Thu, 19 May 2022

Package DGEobj.utils updated to version 1.0.6 with previous version 1.0.5 dated 2022-05-10

Title: Differential Gene Expression (DGE) Analysis Utility Toolkit
Description: Provides a function toolkit to facilitate reproducible RNA-Seq Differential Gene Expression (DGE) analysis (Law (2015) <doi:10.12688/f1000research.9005.3>). The tools include both analysis work-flow and utility functions: mapping/unit conversion, count normalization, accounting for unknown covariates, and more. This is a complement/cohort to the 'DGEobj' package that provides a flexible container to manage and annotate Differential Gene Expression analysis results.
Author: John Thompson [aut], Connie Brett [aut, cre], Isaac Neuhaus [aut], Ryan Thompson [aut]
Maintainer: Connie Brett <connie@aggregate-genius.com>

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Package FRESA.CAD updated to version 3.4.2 with previous version 3.3.1 dated 2021-08-17

Title: Feature Selection Algorithms for Computer Aided Diagnosis
Description: Contains a set of utilities for building and testing statistical models (linear, logistic,ordinal or COX) for Computer Aided Diagnosis/Prognosis applications. Utilities include data adjustment, univariate analysis, model building, model-validation, longitudinal analysis, reporting and visualization.
Author: Jose Gerardo Tamez-Pena, Antonio Martinez-Torteya, Israel Alanis and Jorge Orozco
Maintainer: Jose Gerardo Tamez-Pena <jose.tamezpena@tec.mx>

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Package arulesCBA updated to version 1.2.2 with previous version 1.2.1 dated 2021-11-20

Title: Classification Based on Association Rules
Description: Provides the infrastructure for association rule-based classification including the algorithms CBA, CMAR, CPAR, C4.5, FOIL, PART, PRM, RCAR, and RIPPER to build associative classifiers.
Author: Michael Hahsler [aut, cre, cph], Ian Johnson [aut, cph], Tyler Giallanza [ctb]
Maintainer: Michael Hahsler <mhahsler@lyle.smu.edu>

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Package seqinr updated to version 4.2-16 with previous version 4.2-8 dated 2021-06-09

Title: Biological Sequences Retrieval and Analysis
Description: Exploratory data analysis and data visualization for biological sequence (DNA and protein) data. Seqinr includes utilities for sequence data management under the ACNUC system described in Gouy, M. et al. (1984) Nucleic Acids Res. 12:121-127 <doi:10.1093/nar/12.1Part1.121>.
Author: Delphine Charif [aut], Olivier Clerc [ctb], Carolin Frank [ctb], Jean R. Lobry [aut, cph], Anamaria Necşulea [ctb], Leonor Palmeira [ctb], Simon Penel [cre], Guy Perriere [ctb]
Maintainer: Simon Penel <simon.penel@univ-lyon1.fr>

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Package RcppCWB updated to version 0.5.3 with previous version 0.5.2 dated 2022-03-29

Title: 'Rcpp' Bindings for the 'Corpus Workbench' ('CWB')
Description: 'Rcpp' Bindings for the C code of the 'Corpus Workbench' ('CWB'), an indexing and query engine to efficiently analyze large corpora (<https://cwb.sourceforge.io>). 'RcppCWB' is licensed under the GNU GPL-3, in line with the GPL-3 license of the 'CWB' (<https://www.r-project.org/Licenses/GPL-3>). The 'CWB' relies on 'pcre' (BSD license, see <http://www.pcre.org/licence.txt>) and 'GLib' (LGPL license, see <https://www.gnu.org/licenses/lgpl-3.0.en.html>). See the file LICENSE.note for further information. The package includes modified code of the 'rcqp' package (GPL-2, see <https://cran.r-project.org/package=rcqp>). The original work of the authors of the 'rcqp' package is acknowledged with great respect, and they are listed as authors of this package. To achieve cross-platform portability (including Windows), using 'Rcpp' for wrapper code is the approach used by 'RcppCWB'.
Author: Andreas Blaette [aut, cre], Bernard Desgraupes [aut], Sylvain Loiseau [aut], Oliver Christ [ctb], Bruno Maximilian Schulze [ctb], Stefan Evert [ctb], Arne Fitschen [ctb], Jeroen Ooms [ctb], Marius Bertram [ctb], Tomas Kalibera [ctb]
Maintainer: Andreas Blaette <andreas.blaette@uni-due.de>

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Package MKLE updated to version 1.0.0 with previous version 0.05 dated 2009-01-26

Title: Maximum Kernel Likelihood Estimation
Description: Package for fast computation of the maximum kernel likelihood estimator (mkle).
Author: Thomas Jaki
Maintainer: Thomas Jaki <thomas.jaki@protonmail.com>

Diff between MKLE versions 0.05 dated 2009-01-26 and 1.0.0 dated 2022-05-19

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Package mod2rm updated to version 0.1.0 with previous version 0.0.2 dated 2022-05-02

