.0), Matrix, speedglm, PoissonBinomial
Imports: maftools, data.table, parallel, RColorBrewer, methods
Suggests: knitr, rmarkdown, RUnit, BiocStyle, BiocGenerics, dplyr, kableExtra, TCGAbiolinks, magick, stats
License: Artistic-2.0
LazyData: true
Encoding: UTF-8
biocViews: mutex
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-04-06 08:32:42 UTC; jferrerb
Author: Juan A. Ferrer-Bonsoms Developer [aut, cre], Laura Jareno Developer [aut], Angel Rubio User [aut, ctb]
Maintainer: Juan A. Ferrer-Bonsoms Developer <jafhernandez@tecnun.es>
Repository: CRAN
Date/Publication: 2021-04-07 09:00:02 UTC

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New package gghilbertstrings with initial version 0.3.3
Package: gghilbertstrings
Title: A Fast 'ggplot2'-Based Implementation of Hilbert Curves
Version: 0.3.3
Authors@R: person(given = "André", family = "Calero Valdez", role = c("aut", "cre"), email = "andrecalerovaldez@gmail.com", comment = c(ORCID = "0000-0002-6214-1461"))
Description: A set of functions that help to create plots based on Hilbert curves. Hilbert curves are used to map one dimensional data into the 2D plane. The package provides a function that generate a 2D coordinate from an integer position. As a specific use case the package provides a function that allows mapping a character column in a data frame into 2D space using 'ggplot2'. This allows visually comparing long lists of URLs, words, genes or other data that has a fixed order and position.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/Sumidu/gghilbertstrings
BugReports: https://github.com/Sumidu/gghilbertstrings/issues
SystemRequirements: C++11
Imports: ggplot2, dplyr, magrittr, tibble, lifecycle, Rcpp, rlang
Suggests: testthat, covr, spelling, profvis
Language: en-US
RdMacros: lifecycle
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2021-04-05 15:53:28 UTC; andrecalerovaldez
Author: André Calero Valdez [aut, cre] (<https://orcid.org/0000-0002-6214-1461>)
Maintainer: André Calero Valdez <andrecalerovaldez@gmail.com>
Repository: CRAN
Date/Publication: 2021-04-07 08:30:02 UTC

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New package cuperdec with initial version 1.0.0
Package: cuperdec
Title: Cumulative Percent Decay Curve Generator
Version: 1.0.0
Authors@R: person(given = "James A.", family = "Fellows Yates", role = c("aut", "cre"), email = "jfy133@gmail.com", comment = c(ORCID = "0000-0001-5585-6277"))
Description: Calculates and visualises cumulative percent 'decay' curves, which are typically calculated from metagenomic taxonomic profiles. These can be used to estimate the level of expected 'endogenous' taxa at different abundance levels retrieved from metagenomic samples, when comparing to samples of known sampling site or source.
License: MIT + file LICENSE
URL: https://github.com/jfy133/cuperdec
BugReports: https://github.com/jfy133/cuperdec/issues
Depends: R (>= 3.5.0)
Imports: dplyr, ggplot2, magrittr, readr, rlang, tidyr
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-GB
LazyData: true
NeedsCompilation: no
Packaged: 2021-04-06 15:42:28 UTC; jfellows
Author: James A. Fellows Yates [aut, cre] (<https://orcid.org/0000-0001-5585-6277>)
Maintainer: James A. Fellows Yates <jfy133@gmail.com>
Repository: CRAN
Date/Publication: 2021-04-07 08:40:06 UTC

