Fri, 15 Nov 2019

Package iq updated to version 1.1 with previous version 1.0 dated 2019-11-15

Title: Protein Quantification in Mass Spectrometry-Based Proteomics
Description: An implementation of the maximal peptide ratio extraction module of the MaxLFQ algorithm by Cox et al. (2014) <doi:10.1074/mcp.M113.031591> in a complete pipeline for processing proteomics data in data-independent acquisition mode. It offers additional options for protein quantification using the N most intense fragment ions, using all fragment ions, and a wrapper for the median polish algorithm by Tukey (1977, ISBN:0201076160).
Author: Thang Pham [aut, cre, cph, ctb] (<https://orcid.org/0000-0003-0333-2492>), Alex Henneman [ctb] (<https://orcid.org/0000-0002-3746-4410>)
Maintainer: Thang Pham <t.pham@amsterdamumc.nl>

Diff between iq versions 1.0 dated 2019-11-15 and 1.1 dated 2019-11-15

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Package live updated to version 1.5.11 with previous version 1.5.10 dated 2019-02-28

Title: Local Interpretable (Model-Agnostic) Visual Explanations
Description: Interpretability of complex machine learning models is a growing concern. This package helps to understand key factors that drive the decision made by complicated predictive model (so called black box model). This is achieved through local approximations that are either based on additive regression like model or CART like model that allows for higher interactions. The methodology is based on Tulio Ribeiro, Singh, Guestrin (2016) <doi:10.1145/2939672.2939778>. More details can be found in Staniak, Biecek (2018) <doi:10.32614/RJ-2018-072>.
Author: Mateusz Staniak [cre, aut], Przemysław Biecek [aut]
Maintainer: Mateusz Staniak <mateusz.staniak@math.uni.wroc.pl>

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Package HEMDAG updated to version 2.6.0 with previous version 2.5.9 dated 2019-10-08

Title: Hierarchical Ensemble Methods for Directed Acyclic Graphs
Description: An implementation of several Hierarchical Ensemble Methods (HEMs) for Directed Acyclic Graphs (DAGs). 'HEMDAG' package: 1) reconciles flat predictions with the topology of the ontology; 2) can enhance the predictions of virtually any flat learning methods by taking into account the hierarchical relationships between ontology classes; 3) provides biologically meaningful predictions that always obey the true-path-rule, the biological and logical rule that governs the internal coherence of biomedical ontologies; 4) is specifically designed for exploiting the hierarchical relationships of DAG-structured taxonomies, such as the Human Phenotype Ontology (HPO) or the Gene Ontology (GO), but can be safely applied to tree-structured taxonomies as well (as FunCat), since trees are DAGs; 5) scales nicely both in terms of the complexity of the taxonomy and in the cardinality of the examples; 6) provides several utility functions to process and analyze graphs; 7) provides several performance metrics to evaluate HEMs algorithms. (Marco Notaro, Max Schubach, Peter N. Robinson and Giorgio Valentini (2017) <doi:10.1186/s12859-017-1854-y>).
Author: Marco Notaro [aut, cre] (<https://orcid.org/0000-0003-4309-2200>), Alessandro Petrini [ctb] (<https://orcid.org/0000-0002-0587-1484>), Giorgio Valentini [aut] (<https://orcid.org/0000-0002-5694-3919>)
Maintainer: Marco Notaro <marco.notaro@unimi.it>

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Package effects updated to version 4.1-4 with previous version 4.1-3 dated 2019-10-27

Title: Effect Displays for Linear, Generalized Linear, and Other Models
Description: Graphical and tabular effect displays, e.g., of interactions, for various statistical models with linear predictors.
Author: John Fox [aut, cre], Sanford Weisberg [aut], Brad Price [aut], Michael Friendly [aut], Jangman Hong [aut], Robert Andersen [ctb], David Firth [ctb], Steve Taylor [ctb], R Core Team [ctb]
Maintainer: John Fox <jfox@mcmaster.ca>

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Package aws updated to version 2.3-0 with previous version 2.2-1.1 dated 2019-10-30

Title: Adaptive Weights Smoothing
Description: We provide a collection of R-functions implementing adaptive smoothing procedures in 1D, 2D and 3D. This includes the Propagation-Separation Approach to adaptive smoothing as described in "J. Polzehl and V. Spokoiny (2006) <DOI:10.1007/s00440-005-0464-1>", "J. Polzehl and V. Spokoiny (2004) <DOI:10.20347/WIAS.PREPRINT.998>" and "J. Polzehl, K. Papafitsoros, K. Tabelow (2018) <DOI:10.20347/WIAS.PREPRINT.2520>", the Intersecting Confidence Intervals (ICI), variational approaches and a non-local means filter.
Author: Joerg Polzehl [aut, cre], Felix Anker [ctb]
Maintainer: Joerg Polzehl <joerg.polzehl@wias-berlin.de>

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Package tbrf updated to version 0.1.3 with previous version 0.1.2 dated 2019-02-02

Title: Time-Based Rolling Functions
Description: Provides rolling statistical functions based on date and time windows instead of n-lagged observations.
Author: Michael Schramm [aut, cre] (<https://orcid.org/0000-0003-1876-6592>), Frank Harrell [ctb]
Maintainer: Michael Schramm <michael.schramm@ag.tamu.edu>

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Package OncoBayes2 updated to version 0.5-3 with previous version 0.4-4 dated 2019-08-29