Title: Moderation Analysis for Two-Instance Repeated Measures Designs
Description: Multiple moderation analysis for two-instance repeated measures designs, with up to three simultaneous moderators (dichotomous and/or continuous) with additive or multiplicative relationship. Includes analyses of simple slopes and conditional effects at (automatically determined or manually set) values of the moderator(s). Based on Montoya, A. K. (2018) "Moderation analysis in two-instance repeated measures designs: Probing methods and multiple moderator models" <doi:10.3758/s13428-018-1088-6> .
Author: Matthias Forstmann [aut, cre]
Maintainer: Matthias Forstmann <matthias.forstmann@uzh.ch>

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Package piggyback updated to version 0.1.3 with previous version 0.1.2 dated 2022-04-26

Title: Managing Larger Data on a GitHub Repository
Description: Because larger (> 50 MB) data files cannot easily be committed to git, a different approach is required to manage data associated with an analysis in a GitHub repository. This package provides a simple work-around by allowing larger (up to 2 GB) data files to piggyback on a repository as assets attached to individual GitHub releases. These files are not handled by git in any way, but instead are uploaded, downloaded, or edited directly by calls through the GitHub API. These data files can be versioned manually by creating different releases. This approach works equally well with public or private repositories. Data can be uploaded and downloaded programmatically from scripts. No authentication is required to download data from public repositories.
Author: Carl Boettiger [aut, cre, cph] , Mark Padgham [ctb] , Jeffrey O Hanson [ctb] , Kevin Kuo [ctb] , Tan Ho [ctb]
Maintainer: Carl Boettiger <cboettig@gmail.com>

Diff between piggyback versions 0.1.2 dated 2022-04-26 and 0.1.3 dated 2022-05-19

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Package nzilbb.labbcat updated to version 1.1-1 with previous version 1.1-0 dated 2022-04-12

Title: Accessing Data Stored in 'LaBB-CAT' Instances
Description: 'LaBB-CAT' is a web-based language corpus management system developed by the New Zealand Institute of Language, Brain and Behaviour (NZILBB) - see <https://labbcat.canterbury.ac.nz>. This package defines functions for accessing corpus data in a 'LaBB-CAT' instance. You must have at least version 20220401.1842 of 'LaBB-CAT' to use this package. For more information about 'LaBB-CAT', see Robert Fromont and Jennifer Hay (2008) <doi:10.3366/E1749503208000142> or Robert Fromont (2017) <doi:10.1016/j.csl.2017.01.004>.
Author: Robert Fromont [aut, cre]
Maintainer: Robert Fromont <robert.fromont@canterbury.ac.nz>

Diff between nzilbb.labbcat versions 1.1-0 dated 2022-04-12 and 1.1-1 dated 2022-05-19

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New package EMAS with initial version 0.1.0
Package: EMAS
Title: Epigenome-Wide Mediation Analysis Study
Version: 0.1.0
Date: 2022-05-17
Author: Xiuquan Nie [aut, cph, cre], Mengyi Wang [ctb, rev], Weihong Chen [fnd]
Maintainer: Xiuquan Nie <niexiuquan1995@foxmail.com>
Depends: R (>= 3.5.0)
Imports: mediation, parallel, minfi, qqman
Suggests: IlluminaHumanMethylationEPICanno.ilm10b4.hg19, IlluminaHumanMethylation450kanno.ilmn12.hg19
Description: DNA methylation is essential for human, and environment can change the DNA methylation and affect body status. Epigenome-Wide Mediation Analysis Study (EMAS) can find potential mediator CpG sites between exposure (x) and outcome (y) in epigenome-wide. For more information on the methods we used, please see the following references: Tingley, D. (2014) <doi:10.18637/jss.v059.i05>, Turner, S. D. (2018) <doi:10.21105/joss.00731>.
License: GPL-3
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2022-05-19 08:07:51 UTC; niexi
Repository: CRAN
Date/Publication: 2022-05-19 17:10:02 UTC

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New package ivaBSS with initial version 1.0.0
Package: ivaBSS
Title: Tools for Independent Vector Analysis
Version: 1.0.0
Date: 2022-05-03
Imports: stats, graphics, BSSprep
Suggests: LaplacesDemon
Encoding: UTF-8
Maintainer: Mika Sipilae <mika.e.sipila@student.jyu.fi>
Description: Independent vector analysis (IVA) is a blind source separation (BSS) model where several datasets are jointly unmixed. This package provides several methods for the unmixing together with some performance measures. For details, see Anderson et al. (2011) <doi:10.1109/TSP.2011.2181836> and Lee et al. (2007) <doi:10.1016/j.sigpro.2007.01.010>.
License: GPL (>= 3)
NeedsCompilation: no
Packaged: 2022-05-19 08:16:26 UTC; developer
Author: Mika Sipilae [aut, cre], Klaus Nordhausen [aut] , Sara Taskinen [aut]
Repository: CRAN
Date/Publication: 2022-05-19 17:00:02 UTC