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New package ClaimsProblems with initial version 0.1.0
Package: ClaimsProblems
Title: Analysis of Conflicting Claims
Version: 0.1.0
Authors@R: c( person("Iago","Núñez Lugilde",role=c("aut","cre"), email="iago.nunez.lugilde@uvigo.es",comment="SIDOR. Departamento de Estatística e Investigación Operativa. Universidade de Vigo. Spain"), person("Miguel Ángel","Mirás Calvo",role=c("aut"), comment="ECOBAS. Departamento de Matemáticas. Universidade de Vigo. Spain"), person("Carmen","Quinteiro Sandomingo",role=c("aut"), comment="Departamento de Matemáticas. Universidade de Vigo. Spain"), person("Estela","Sánchez Rodríguez",role=c("aut"),comment="CINBIO. Universidade de Vigo. Grupo SIDOR. Departamento de Estatística e Investigación Operativa. Universidade de Vigo. Spain") )
Maintainer: Iago Núñez Lugilde <iago.nunez.lugilde@uvigo.es>
Description: The analysis of conflicting claims arises when an amount has to be divided among a set of agents with claims that exceed what is available. A rule is a way of selecting a division among the claimants. This package computes the main rules introduced in the literature from the old times until nowadays. The inventory of rules covers the proportional and the adjusted proportional rules, the constrained equal awards and the constrained equal losses rules, the constrained egalitarian, the Piniles’ and the minimal overlap rules, the random arrival and the Talmud rules. Besides, the Dominguez and Thomson and the average of awards rules are also included. All of them can be found in the book of W. Thomson (2019), 'How to divide when there isn't enough. From Aristotle, the Talmud, and Maimonides to the axiomatics of resource allocation'. Cambridge University Press, ISBN: 9781316646441, with the exception of the average of awards rule (Mirás et al. (2020) <http://ecobas.webs.uvigo.es/wk/2020-02-corecenterforthebankruptcyproblem.pdf>). In addition, graphical diagrams allow the user to represent, among others, the set of awards, the paths of awards, and the schedules of awards of a rule, and some indexes. A good understanding of the similarities and the differences of the rules is useful for a better decision making. Therefore this package could be helpful to students, researchers and managers alike.
License: GPL-3
Encoding: UTF-8
Imports: graphics, rgl, geometry, grDevices, stats
NeedsCompilation: no
Packaged: 2021-04-05 15:15:11 UTC; iagol
Author: Iago Núñez Lugilde [aut, cre] (SIDOR. Departamento de Estatística e Investigación Operativa. Universidade de Vigo. Spain), Miguel Ángel Mirás Calvo [aut] (ECOBAS. Departamento de Matemáticas. Universidade de Vigo. Spain), Carmen Quinteiro Sandomingo [aut] (Departamento de Matemáticas. Universidade de Vigo. Spain), Estela Sánchez Rodríguez [aut] (CINBIO. Universidade de Vigo. Grupo SIDOR. Departamento de Estatística e Investigación Operativa. Universidade de Vigo. Spain)
Repository: CRAN
Date/Publication: 2021-04-07 08:30:06 UTC

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Package bikeshare14 updated to version 0.1.4 with previous version 0.1.2 dated 2019-01-03

Title: Bay Area Bike Share Trips in 2014
Description: Anonymised Bay Area bike share trip data for the year 2014. Also contains additional metadata on stations and weather.
Author: Arunkumar Srinivasan [aut, cre]
Maintainer: Arunkumar Srinivasan <asrini@pm.me>

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Package autostsm updated to version 1.2.2 with previous version 1.2.1 dated 2021-03-01

Title: Automatic Structural Time Series Models
Description: Automatic model selection for structural time series decomposition into trend, cycle, and seasonal components using the Kalman filter. Koopman, Siem Jan and Marius Ooms (2012) "Forecasting Economic Time Series Using Unobserved Components Time Series Models" <doi:10.1093/oxfordhb/9780195398649.013.0006>. Kim, Chang-Jin and Charles R. Nelson (1999) "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications" <doi:10.7551/mitpress/6444.001.0001><http://econ.korea.ac.kr/~cjkim/>.
Author: Alex Hubbard
Maintainer: Alex Hubbard <hubbard.alex@gmail.com>

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Package adespatial updated to version 0.3-14 with previous version 0.3-13 dated 2021-02-26

Title: Multivariate Multiscale Spatial Analysis
Description: Tools for the multiscale spatial analysis of multivariate data. Several methods are based on the use of a spatial weighting matrix and its eigenvector decomposition (Moran's Eigenvectors Maps, MEM). Several approaches are described in the review Dray et al (2012) <doi:10.1890/11-1183.1>.
Author: Stéphane Dray, David Bauman, Guillaume Blanchet, Daniel Borcard, Sylvie Clappe, Guillaume Guenard, Thibaut Jombart, Guillaume Larocque, Pierre Legendre, Naima Madi, Helene H Wagner
Maintainer: Stéphane Dray <stephane.dray@univ-lyon1.fr>