Title: Bayesian Logistic Regression for Oncology Dose-Escalation Trials
Description: Bayesian logistic regression model with optional EXchangeability-NonEXchangeability parameter modelling for flexible borrowing from historical or concurrent data-sources. The safety model can guide dose-escalation decisions for adaptive oncology Phase I dose-escalation trials which involve an arbitrary number of drugs. Please refer to Neuenschwander et al. (2008) <doi:10.1002/sim.3230> and Neuenschwander et al. (2016) <doi:10.1080/19466315.2016.1174149> for details on the methodology.
Author: Novartis Pharma AG [cph], Sebastian Weber [aut, cre], Andrew Bean [aut], Lukas A. Widmer [aut], Trustees of Columbia University [cph] (src/init.cpp, tools/make_cc.R, R/stanmodels.R, src/Makevars, src/Makevars.win)
Maintainer: Sebastian Weber <sebastian.weber@novartis.com>

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Package MultNonParam updated to version 1.3.0 with previous version 1.2.8 dated 2019-09-07

Title: Multivariate Nonparametric Methods
Description: A collection of multivariate nonparametric methods, selected in part to support an MS level course in nonparametric statistical methods. Methods include adjustments for multiple comparisons, implementation of multivariate Mann-Whitney-Wilcoxon testing, inversion of these tests to produce a confidence region, some permutation tests for linear models, and some algorithms for calculating exact probabilities associated with one- and two- stage testing involving Mann-Whitney-Wilcoxon statistics.
Author: John E. Kolassa [cre], Stephane Jankowski [aut]
Maintainer: John E. Kolassa <kolassa@stat.rutgers.edu>

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New package mauricer with initial version 2.0.3
Package: mauricer
Type: Package
Title: Install BEAST2 Packages
Version: 2.0.3
Author: Richèl J.C. Bilderbeek
Maintainer: Richèl J.C. Bilderbeek <richel@richelbilderbeek.nl>
Description: 'BEAST2' (<http://www.beast2.org>) is a widely used Bayesian phylogenetic tool, that uses DNA/RNA/protein data and many model priors to create a posterior of jointly estimated phylogenies and parameters. 'BEAST2' is commonly accompanied by 'BEAUti 2' (<http://www.beast2.org>), which, among others, allows one to install 'BEAST2' package. This package allows to install 'BEAST2' packages from 'R'.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: beastier
Imports: stringr
Suggests: testit, testthat (>= 2.1.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/ropensci/mauricer
BugReports: https://github.com/ropensci/mauricer/issues
SystemRequirements: BEAST2 (http://www.beast2.org/)
NeedsCompilation: no
Packaged: 2019-11-11 12:27:36 UTC; richel
Repository: CRAN
Date/Publication: 2019-11-15 20:20:02 UTC

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Package esreg updated to version 0.5.0 with previous version 0.4.0 dated 2019-01-09

Title: Joint Quantile and Expected Shortfall Regression
Description: Simultaneous modeling of the quantile and the expected shortfall of a response variable given a set of covariates, see Dimitriadis and Bayer (2019) <doi:10.1214/19-EJS1560>.
Author: Sebastian Bayer [aut, cre], Timo Dimitriadis [aut]
Maintainer: Sebastian Bayer <sebastian.bayer@uni-konstanz.de>

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New package thectar with initial version 1.0.0
Package: thectar
Type: Package
Title: Hermeneutic Content Analysis
Version: 1.0.0
Date: 2019-11-06
Author: Lena Berger
Maintainer: Lena Berger <bergerl@email.arizona.edu>
Description: A collection of tools for performing the second step of Hermeneutic Content Analysis (HCA; see Bergman, 2010, <doi:10.4135/9781506335193>). The current version provides tools for implementing multidimensional scaling (MDS) within an HCA framework. The tools offer assistance in data preparation, modeling, and interpretation of MDS maps. The data preparation tools help users to create similarity matrices based on co-occurrence or sorting data. The modelling tools allow users to optimize the modelling process by systematically calculating Stress values for a set of p points out of n points. The tools assisting interpretation allow users to highlight the highest similarities either per point or overall in an MDS representation.
Imports: smacof, graphics, utils, proxy
Depends: R (>= 2.10)
License: GPL-3
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-11-10 01:43:18 UTC; Lena
Repository: CRAN
Date/Publication: 2019-11-15 19:40:02 UTC

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Package rhoR updated to version 1.3.0.0 with previous version 1.2.1.2 dated 2019-11-05

Title: Rho for Inter Rater Reliability
Description: Rho is used to test the generalization of inter rater reliability (IRR) statistics. Calculating rho starts by generating a large number of simulated, fully-coded data sets: a sizable collection of hypothetical populations, all of which have a kappa value below a given threshold -- which indicates unacceptable agreement. Then kappa is calculated on a sample from each of those sets in the collection to see if it is equal to or higher than the kappa in then real sample. If less than five percent of the distribution of samples from the simulated data sets is greater than actual observed kappa, the null hypothesis is rejected and one can conclude that if the two raters had coded the rest of the data, we would have acceptable agreement (kappa above the threshold).
Author: Brendan Eagan [aut], Brad Rogers [aut], Rebecca Pozen [aut], Cody L Marquart [cre, aut] (<https://orcid.org/0000-0002-3387-6792>), David Williamson Shaffer [aut]
Maintainer: Cody L Marquart <cody.marquart@wisc.edu>

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More information about rhoR at CRAN
Permanent link

Package IDSpatialStats updated to version 0.3.10 with previous version 0.3.5 dated 2018-06-12

Title: Estimate Global Clustering in Infectious Disease
Description: Implements various novel and standard clustering statistics and other analyses useful for understanding the spread of infectious disease.
Author: John Giles <giles@jhu.edu>, Henrik Salje <hsalje@jhsph.edu>, Justin Lessler <justin@jhu.edu>
Maintainer: Justin Lessler <justin@jhu.edu>