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Package fossilbrush updated to version 1.0.1 with previous version 1.0 dated 2022-05-09

Title: Automated Cleaning of Fossil Occurrence Data
Description: Functions to automate the detection and resolution of taxonomic and stratigraphic errors in fossil occurrence datasets. Functions were developed using data from the Paleobiology Database.
Author: Joe Flannery-Sutherland [aut, cre] , Nussaïbah Raja-Schoob [aut, ctb], Ádam Kocsis [aut, ctb], Wolfgang Kiessling [aut]
Maintainer: Joe Flannery-Sutherland <jf15558@bristol.ac.uk>

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Package supcluster updated to version 1.0.1 with previous version 1.0 dated 2015-05-18

Title: Supervised Cluster Analysis
Description: Clusters features under the assumption that each cluster has a random effect and there is an outcome variable that is related to the random effects by a linear regression. In this way the cluster analysis is ``supervised'' by the outcome variable. An alternate specification is that features in each cluster have the same compound symmetric normal distribution, and the conditional distribution of the outcome given the features has the same coefficient for each feature in a cluster.
Author: David A. Schoenfeld, Jesse Hsu
Maintainer: David A. Schoenfeld <dschoenfeld@mgh.harvard.edu>

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Package matsindf updated to version 0.3.11 with previous version 0.3.10 dated 2021-12-17

Title: Matrices in Data Frames
Description: Provides functions to collapse a tidy data frame into matrices in a data frame and expand a data frame of matrices into a tidy data frame.
Author: Matthew Heun [aut, cre]
Maintainer: Matthew Heun <matthew.heun@me.com>

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Package cape updated to version 3.1.1 with previous version 3.1.0 dated 2021-02-10

Title: Combined Analysis of Pleiotropy and Epistasis for Diversity Outbred Mice
Description: Combined Analysis of Pleiotropy and Epistasis infers predictive networks between genetic variants and phenotypes. It can be used with standard two-parent populations as well as multi-parent populations, such as the Diversity Outbred (DO) mice, Collaborative Cross (CC) mice, or the multi-parent advanced generation intercross (MAGIC) population of Arabidopsis thaliana. It uses complementary information of pleiotropic gene variants across different phenotypes to resolve models of epistatic interactions between alleles. To do this, cape reparametrizes main effect and interaction coefficients from pairwise variant regressions into directed influence parameters. These parameters describe how alleles influence each other, in terms of suppression and enhancement, as well as how gene variants influence phenotypes. All of the final interactions are reported as directed interactions between pairs of parental alleles. For detailed descriptions of the methods used in this package please see the following references. Carter, G. W., Hays, M., Sherman, A. & Galitski, T. (2012) <doi:10.1371/journal.pgen.1003010>. Tyler, A. L., Lu, W., Hendrick, J. J., Philip, V. M. & Carter, G. W. (2013) <doi:10.1371/journal.pcbi.1003270>.
Author: Anna Tyler [aut, cre], Jake Emerson [aut], Baha El Kassaby [aut], Ann Wells [aut], Georgi Kolishovski [aut], Vivek Philip [aut], Gregory Carter [aut]
Maintainer: Anna Tyler <anna.tyler@jax.org>

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New package STARTS with initial version 1.3-8
Package: STARTS
Title: Functions for the STARTS Model
Version: 1.3-8
Date: 2022-05-19 09:47:44
Author: Alexander Robitzsch [aut,cre] , Oliver Luedtke [aut]
Maintainer: Alexander Robitzsch <robitzsch@ipn.uni-kiel.de>
Description: Contains functions for estimating the STARTS model of Kenny and Zautra (1995, 2001) <DOI:10.1037/0022-006X.63.1.52>, <DOI:10.1037/10409-008>. Penalized maximum likelihood estimation and Markov Chain Monte Carlo estimation are also provided, see Luedtke, Robitzsch and Wagner (2018) <DOI:10.1037/met0000155>.
Depends: R (>= 3.1)
Imports: CDM (>= 7.1-19), graphics, LAM (>= 0.3-27), sirt (>= 2.3), Rcpp, stats, utils
Suggests: lavaan
LinkingTo: Rcpp, RcppArmadillo
URL: https://github.com/alexanderrobitzsch/STARTS, https://sites.google.com/site/alexanderrobitzsch2/software
License: GPL (>= 2)
NeedsCompilation: yes
Packaged: 2022-05-19 07:48:19 UTC; sunpn563
Repository: CRAN
Date/Publication: 2022-05-19 11:20:02 UTC

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Package r3PG updated to version 0.1.4 with previous version 0.1.3 dated 2021-02-19