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Package RNewsflow updated to version 1.2.6 with previous version 1.2.5 dated 2020-11-02

Title: Tools for Comparing Text Messages Across Time and Media
Description: A collection of tools for measuring the similarity of text messages and tracing the flow of messages over time and across media.
Author: Kasper Welbers & Wouter van Atteveldt
Maintainer: Kasper Welbers <kasperwelbers@gmail.com>

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Package scPDSI (with last version 0.1.3) was removed from CRAN

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2018-11-18 0.1.3
2018-10-31 0.1.2

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Package compboost (with last version 0.1.0) was removed from CRAN

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2018-10-28 0.1.0

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Package PPtree (with last version 2.3.0) was removed from CRAN

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2014-05-08 2.3.0
2013-05-02 2.2.0
2012-08-17 2.0.6

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

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2014-10-07 0.1.1
2014-10-05 0.1

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Package cit (with last version 2.2) was removed from CRAN

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2017-12-15 2.2
2016-11-15 2.1
2016-03-07 2.0
2016-01-10 1.9
2016-01-09 1.8
2015-10-28 1.7
2015-10-25 1.5
2015-03-10 1.4
2014-12-10 1.3
2013-12-20 1.2
2011-12-10 1.1
2011-09-07 1.0

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Package blockcluster (with last version 4.4.3) was removed from CRAN

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2019-03-26 4.4.3
2018-10-05 4.3.2
2018-01-24 4.2.6
2017-02-27 4.2.3
2016-11-30 4.2.1
2016-11-29 4.2.0
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2015-01-23 3.0.2
2014-01-16 3.0.1

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Package mined (with last version 1.0-2) was removed from CRAN

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2019-07-18 1.0-2
2018-12-16 1.0-1

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Package icemelt (with last version 1.0) was removed from CRAN

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2019-07-15 1.0

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2019-04-25 1.0

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Package gconcord (with last version 0.4) was removed from CRAN

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2014-01-24 0.4
2014-01-24 0.41

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

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2017-11-13 1.0.3
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2015-11-26 0.1.4
2015-07-01 0.1.3

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

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Package BAREB (with last version 0.1.0) was removed from CRAN

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2020-03-06 0.1.0

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Package strucchangeRcpp (with last version 1.5-3-1.0.1) was removed from CRAN

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Package bRacatus (with last version 1.0.2) was removed from CRAN

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Package SortedEffects updated to version 1.3.0 with previous version 1.2.0 dated 2020-04-01

Title: Estimation and Inference Methods for Sorted Causal Effects and Classification Analysis
Description: Implements the estimation and inference methods for sorted causal effects and classification analysis as in Chernozhukov, Fernandez-Val and Luo (2018) <doi:10.3982/ECTA14415>.
Author: Shuowen Chen [aut, cre], Victor Chernozhukov [aut], Ivan Fernandez-Val [aut], Ye Luo [aut]
Maintainer: Shuowen Chen <swchen@bu.edu>

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Package biotools updated to version 4.1 with previous version 4.0 dated 2020-12-07

Title: Tools for Biometry and Applied Statistics in Agricultural Science
Description: Tools designed to perform and evaluate cluster analysis (including Tocher's algorithm), discriminant analysis and path analysis (standard and under collinearity), as well as some useful miscellaneous tools for dealing with sample size and optimum plot size calculations. A test for seed sample heterogeneity is now available. Mantel's permutation test can be found in this package. A new approach for calculating its power is implemented. biotools also contains tests for genetic covariance components. Heuristic approaches for performing non-parametric spatial predictions of generic response variables and spatial gene diversity are implemented.
Author: Anderson Rodrigo da Silva [aut, cre] (<https://orcid.org/0000-0003-2518-542X>)
Maintainer: Anderson Rodrigo da Silva <anderson.agro@hotmail.com>

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