Diff between IDSpatialStats versions 0.3.5 dated 2018-06-12 and 0.3.10 dated 2019-11-15

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More information about IDSpatialStats at CRAN
Permanent link

Package spThin updated to version 0.2.0 with previous version 0.1.0.1 dated 2019-03-11

Title: Functions for Spatial Thinning of Species Occurrence Records for Use in Ecological Models
Description: A set of functions that can be used to spatially thin species occurrence data. The resulting thinned data can be used in ecological modeling, such as ecological niche modeling.
Author: Matthew E. Aiello-Lammens [aut, cre], Robert A. Boria [aut], Aleksandar Radosavljevic [aut], Bruno Vilela [aut], Robert P. Anderson [aut], Robert Bjornson [ctb], Steve Weston [ctb]
Maintainer: Matthew E. Aiello-Lammens <matt.lammens@gmail.com>

Diff between spThin versions 0.1.0.1 dated 2019-03-11 and 0.2.0 dated 2019-11-15

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More information about spThin at CRAN
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New package qMRI with initial version 1.1.1
Package: qMRI
Type: Package
Title: Methods for Quantitative Magnetic Resonance Imaging ('qMRI')
Version: 1.1.1
Date: 2019-11-14
Authors@R: c(person("Joerg", "Polzehl", role = c("aut"), email = "joerg.polzehl@wias-berlin.de"), person("Karsten", "Tabelow", role = c("aut", "cre"), email = "karsten.tabelow@wias-berlin.de"), person("WIAS Berlin", role = c("cph", "fnd")))
Maintainer: Karsten Tabelow <karsten.tabelow@wias-berlin.de>
Depends: R (>= 3.5), awsMethods (>= 1.0), methods
Imports: oro.nifti (>= 0.9), stringr, dti (>= 1.4), aws (>= 2.2), adimpro (>= 0.9)
LazyData: TRUE
Description: Implementation of methods for estimation of quantitative maps from Multi-Parameter Mapping (MPM) acquisitions (Weiskopf et al. (2013) <doi:10.3389/fnins.2013.00095>) including adaptive smoothing methods in the framework of the ESTATICS model (Estimating the apparent transverse relaxation time (R2*) from images with different contrasts, Weiskopf et al. (2014) <doi:10.3389/fnins.2014.00278>). The smoothing method is described in Mohammadi et al. (2017). <doi:10.20347/WIAS.PREPRINT.2432>. Usage of the package is also described in Polzehl and Tabelow (2019), Magnetic Resonance Brain Imaging, Chapter 6, Springer, Use R! Series. <doi:10.1007/978-3-030-29184-6_6>.
License: GPL (>= 2)
Copyright: This package is Copyright (C) 2015-2019 Weierstrass Institute for Applied Analysis and Stochastics.
URL: http://www.wias-berlin.de/research/ats/imaging/
Suggests: covr, testthat, knitr, rmarkdown
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-11-14 10:53:48 UTC; polzehl
Author: Joerg Polzehl [aut], Karsten Tabelow [aut, cre], WIAS Berlin [cph, fnd]
Repository: CRAN
Date/Publication: 2019-11-15 18:50:02 UTC

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Package pmsampsize updated to version 1.0.2 with previous version 1.0.1 dated 2019-08-02

Title: Calculates the Minimum Sample Size Required for Developing a Multivariable Prediction Model
Description: Computes the minimum sample size required for the development of a new multivariable prediction model using the criteria proposed by Riley et al. (2018) <doi: 10.1002/sim.7992>. pmsampsize can be used to calculate the minimum sample size for the development of models with continuous, binary or survival (time-to-event) outcomes. Riley et al. (2018) <doi: 10.1002/sim.7992> lay out a series of criteria the sample size should meet. These aim to minimise the overfitting and to ensure precise estimation of key parameters in the prediction model.
Author: Joie Ensor [aut, cre], Emma C. Martin [aut], Richard D. Riley [aut]
Maintainer: Joie Ensor <j.ensor@keele.ac.uk>

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Package kde1d updated to version 1.0.1 with previous version 1.0.0 dated 2019-11-15

Title: Univariate Kernel Density Estimation
Description: Provides an efficient implementation of univariate local polynomial kernel density estimators that can handle bounded and discrete data. See Geenens (2014) <arXiv:1303.4121>, Geenens and Wang (2018) <arXiv:1602.04862>, Nagler (2018a) <arXiv:1704.07457>, Nagler (2018b) <arXiv:1705.05431>.
Author: Thomas Nagler [aut, cre], Thibault Vatter [aut]
Maintainer: Thomas Nagler <mail@tnagler.com>

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Package grattan updated to version 1.8.0.0 with previous version 1.7.1.2 dated 2019-05-20

Title: Australian Tax Policy Analysis
Description: Utilities for costing and evaluating Australian tax policy, including high-performance tax and transfer calculators, a fast method of projecting tax collections, and an interface to common indices from the Australian Bureau of Statistics. Written to support Grattan Institute's Australian Perspectives program. For access to the 'taxstats' package, please run install.packages("taxstats", repos = "https://hughparsonage.github.io/tax-drat/", type = "source"). N.B. The 'taxstats' package is approximately 50 MB.
Author: Hugh Parsonage [aut, cre], Tim Cameron [aut], Brendan Coates [aut], Matthew Katzen [aut], William Young [aut], Ittima Cherastidtham [dtc], W. Karsten [ctb], M. Enrique Garcia [ctb], Matt Cowgill [aut]
Maintainer: Hugh Parsonage <hugh.parsonage@gmail.com>

Diff between grattan versions 1.7.1.2 dated 2019-05-20 and 1.8.0.0 dated 2019-11-15