Title: Simulating Forest Growth using the 3-PG Model
Description: Provides a flexible and easy-to-use interface for the Physiological Processes Predicting Growth (3-PG) model written in Fortran. The r3PG serves as a flexible and easy-to-use interface for the 3-PGpjs (monospecific, evenaged and evergreen forests) described in Landsberg & Waring (1997) <doi:10.1016/S0378-1127(97)00026-1> and the 3-PGmix (deciduous, uneven-aged or mixed-species forests) described in Forrester & Tang (2016) <doi:10.1016/j.ecolmodel.2015.07.010>.
Author: Volodymyr Trotsiuk [aut, cre] , Florian Hartig [aut] , David Forrester [aut], Ramiro Silveyra Gonzalez [aut]
Maintainer: Volodymyr Trotsiuk <volodymyr.trotsiuk@wsl.ch>

Diff between r3PG versions 0.1.3 dated 2021-02-19 and 0.1.4 dated 2022-05-19

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Package nloptr updated to version 2.0.2 with previous version 2.0.1 dated 2022-05-03

Title: R Interface to NLopt
Description: Solve optimization problems using an R interface to NLopt. NLopt is a free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines available online as well as original implementations of various other algorithms. See <https://nlopt.readthedocs.io/en/latest/NLopt_Algorithms/> for more information on the available algorithms. Building from included sources requires 'CMake'. On Linux and 'macOS', if a suitable system build of NLopt (2.7.0 or later) is found, it is used; otherwise, it is built from included sources via 'CMake'. On Windows, NLopt is obtained through 'rwinlib' for 'R <= 4.1.x' or grabbed from the 'Rtools42 toolchain' for 'R >= 4.2.0'.
Author: Jelmer Ypma [aut], Steven G. Johnson [aut] , Hans W. Borchers [ctb], Dirk Eddelbuettel [ctb], Brian Ripley [ctb] , Kurt Hornik [ctb] , Julien Chiquet [ctb], Avraham Adler [ctb] , Xiongtao Dai [ctb], Aymeric Stamm [ctb, cre] , Jeroen Ooms [ctb]
Maintainer: Aymeric Stamm <aymeric.stamm@math.cnrs.fr>

Diff between nloptr versions 2.0.1 dated 2022-05-03 and 2.0.2 dated 2022-05-19

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Package x12 updated to version 1.10.3 with previous version 1.10.2 dated 2022-02-02

Title: Interface to 'X12-ARIMA'/'X13-ARIMA-SEATS' and Structure for Batch Processing of Seasonal Adjustment
Description: The 'X13-ARIMA-SEATS' <https://www.census.gov/data/software/x13as.html> methodology and software is a widely used software and developed by the US Census Bureau. It can be accessed from 'R' with this package and 'X13-ARIMA-SEATS' binaries are provided by the 'R' package 'x13binary'.
Author: Alexander Kowarik <alexander.kowarik@statistik.gv.at>, Angelika Meraner
Maintainer: Alexander Kowarik <alexander.kowarik@statistik.gv.at>

Diff between x12 versions 1.10.2 dated 2022-02-02 and 1.10.3 dated 2022-05-19

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New package ModEstM with initial version 0.0.1
Package: ModEstM
Title: Mode Estimation, Even in the Multimodal Case
Version: 0.0.1
Description: Function ModEstM() is the only one of this package, it estimates the modes of an empirical univariate distribution. It relies on the stats::density() function, even for input control. Due to very good performance of the density estimation, computation time is not an issue. The multiple modes are handled using dplyr::group_by(). For conditions and rates of convergences, see Eddy (1980) <doi:10.1214/aos/1176345080>.
Depends: R (>= 4.1)
License: GPL-3
Encoding: UTF-8
Imports: dplyr, rlang, stats
NeedsCompilation: no
Packaged: 2022-05-19 07:10:02 UTC; Jerome
Author: Jerome Collet [aut, cre]
Maintainer: Jerome Collet <jeromepcollet@gmail.com>
Repository: CRAN
Date/Publication: 2022-05-19 08:10:02 UTC

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New package SoundShape with initial version 1.2.1
Package: SoundShape
Title: Sound Waves Onto Morphometric Data
Version: 1.2.1
Date: 2022-05-16
Description: Implement a promising, and yet little explored protocol for bioacoustical analysis, the eigensound method by MacLeod, Krieger and Jones (2013) <doi:10.4404/hystrix-24.1-6299>. Eigensound is a multidisciplinary method focused on the direct comparison between stereotyped sounds from different species. 'SoundShape', in turn, provide the tools required for anyone to go from sound waves to Principal Components Analysis, using tools extracted from traditional bioacoustics (i.e. 'tuneR' and 'seewave' packages), geometric morphometrics (i.e. 'geomorph' package) and multivariate analysis (e.g. 'stats' package). For more information, please see Rocha and Romano (2021) and check 'SoundShape' repository on GitHub for news and updates <https://github.com/p-rocha/SoundShape>.
Depends: R (>= 3.3.1)
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/p-rocha/SoundShape
BugReports: https://github.com/p-rocha/SoundShape/issues
Imports: abind, geomorph (>= 3.0.2), graphics, grDevices, plot3D, reshape2, seewave, stats, tuneR, utils
Suggests: vegan, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2022-05-16 23:49:44 UTC; Pedro
Author: Pedro Rocha [aut, cre]
Maintainer: Pedro Rocha <p.rocha1990@gmail.com>
Repository: CRAN
Date/Publication: 2022-05-19 07:50:17 UTC