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New package subformula with initial version 0.1.0
Package: subformula
Type: Package
Title: Create Subformulas of a Formula
Version: 0.1.0
Authors@R: c( person("Jonas", "Moss", , "jonas.gjertsen@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-6876-6964") ))
Description: A formula 'sub' is a subformula of 'formula' if all the terms on the right hand side of 'sub' are terms of 'formula' and their left hand sides are identical. This package aids in the creation of subformulas.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: testthat, rmarkdown, knitr, covr
VignetteBuilder: knitr
URL: https://github.com/JonasMoss/subformula,
BugReports: https://github.com/JonasMoss/subformula/issues
NeedsCompilation: no
Packaged: 2019-11-12 16:25:04 UTC; jonas
Author: Jonas Moss [aut, cre] (<https://orcid.org/0000-0002-6876-6964>)
Maintainer: Jonas Moss <jonas.gjertsen@gmail.com>
Repository: CRAN
Date/Publication: 2019-11-15 17:10:02 UTC

More information about subformula at CRAN
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Package RMAWGEN updated to version 1.3.6 with previous version 1.3.3 dated 2017-02-10

Title: Multi-Site Auto-Regressive Weather GENerator
Description: S3 and S4 functions are implemented for spatial multi-site stochastic generation of daily time series of temperature and precipitation. These tools make use of Vector AutoRegressive models (VARs). The weather generator model is then saved as an object and is calibrated by daily instrumental "Gaussianized" time series through the 'vars' package tools. Once obtained this model, it can it can be used for weather generations and be adapted to work with several climatic monthly time series.
Author: Emanuele Cordano, Emanuele Eccel
Maintainer: Emanuele Cordano <emanuele.cordano@gmail.com>

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Package NPCD updated to version 1.0-11 with previous version 1.0-10 dated 2016-10-18

Title: Nonparametric Methods for Cognitive Diagnosis
Description: An array of nonparametric and parametric estimation methods for cognitive diagnostic models, including nonparametric classification of examinee attribute profiles, joint maximum likelihood estimation (JMLE) of examinee attribute profiles and item parameters, and nonparametric refinement of the Q-matrix, as well as conditional maximum likelihood estimation (CMLE) of examinee attribute profiles given item parameters and CMLE of item parameters given examinee attribute profiles. Currently the nonparametric methods in the package support both conjunctive and disjunctive models, and the parametric methods in the package support the DINA model, the DINO model, the NIDA model, the G-NIDA model, and the R-RUM model.
Author: Yi Zheng [aut, cre], Chia-Yi Chiu [aut], Jeffrey A. Douglas [ctb]
Maintainer: Yi Zheng <yi.isabel.zheng@asu.edu>

Diff between NPCD versions 1.0-10 dated 2016-10-18 and 1.0-11 dated 2019-11-15

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Package JQL updated to version 3.6.9 with previous version 2.3.3 dated 2019-02-22

Title: Jump Q-Learning for Individualized Interval-Valued Dose Rule
Description: We provide tools to estimate the individualized interval-valued dose rule (I2DR) that maximizes the expected beneficial clinical outcome for each individual and returns an optimal interval-valued dose, by using the jump Q-learning (JQL) method. The jump Q-learning method directly models the conditional mean of the response given the dose level and the baseline covariates via jump penalized least squares regression under the framework of Q learning. We develop a searching algorithm by dynamic programming in order to find the optimal I2DR with the time complexity O(n2) and spatial complexity O(n). To alleviate the effects of misspecification of the Q-function, a residual jump Q-learning is further proposed to estimate the optimal I2DR. The outcome of interest includes the best partition of the entire dosage of interest, the regression coefficients of each partition, and the value function under the estimated I2DR as well as the Wald-type confidence interval of value function constructed through the Bootstrap.
Author: Hengrui Cai <hcai5@ncsu.edu>, Chengchun shi <cshi4@ncsu.edu>, Rui Song <rsong@ncsu.edu>, Wenbin Lu <wlu4@ncsu.edu>
Maintainer: Hengrui Cai <hcai5@ncsu.edu>

Diff between JQL versions 2.3.3 dated 2019-02-22 and 3.6.9 dated 2019-11-15

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New package ezCutoffs with initial version 1.0.0
Package: ezCutoffs
Date: 2019-11-09
Type: Package
Title: Fit Measure Cutoffs in SEM
Version: 1.0.0
Depends: R (>= 2.15.1)
Authors@R: c(person(given = "Bjarne", family = "Schmalbach", comment = c(ORCID = "0000-0001-6853-412X"), role = c("aut", "cre"), email = "bjarne.schmalbach@gmail.com"), person(given = "Julien Patrick", family = "Irmer", role= "aut"), person(given = "Martin", family = "Schultze", role = "aut"))
Description: Calculate cutoff values for model fit measures used in structural equation modeling (SEM) by simulating and testing data sets (cf. Hu & Bentler, 1999 <doi:10.1080/10705519909540118>) with the same parameters (population model, number of observations, etc.) as the model under consideration.
License: GPL-3
Imports: doSNOW, foreach, ggplot2, lavaan, moments, parallel, progress, stats, utils
Suggests: boot
Maintainer: Bjarne Schmalbach <bjarne.schmalbach@gmail.com>
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Author: Bjarne Schmalbach [aut, cre] (<https://orcid.org/0000-0001-6853-412X>), Julien Patrick Irmer [aut], Martin Schultze [aut]
NeedsCompilation: no
Packaged: 2019-11-15 15:25:20 UTC; q7
Repository: CRAN
Date/Publication: 2019-11-15 17:10:05 UTC

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New package EPT with initial version 0.7.3
Package: EPT
Version: 0.7.3
Date: 2019-11-09
Title: Ensemble Patch Transform, Visualization and Decomposition
Authors@R: c(person("Donghoh", "Kim", role = c("aut", "cre"), email = "donghoh.kim@gmail.com"), person("Hee-Seok", "Oh", role = "aut", email = "heeseok@stats.snu.ac.kr"), person("Guebin", "Choi", role = "ctb"))
Author: Donghoh Kim [aut, cre], Hee-Seok Oh [aut], Guebin Choi [ctb]
Maintainer: Donghoh Kim <donghoh.kim@gmail.com>
Depends: R (>= 3.0)
Description: For multiscale analysis, this package carries out ensemble patch transform, its visualization and multiscale decomposition. The detailed procedure is described in Donghoh Kim, Guebin Choi and Hee-Seok Oh (2019) <arXiv:1904.03643>.
License: GPL (>= 3)
NeedsCompilation: no
Packaged: 2019-11-15 14:17:30 UTC; donghohkim
Repository: CRAN
Date/Publication: 2019-11-15 17:10:08 UTC

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Package colourvalues updated to version 0.3.1 with previous version 0.3.0 dated 2019-09-23

Title: Assigns Colours to Values
Description: Maps one of the viridis colour palettes, or a user-specified palette to values. Viridis colour maps are created by Stéfan van der Walt and Nathaniel Smith. They were set as the default palette for the 'Python' 'Matplotlib' library, introduced at SciPy 2015 conference <http://scipy2015.scipy.org/ehome/index.php?eventid=115969&>. Other palettes available in this library have been derived from 'RColorBrewer' <https://CRAN.R-project.org/package=RColorBrewer> and 'colorspace' <https://CRAN.R-project.org/package=colorspace> packages.
Author: David Cooley [aut, cre]
Maintainer: David Cooley <dcooley@symbolix.com.au>

Diff between colourvalues versions 0.3.0 dated 2019-09-23 and 0.3.1 dated 2019-11-15

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New package diem with initial version 1.0
Package: diem
Title: Debris-Containing Droplet Identification using EM
Version: 1.0
Date: 2019-11-05
Authors@R: c(person(given = "Marcus", family = "Alvarez", role = c("aut", "cre"), email = "malvarez@mednet.ucla.edu"), person(given = "Elior", family = "Rahmani", role = "aut", email = "elior.rahmani@gmail.com"))
Description: Identification of debris-containing droplets from a droplet-based single cell/nucleus RNA-seq. 'diem' uses the expression profile of background RNA droplets, followed by expectation maximization (EM), to assign candidates as debris or nuclei. See Alvarez M, Rahmani E, et al (2019) <doi:10.1101/786285> for details.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 3.5.0), methods
LinkingTo: Rcpp, RcppEigen
Imports: ggplot2, Matrix, scales, dbscan, igraph, utils, stats
Suggests: Seurat (>= 3.0.0), testthat, knitr, rmarkdown
VignetteBuilder: knitr
URL: https://www.biorxiv.org/content/10.1101/786285v2
BugReports: https://github.com/marcalva/diem/issues
NeedsCompilation: yes
Packaged: 2019-11-13 01:35:39 UTC; malvarez
Author: Marcus Alvarez [aut, cre], Elior Rahmani [aut]
Maintainer: Marcus Alvarez <malvarez@mednet.ucla.edu>
Repository: CRAN
Date/Publication: 2019-11-15 17:30:03 UTC

More information about diem at CRAN
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Package rslurm updated to version 0.5.0 with previous version 0.4.0 dated 2017-10-19

Title: Submit R Calculations to a 'Slurm' Cluster
Description: Functions that simplify submitting R scripts to a 'Slurm' workload manager, in part by automating the division of embarrassingly parallel calculations across cluster nodes.
Author: Philippe Marchand [aut], Ian Carroll [aut], Mike Smorul [ctb], Rachael Blake [ctb], Quentin Read [ctb, cre]
Maintainer: Quentin Read <qread@sesync.org>

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Package car updated to version 3.0-5 with previous version 3.0-4 dated 2019-10-27

Title: Companion to Applied Regression
Description: Functions to Accompany J. Fox and S. Weisberg, An R Companion to Applied Regression, Third Edition, Sage, 2019.
Author: John Fox [aut, cre], Sanford Weisberg [aut], Brad Price [aut], Daniel Adler [ctb], Douglas Bates [ctb], Gabriel Baud-Bovy [ctb], Ben Bolker [ctb], Steve Ellison [ctb], David Firth [ctb], Michael Friendly [ctb], Gregor Gorjanc [ctb], Spencer Graves [ctb], Richard Heiberger [ctb], Pavel Krivitsky [ctb], Rafael Laboissiere [ctb], Martin Maechler [ctb], Georges Monette [ctb], Duncan Murdoch [ctb], Henric Nilsson [ctb], Derek Ogle [ctb], Brian Ripley [ctb], William Venables [ctb], Steve Walker [ctb], David Winsemius [ctb], Achim Zeileis [ctb], R-Core [ctb]
Maintainer: John Fox <jfox@mcmaster.ca>

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Package shar updated to version 1.1 with previous version 1.0.1 dated 2019-09-10

Title: Species-Habitat Associations
Description: Analyse species-habitat associations in R. Therefore, information about the location of the species is needed and about the environmental conditions. To test for significance habitat associations, one of the two components is randomized. Methods are mainly based on Plotkin et al. (2000) <doi:10.1006/jtbi.2000.2158> and Harms et al. (2001) <doi:10.1111/j.1365-2745.2001.00615.x>.
Author: Maximillian H.K. Hesselbarth [aut, cre] (<https://orcid.org/0000-0003-1125-9918>), Marco Sciaini [aut] (<https://orcid.org/0000-0002-3042-5435>)
Maintainer: Maximillian H.K. Hesselbarth <maximilian.hesselbarth@uni-goettingen.de>