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Package pomdp updated to version 1.0.3 with previous version 1.0.2 dated 2022-05-17

Title: Infrastructure for Partially Observable Markov Decision Processes (POMDP)
Description: Provides the infrastructure to define and analyze the solutions of Partially Observable Markov Decision Process (POMDP) models. Interfaces for various exact and approximate solution algorithms are available including value iteration, point-based value iteration and SARSOP. Smallwood and Sondik (1973) <doi:10.1287/opre.21.5.1071>.
Author: Michael Hahsler [aut, cph, cre], Hossein Kamalzadeh [ctb]
Maintainer: Michael Hahsler <mhahsler@lyle.smu.edu>

Diff between pomdp versions 1.0.2 dated 2022-05-17 and 1.0.3 dated 2022-05-19

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Package mpathsenser updated to version 1.0.1 with previous version 1.0.0 dated 2022-05-17

Title: Process and Analyse Data from m-Path Sense
Description: Overcomes one of the major challenges in mobile (passive) sensing, namely being able to pre-process the raw data that comes from a mobile sensing app, specifically "m-Path Sense" <https://m-path.io>. The main task of 'mpathsenser' is therefore to read "m-Path Sense" JSON files into a database and provide several convenience functions to aid in data processing.
Author: Koen Niemeijer [aut, cre]
Maintainer: Koen Niemeijer <koen.niemeijer@kuleuven.be>

Diff between mpathsenser versions 1.0.0 dated 2022-05-17 and 1.0.1 dated 2022-05-19

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Package mlt.docreg updated to version 1.1-4 with previous version 1.1-3 dated 2022-01-13

Title: Most Likely Transformations: Documentation and Regression Tests
Description: Additional documentation, a package vignette and regression tests for package mlt.
Author: Torsten Hothorn [aut, cre]
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

Diff between mlt.docreg versions 1.1-3 dated 2022-01-13 and 1.1-4 dated 2022-05-19

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New package FIESTA with initial version 3.4.0
Package: FIESTA
Title: Forest Inventory Estimation and Analysis
Version: 3.4.0
Date: 2022-05-13
Description: A research estimation tool for analysts that work with sample-based inventory data from the U.S. Department of Agriculture, Forest Service, Forest Inventory and Analysis (FIA) Program.
Depends: R (>= 4.0)
Imports: data.table, DBI, FIESTAutils (>= 1.1.1), grDevices, graphics, methods, rgdal, RSQLite, sf, sqldf, utils
Suggests: knitr, raster, rmarkdown
VignetteBuilder: knitr
License: GPL-3
Copyright: See file COPYRIGHTS for details.
LazyData: true
SystemRequirements: C++11
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2022-05-18 23:26:08 UTC; graysonwhite
Author: Tracey Frescino [aut], Gretchen Moisen [aut], Paul Patterson [aut], Chris Toney [aut], Grayson White [aut, cre]
Maintainer: Grayson White <graysonwhite13@gmail.com>
Repository: CRAN
Date/Publication: 2022-05-19 07:50:20 UTC

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Package epm updated to version 1.0.1 with previous version 1.0.0 dated 2022-05-17

Title: EcoPhyloMapper
Description: Facilitates the aggregation of species' geographic ranges from vector or raster spatial data, and that enables the calculation of various morphological and phylogenetic community metrics across geography.
Author: Pascal Title [aut, cre] , Donald Swiderski [aut], Miriam Zelditch [aut]
Maintainer: Pascal Title <pascal.title@stonybrook.edu>

Diff between epm versions 1.0.0 dated 2022-05-17 and 1.0.1 dated 2022-05-19

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Package DQAstats updated to version 0.3.0 with previous version 0.2.6 dated 2022-03-02

Title: Core Functions for Data Quality Assessment
Description: Perform data quality assessment ('DQA') of electronic health records ('EHR'). Publication: Kapsner et al. (2021) <doi:10.1055/s-0041-1733847>.
Author: Lorenz A. Kapsner [cre, aut] , Jonathan M. Mang [aut] , MIRACUM - Medical Informatics in Research and Care in University Medicine [fnd], Universitaetsklinikum Erlangen [cph]
Maintainer: Lorenz A. Kapsner <lorenz.kapsner@uk-erlangen.de>