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Package qgraph updated to version 1.6.4 with previous version 1.6.3 dated 2019-06-19

Title: Graph Plotting Methods, Psychometric Data Visualization and Graphical Model Estimation
Description: Weighted network visualization and analysis, as well as Gaussian graphical model computation. See Epskamp et al. (2012) <doi:10.18637/jss.v048.i04>.
Author: Sacha Epskamp [aut, cre], Giulio Costantini [aut], Jonas Haslbeck [aut], Adela Isvoranu [aut], Angelique O. J. Cramer [ctb], Lourens J. Waldorp [ctb], Verena D. Schmittmann [ctb], Denny Borsboom [ctb]
Maintainer: Sacha Epskamp <mail@sachaepskamp.com>

Diff between qgraph versions 1.6.3 dated 2019-06-19 and 1.6.4 dated 2019-11-15

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New package fmri with initial version 1.9.2.1
Package: fmri
Version: 1.9.2.1
Date: 2019-11-14
Title: Analysis of fMRI Experiments
Authors@R: c(person("Karsten", "Tabelow", role = c("aut", "cre"), email = "tabelow@wias-berlin.de"), person("Joerg", "Polzehl", role = c("aut"), email = "polzehl@wias-berlin.de"), person("Brandon", "Whitcher", role = c("ctb")), person("Dames", "Sibylle", role = c("ctb")))
Depends: R (>= 3.2.0), awsMethods (>= 1.1-1), nlme
Imports: parallel, metafor, methods, aws
Suggests: tcltk, tkrplot, fastICA, adimpro (>= 0.9), oro.nifti
LazyData: true
Description: Contains R-functions to perform an fMRI analysis as described in Tabelow et al. (2006) <DOI:10.1016/j.neuroimage.2006.06.029>, Polzehl et al. (2010) <DOI:10.1016/j.neuroimage.2010.04.241>, Tabelow and Polzehl (2011) <DOI:10.18637/jss.v044.i11>.
License: GPL (>= 2)
Copyright: This package is Copyright (C) 2006-2019 Weierstrass Institute for Applied Analysis and Stochastics.
URL: http://www.wias-berlin.de/software/imaging/
Note: This software comes with NO warranty! It is NOT intended to be used in clinical applications! For evaluation only!
RoxygenNote: 6.1.0
NeedsCompilation: yes
Packaged: 2019-11-14 12:06:50 UTC; polzehl
Author: Karsten Tabelow [aut, cre], Joerg Polzehl [aut], Brandon Whitcher [ctb], Dames Sibylle [ctb]
Maintainer: Karsten Tabelow <tabelow@wias-berlin.de>
Repository: CRAN
Date/Publication: 2019-11-15 16:00:03 UTC

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New package dti with initial version 1.4.3
Package: dti
Version: 1.4.3
Date: 2019-11-14
Title: Analysis of Diffusion Weighted Imaging (DWI) Data
Authors@R: c(person("Karsten", "Tabelow", role = c("aut", "cre"), email = "karsten.tabelow@wias-berlin.de"), person("Joerg", "Polzehl", role = c("aut"), email = "joerg.polzehl@wias-berlin.de"), person("Felix", "Anker", role = c("ctb")))
Author: Karsten Tabelow [aut, cre], Joerg Polzehl [aut], Felix Anker [ctb]
Maintainer: Karsten Tabelow <karsten.tabelow@wias-berlin.de>
Depends: R (>= 3.5.0), awsMethods (>= 1.1-1)
SystemRequirements: gsl
Imports: methods, parallel, adimpro (>= 0.9), rgl, oro.nifti (>= 0.3.9), oro.dicom, gsl, quadprog
LazyData: TRUE
Description: Diffusion Weighted Imaging (DWI) is a Magnetic Resonance Imaging modality, that measures diffusion of water in tissues like the human brain. The package contains R-functions to process diffusion-weighted data. The functionality includes diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), modeling for high angular resolution diffusion weighted imaging (HARDI) using Q-ball-reconstruction and tensor mixture models, several methods for structural adaptive smoothing including POAS and msPOAS, and a streamline fiber tracking for tensor and tensor mixture models. The package provides functionality to manipulate and visualize results in 2D and 3D.
License: GPL (>= 2)
Copyright: This package is Copyright (C) 2005-2019 Weierstrass Institute for Applied Analysis and Stochastics.
URL: http://www.wias-berlin.de/research/ats/imaging/
Suggests: covr
RoxygenNote: 6.1.0
NeedsCompilation: yes
Packaged: 2019-11-14 11:10:26 UTC; polzehl
Repository: CRAN
Date/Publication: 2019-11-15 16:00:07 UTC

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New package multbxxc with initial version 1.0.1
Package: multbxxc
Type: Package
Title: Auxiliary Routines for Influx Software
Version: 1.0.1
Date: 2019-11-12
Author: Serguei Sokol
Maintainer: Serguei Sokol <sokol@insa-toulouse.fr>
Description: Contains auxiliary routines for influx software. This packages is not intended to be used directly. Influx was published here: Sokol et al. (2012) <doi:10.1093/bioinformatics/btr716>.
License: GPL (>= 2)
Imports: Rcpp (>= 1.0.0)
LinkingTo: Rcpp, RcppArmadillo, rmumps
Depends: R (>= 3.4), rmumps (>= 5.2.1-6)
URL: https://metasys.insa-toulouse.fr/software/influx/
RoxygenNote: 6.1.1
Encoding: UTF-8
Suggests: testthat
NeedsCompilation: yes
Packaged: 2019-11-09 16:51:24 UTC; sokol
Repository: CRAN
Date/Publication: 2019-11-15 13:10:02 UTC