Diff between DQAstats versions 0.2.6 dated 2022-03-02 and 0.3.0 dated 2022-05-19

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New package chromatographR with initial version 0.4.1
Package: chromatographR
Title: Import and Analyze HPLC-DAD/UV Data
Version: 0.4.1
Maintainer: Ethan Bass <ethanbass@gmail.com>
Description: Tools for high-throughput analysis of HPLC-DAD/UV chromatograms (or similar data). Includes functions for preprocessing, alignment, peak-finding and fitting, peak-table construction, data-visualization, etc. Preprocessing and peak-table construction follow the rough formula laid out in alsace (Wehrens, R., Bloemberg, T.G., and Eilers P.H.C., 2015. <doi:10.1093/bioinformatics/btv299>. Alignment of chromatograms is available using parametric time warping (ptw) (Wehrens, R., Bloemberg, T.G., and Eilers P.H.C. 2015. <doi:10.1093/bioinformatics/btv299>) or variable penalty dynamic time warping (VPdtw) (Clifford, D., & Stone, G. 2012. <doi:10.18637/jss.v047.i08>). Peak-finding uses the algorithm by Tom O'Haver <http://terpconnect.umd.edu/~toh/spectrum/PeakFindingandMeasurement.htm>. Peaks are then fitted to a gaussian or exponential-gaussian hybrid peak shape using non-linear least squares (Lan, K. & Jorgenson, J. W. 2001. <doi:10.1016/S0021-9673(01)00594-5>). See the vignette for more details and suggested workflow.
License: GPL (>= 2)
URL: https://ethanbass.github.io/chromatographR/
BugReports: https://github.com/ethanbass/chromatographR/issues
Depends: R (>= 3.5.0)
Imports: chromConverter, dynamicTreeCut, fastcluster, graphics, grDevices, lattice, methods, minpack.lm, parallel, ptw, pvclust, scales, smoother, stats, utils
Suggests: knitr, rmarkdown, spelling, testthat (>= 3.0.0), VPdtw
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
LazyData: true
LazyDataCompression: xz
Additional_repositories: https://ethanbass.github.io/drat/
NeedsCompilation: no
Packaged: 2022-05-18 21:26:28 UTC; ethanbass
Author: Ethan Bass [aut, cre]
Repository: CRAN
Date/Publication: 2022-05-19 07:40:02 UTC

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New package BranchGLM with initial version 1.0.0
Package: BranchGLM
Title: Glm Fitting and Variable Selection using 'RcppArmadillo'
Version: 1.0.0
Date: 2022-5-16
Maintainer: Jacob Seedorff <jwseedorff@uiowa.edu>
URL: https://github.com/JacobSeedorff21/BranchGLM
BugReports: https://github.com/JacobSeedorff21/BranchGLM/issues
Description: Fits glms using 'RcppArmadillo', can use Fisher's scoring, BFGS, or L-BFGS. Can also make use of parallel computation to speed up fitting process via 'OpenMP'. Also can perform best subset selection with an efficient branch and bound algorithm that allows best subset selection for more variables.
License: Apache License (>= 2)
Depends: R (>= 3.3.0)
Imports: Rcpp (>= 1.0.7), methods
LinkingTo: Rcpp, RcppArmadillo
Encoding: UTF-8
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2022-05-19 04:22:06 UTC; Jacob
Author: Jacob Seedorff [aut, cre]
Repository: CRAN
Date/Publication: 2022-05-19 08:00:02 UTC

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Package abc updated to version 2.2.1 with previous version 2.1 dated 2015-05-05

Title: Tools for Approximate Bayesian Computation (ABC)
Description: Implements several ABC algorithms for performing parameter estimation, model selection, and goodness-of-fit. Cross-validation tools are also available for measuring the accuracy of ABC estimates, and to calculate the misclassification probabilities of different models.
Author: Csillery Katalin [aut], Lemaire Louisiane [aut], Francois Olivier [aut], Blum Michael [aut, cre]
Maintainer: Blum Michael <michael.blum.temp@gmail.com>

Diff between abc versions 2.1 dated 2015-05-05 and 2.2.1 dated 2022-05-19

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New package sits with initial version 1.0.0
Package: sits
Version: 1.0.0
Title: Satellite Image Time Series Analysis for Earth Observation Data Cubes
Maintainer: Gilberto Camara <gilberto.camara.inpe@gmail.com>
Description: An end-to-end toolkit for land use and land cover classification using big Earth observation data, based on machine learning methods applied to satellite image data cubes, as described in Simoes et al (2021) <doi:10.3390/rs13132428>. Builds regular data cubes from collections in AWS, Microsoft Planetary Computer, Brazil Data Cube, and Digital Earth Africa using the STAC protocol <https://stacspec.org/> and the 'gdalcubes' R package <doi:10.3390/data4030092>. Supports visualization methods for images and time series and smoothing filters for dealing with noisy time series. Includes functions for quality assessment of training samples using self-organized maps as presented by Santos et al (2021) <doi:10.1016/j.isprsjprs.2021.04.014>. Provides machine learning methods including support vector machines, random forests, extreme gradient boosting, multi-layer perceptrons, temporal convolutional neural networks <doi:10.3390/rs11050523>, residual networks <arxiv:1809.04356>, and temporal attention encoders <arXiv:2007.00586>. Performs efficient classification of big Earth observation data cubes and includes functions for post-classification smoothing based on Bayesian inference, and methods for uncertainty assessment. Enables best practices for estimating area and assessing accuracy of land change as recommended by Olofsson et al(2014) <doi:10.1016/j.rse.2014.02.015>. Minimum recommended requirements: 16 GB RAM and 4 CPU dual-core.
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.0.0)
URL: https://github.com/e-sensing/sits/, https://e-sensing.github.io/sitsbook/
BugReports: https://github.com/e-sensing/sits/issues
License: GPL-2
ByteCompile: true
LazyData: true
Imports: magrittr, yaml, data.table (>= 1.13), dplyr (>= 1.0.0), gdalUtilities, grDevices, ggplot2, graphics, lubridate, parallel (>= 4.0.5), purrr (>= 0.3.0), Rcpp, rstac (>= 0.9.1-5), sf (>= 1.0), slider (>= 0.2.0), stats, terra (>= 1.5-17), tibble (>= 3.1), tidyr (>= 1.2.0), torch (>= 0.7.0), utils
Suggests: caret, dendextend, dtwclust, dtwSat (>= 0.2.7), digest, e1071, FNN, gdalcubes (>= 0.6.0), geojsonsf, httr, jsonlite, kohonen(>= 3.0.11), leafem (>= 0.2.0), leaflet (>= 2.1.1), luz (>= 0.2.0), methods, mgcv, openxlsx, randomForest, RcppArmadillo (>= 0.11), scales, stars (>= 0.5), testthat (>= 3.1.3), torchopt(>= 0.1.1), xgboost, zoo
Config/testthat/parallel: false
Config/testthat/start-first: cube, raster, ml
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Packaged: 2022-05-19 00:09:17 UTC; gilbertocamara
Author: Rolf Simoes [aut], Gilberto Camara [aut, cre], Felipe Souza [aut], Lorena Santos [aut], Pedro Andrade [aut], Karine Ferreira [aut], Alber Sanchez [aut], Gilberto Queiroz [aut]
Repository: CRAN
Date/Publication: 2022-05-19 07:00:02 UTC

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Package RadOnc updated to version 1.1.6 with previous version 1.1.5 dated 2019-03-20

Title: Analytical Tools for Radiation Oncology
Description: Designed for the import, analysis, and visualization of dosimetric and volumetric data in Radiation Oncology, the tools herein enable import of dose-volume histogram information from multiple treatment planning system platforms and 3D structural representations and dosimetric information from 'DICOM-RT' files. These tools also enable subsequent visualization and statistical analysis of these data.
Author: Reid F. Thompson <reid.thompson@gmail.com>
Maintainer: Reid F. Thompson <reid.thompson@gmail.com>

Diff between RadOnc versions 1.1.5 dated 2019-03-20 and 1.1.6 dated 2022-05-19

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Package QBMS updated to version 0.8.0 with previous version 0.7.0 dated 2022-03-02

Title: Query the Breeding Management System(s)
Description: Query the Breeding Management System(s) like BMS <https://bmspro.io>, BreeBase <https://breedbase.org>, and GIGWA <https://southgreen.fr/content/gigwa> (using 'BrAPI' <https://brapi.org> calls) to help breeders as targeted end-users retrieve phenotypic and genotypic data directly into their analyzing pipelines.
Author: Khaled Al-Shamaa [aut, cre], Mariano Omar Crimi [ctb], Zakaria Kehel [ctb], ICARDA [cph]
Maintainer: Khaled Al-Shamaa <k.el-shamaa@cgiar.org>

Diff between QBMS versions 0.7.0 dated 2022-03-02 and 0.8.0 dated 2022-05-19

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Package powerpkg updated to version 1.6 with previous version 1.5 dated 2012-10-11

Title: Power Analyses for the Affected Sib Pair and the TDT Design
Description: There are two main functions: (1) To estimate the power of testing for linkage using an affected sib pair design, as a function of the recurrence risk ratios. We will use analytical power formulae as implemented in R. These are based on a Mathematica notebook created by Martin Farrall. (2) To examine how the power of the transmission disequilibrium test (TDT) depends on the disease allele frequency, the marker allele frequency, the strength of the linkage disequilibrium, and the magnitude of the genetic effect. We will use an R program that implements the power formulae of Abel and Muller-Myhsok (1998). These formulae allow one to quickly compute power of the TDT approach under a variety of different conditions. This R program was modeled on Martin Farrall's Mathematica notebook.
Author: Daniel E. Weeks
Maintainer: Daniel E. Weeks <weeks@pitt.edu>

Diff between powerpkg versions 1.5 dated 2012-10-11 and 1.6 dated 2022-05-19

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Package inti updated to version 0.5.6 with previous version 0.5.5 dated 2022-04-01

Title: Tools and Statistical Procedures in Plant Science
Description: The 'inti' package is part of the 'inkaverse' project for developing different procedures and tools used in plant science and experimental designs. The mean aim of the package is to support researchers during the planning of experiments and data collection (tarpuy()), data analysis and graphics (yupana()) , and technical writing. Learn more about the 'inkaverse' project at <https://inkaverse.com/>.
Author: Flavio Lozano-Isla [aut, cre] , QuipoLab [ctb], Inkaverse [cph]
Maintainer: Flavio Lozano-Isla <flavjack@gmail.com>