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New package ip2location with initial version 8.0.0
Package: ip2location
Title: Lookup for IP Address Information
Version: 8.0.0
Author: Chris Lim
Maintainer: Chris Lim <chris@ip2location.com>
Description: Enables the user to find the country, region, city, coordinates, zip code, time zone, ISP, domain name, connection type, area code, weather station code, weather station name, mobile, usage types, etc that any IP address or hostname originates from. Supported IPv4 and IPv6. Please visit <https://www.ip2location.com> to learn more. You may also want to visit <https://lite.ip2location.com> for free database download. This package requires 'IP2Location Python' module. At the terminal, please run 'pip install IP2Location' to install the module.
License: MIT + file LICENSE
URL: https://github.com/ip2location/ip2location-r
Encoding: UTF-8
Depends: R (>= 3.2.3)
SystemRequirements: IP2Location Python library <https://www.ip2location.com/development-libraries/ip2location/python>
Imports: reticulate (>= 1.13), stringr (>= 1.4.0), jsonlite (>= 1.6)
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-11-12 03:15:33 UTC; Chris
Repository: CRAN
Date/Publication: 2019-11-15 13:10:05 UTC

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New package tidydice with initial version 0.0.3
Package: tidydice
Type: Package
Title: Simulates Dice Rolls and Coin Flips
Version: 0.0.3
Author: Roland Krasser
Maintainer: Roland Krasser <roland.krasser@gmail.com>
Description: Utils for basic statistical experiments, that can be used for teaching introductory statistics. Each experiment generates a tibble. Dice rolls and coin flips are simulated using sample(). The properties of the dice can be changed, like the number of sides. A coin flip is simulated using a two sided dice. Experiments can be combined with the pipe-operator.
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: http://github.com/rolkra/tidydice
Imports: assertthat, dplyr, magrittr, purrr, tibble
RoxygenNote: 6.1.1
Suggests: explore, knitr, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-11-11 07:32:55 UTC; uJQB7LF
Repository: CRAN
Date/Publication: 2019-11-15 12:10:02 UTC

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New package SummaryLasso with initial version 1.2.1
Package: SummaryLasso
Type: Package
Title: Building Polygenic Risk Score Using GWAS Summary Statistics
Version: 1.2.1
Author: Ting-Huei Chen
Maintainer: Ting-Huei Chen <tingstat22@gmail.com>
Depends: R(>= 3.5.0), gtools
Description: Shrinkage estimator for polygenic risk prediction models based on summary statistics of genome-wide association studies.
License: GPL-3
Packaged: 2019-11-11 15:52:02 UTC; ting-huei
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2019-11-15 12:40:02 UTC

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New package iq with initial version 1.0
Package: iq
Type: Package
Title: Protein Quantification in Mass Spectrometry-Based Proteomics
Version: 1.0
Authors@R: c(person("Thang", "Pham", email = "t.pham@amsterdamumc.nl", role = c("aut", "cre", "cph", "ctb"), comment = c(ORCID = "0000-0003-0333-2492")), person("Alex", "Henneman", email = "a.henneman@amsterdamumc.nl", role = c("ctb"), comment = c(ORCID = "0000-0002-3746-4410")))
Maintainer: Thang Pham <t.pham@amsterdamumc.nl>
Description: An implementation of the maximal peptide ratio extraction module of the MaxLFQ algorithm by Cox et al. (2014) <doi:10.1074/mcp.M113.031591> in a complete pipeline for processing proteomics data in data-independent acquisition mode. It offers additional options for protein quantification using the N most intense fragment ions, using all fragment ions, and a wrapper for the median polish algorithm by Tukey (1977, ISBN:0201076160).
Depends: R (>= 2.10)
License: BSD_3_clause + file LICENSE
Encoding: UTF-8
LazyData: true
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-11-11 09:14:22 UTC; t.pham
Author: Thang Pham [aut, cre, cph, ctb] (<https://orcid.org/0000-0003-0333-2492>), Alex Henneman [ctb] (<https://orcid.org/0000-0002-3746-4410>)
Repository: CRAN
Date/Publication: 2019-11-15 12:10:05 UTC

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New package effectsize with initial version 0.0.1
Package: effectsize
Type: Package
Title: Indices of Effect Size and Standardized Parameters
Version: 0.0.1
Authors@R: c( person("Dominique", "Makowski", email = "dom.makowski@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-5375-9967")), person("Daniel", "Lüdecke", role = c("aut"), email = "d.luedecke@uke.de", comment = c(ORCID = "0000-0002-8895-3206")), person("Mattan S.", "Ben-Shachar", role = c("aut"), email = "matanshm@post.bgu.ac.il", comment = c(ORCID = "0000-0002-4287-4801")), person("Ken", "Kelley", role = c("ctb")), person("David", "Stanley", role = c("ctb")) )
Maintainer: Dominique Makowski <dom.makowski@gmail.com>
URL: https://github.com/easystats/effectsize
BugReports: https://github.com/easystats/effectsize/issues
Description: Provide utilities to work with indices of effect size and standardized parameters for a wide variety of models (see support list of insight; Lüdecke, Waggoner & Makowski (2019) <doi:10.21105/joss.01412>), allowing computation and conversion of indices such as Cohen's d, r, odds, etc.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.0)
Imports: insight (>= 0.6.0), bayestestR (>= 0.4.0), parameters (>= 0.2.0), methods, stats, utils
Suggests: afex, brms, boot, covr, dplyr, emmeans, gamm4, ggplot2, knitr, lmerTest, lm.beta, lme4, MuMIn, performance, ppcor, rmarkdown, rstan, rstanarm, see, testthat, tidyr
RoxygenNote: 6.1.1
Language: en-GB
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-11-11 23:45:12 UTC; Dom
Author: Dominique Makowski [aut, cre] (<https://orcid.org/0000-0001-5375-9967>), Daniel Lüdecke [aut] (<https://orcid.org/0000-0002-8895-3206>), Mattan S. Ben-Shachar [aut] (<https://orcid.org/0000-0002-4287-4801>), Ken Kelley [ctb], David Stanley [ctb]
Repository: CRAN
Date/Publication: 2019-11-15 13:00:02 UTC