Diff between inti versions 0.5.5 dated 2022-04-01 and 0.5.6 dated 2022-05-19

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Package GEInter updated to version 0.3.2 with previous version 0.3.1 dated 2021-07-10

Title: Robust Gene-Environment Interaction Analysis
Description: Description: For the risk, progression, and response to treatment of many complex diseases, it has been increasingly recognized that gene-environment interactions play important roles beyond the main genetic and environmental effects. In practical interaction analyses, outliers in response variables and covariates are not uncommon. In addition, missingness in environmental factors is routinely encountered in epidemiological studies. The developed package consists of five robust approaches to address the outliers problems, among which two approaches can also accommodate missingness in environmental factors. Both continuous and right censored responses are considered. The proposed approaches are based on penalization and sparse boosting techniques for identifying important interactions, which are realized using efficient algorithms. Beyond the gene-environment analysis, the developed package can also be adopted to conduct analysis on interactions between other types of low-dimensional and high-dimensional data. (Mengyun Wu et al (2017), <doi:10.1080/00949655.2018.1523411>; Mengyun Wu et al (2017), <doi:10.1002/gepi.22055>; Yaqing Xu et al (2018), <doi:10.1080/00949655.2018.1523411>; Yaqing Xu et al (2019), <doi:10.1016/j.ygeno.2018.07.006>; Mengyun Wu et al (2021), <doi:10.1093/bioinformatics/btab318>).
Author: Mengyun Wu [aut], Xing Qin [aut, cre], Shuangge Ma [aut]
Maintainer: Xing Qin <qin.xing@163.sufe.edu.cn>

Diff between GEInter versions 0.3.1 dated 2021-07-10 and 0.3.2 dated 2022-05-19

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Package FMStable updated to version 0.1-3 with previous version 0.1-2 dated 2012-09-06

Title: Finite Moment Stable Distributions
Description: Some basic procedures for dealing with log maximally skew stable distributions, which are also called finite moment log stable distributions.
Author: Geoff Robinson
Maintainer: Daniel Wilson <hmp.R.package@gmail.com>

Diff between FMStable versions 0.1-2 dated 2012-09-06 and 0.1-3 dated 2022-05-19

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New package DepCens with initial version 0.2.1
Package: DepCens
Title: Dependent Censoring Regression Models
Version: 0.2.1
Description: Dependent censoring regression models for survival multivariate data. These models are based on extensions of the frailty models, capable to accommodating the dependence between failure and censoring times, with Weibull and piecewise exponential marginal distributions. Theoretical details regarding the models implemented in the package can be found in Schneider et al. (2019) <doi:10.1002/bimj.201800391>.
License: GPL (>= 2)
URL: https://github.com/GabrielGrandemagne/DepCens
BugReports: https://github.com/GabrielGrandemagne/DepCens/issues
Depends: R (>= 2.10)
Imports: dlm, Formula, rootSolve, survival, matrixStats, stats
Encoding: UTF-8
LazyData: true
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2022-05-18 18:49:28 UTC; Gabriel-PC
Author: Silvana Schneider [aut, cre] , Gabriel Grandemagne dos Santos [ctb]
Maintainer: Silvana Schneider <silvana.schneider@ufrgs.br>
Repository: CRAN
Date/Publication: 2022-05-19 06:50:23 UTC

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New package cellpypes with initial version 0.1.3
Package: cellpypes
Title: Cell Type Pipes for Single-Cell RNA Sequencing Data
Version: 0.1.3
Description: Annotate single-cell RNA sequencing data manually based on marker gene thresholds. Find cell type rules (gene+threshold) through exploration, use the popular piping operator '%>%' to reconstruct complex cell type hierarchies. 'cellpypes' models technical noise to find positive and negative cells for a given expression threshold and returns cell type labels or pseudobulks. Cite this package as Frauhammer (2022) <doi:10.5281/zenodo.6555728> and visit <https://github.com/FelixTheStudent/cellpypes> for tutorials and newest features.
URL: https://github.com/FelixTheStudent/cellpypes
BugReports: https://github.com/FelixTheStudent/cellpypes/issues
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, Seurat, DESeq2, RcppAnnoy, tibble, SeuratObject
Imports: scUtils, ggplot2, Matrix, rlang, viridis, cowplot, dplyr, scales, methods, scattermore
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2022-05-18 20:33:14 UTC; felix
Author: Felix Frauhammer [aut, cre]
Maintainer: Felix Frauhammer <felixfrauhammer@gmail.com>
Repository: CRAN
Date/Publication: 2022-05-19 07:00:08 UTC

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Package cvcqv (with last version 1.0.0) was removed from CRAN

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

2019-08-06 1.0.0

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