More information about effectsize at CRAN
Permanent link

New package BAGofT with initial version 0.1.0
Package: BAGofT
Type: Package
Title: A Binary Regression Adaptive Goodness-of-Fit Test (BAGofT)
Version: 0.1.0
Authors@R: c(person("Jiawei", "Zhang", email = "zhan4362@umn.edu", role = c("aut", "cre")), person("Jie", "Ding", email = "dingj@umn.edu", role = "aut"), person("Yuhong", "Yang", email = "yangx374@umn.edu", role = "aut"))
Description: Performs goodness-of-fit test for binary regression models with at least 1 continuous covariate. The implemented method BAGofT is from Zhang, Ding and Yang (2019) <arXiv:1911.03063>.
Depends: R (>= 3.6.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: stringr (>= 1.4.0)
Suggests: nnet (>= 7.3.12), randomForest (>= 4.6.14)
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-11-11 20:28:39 UTC; mikezhang
Author: Jiawei Zhang [aut, cre], Jie Ding [aut], Yuhong Yang [aut]
Maintainer: Jiawei Zhang <zhan4362@umn.edu>
Repository: CRAN
Date/Publication: 2019-11-15 12:30:02 UTC

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New package azuremlsdk with initial version 0.5.7
Package: azuremlsdk
Type: Package
Title: Interface to the 'Azure Machine Learning' 'SDK'
Version: 0.5.7
Authors@R: c( person("Heemanshu", "Suri", email = "Heemanshu.Suri@microsoft.com", role = c("cre", "aut")), person("Billy", "Hu", email = "ninhu@microsoft.com", role = c("aut")), person("Diondra", "Peck", email = "Diondra.Peck@microsoft.com", role = c("aut")), person("Minna", "Xiao", email = "Minna.Xiao@microsoft.com", role = c("aut")), person("Himanshu", "Chandola", email = "Himanshu.Chandola@microsoft.com", role = c("ctb")), person("Abe", "Omorogbe", email = "Osarumwense.Omorogbe@microsoft.com", role = c("ctb")), person("Microsoft", role = c("cph", "fnd")), person(family = "Google Inc.", role = c("cph"), comment = "Examples and Tutorials"), person(family = "The TensorFlow Authors", role = c("cph"), comment = "Examples and Tutorials"), person(family = "RStudio Inc.", role = c("cph"), comment = "Examples and Tutorials") )
URL: https://github.com/azure/azureml-sdk-for-r
BugReports: https://github.com/azure/azureml-sdk-for-r/issues
Description: Interface to the 'Azure Machine Learning' Software Development Kit ('SDK'). Data scientists can use the 'SDK' to train, deploy, automate, and manage machine learning models on the 'Azure Machine Learning' service. To learn more about 'Azure Machine Learning' visit the website: <https://docs.microsoft.com/en-us/azure/machine-learning/service/overview-what-is-azure-ml>.
Encoding: UTF-8
License: MIT + file LICENSE
RoxygenNote: 6.1.1
Depends: R (>= 3.5.0)
Imports: ggplot2, reticulate (>= 1.12), plyr (>= 1.8), DT, rstudioapi (>= 0.7), htmltools
Suggests: rmarkdown, knitr, testthat, dplyr, jsonlite
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-11-11 22:21:12 UTC; hesuri
Author: Heemanshu Suri [cre, aut], Billy Hu [aut], Diondra Peck [aut], Minna Xiao [aut], Himanshu Chandola [ctb], Abe Omorogbe [ctb], Microsoft [cph, fnd], Google Inc. [cph] (Examples and Tutorials), The TensorFlow Authors [cph] (Examples and Tutorials), RStudio Inc. [cph] (Examples and Tutorials)
Maintainer: Heemanshu Suri <Heemanshu.Suri@microsoft.com>
Repository: CRAN
Date/Publication: 2019-11-15 13:00:06 UTC

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New package vhcub with initial version 1.0.0
Package: vhcub
Title: Virus-Host Codon Usage Co-Adaptation Analysis
Version: 1.0.0
Authors@R: c( person(given = "Ali",family = "Mostafa Anwar",role = c("aut", "cre"),email = "ali.mo.anwar@std.agr.cu.edu.eg"), person(given = "Mohamed",family = "Soudy",email = "MohmedSoudy2009@gmail.com", role = "aut"))
Author: Ali Mostafa Anwar [aut, cre], Mohamed Soudy [aut]
Maintainer: Ali Mostafa Anwar <ali.mo.anwar@std.agr.cu.edu.eg>
Description: Analyze the co-adaptation of codon usage between a virus and its host, calculate various codon usage bias measurements as: effective number of codons (ENc) Novembre (2002) <doi:10.1093/oxfordjournals.molbev.a004201>, codon adaptation index (CAI) Sharp and Li (1987) <doi:10.1093/nar/15.3.1281>, relative codon deoptimization index (RCDI) Puigbò et al (2010) <doi:10.1186/1756-0500-3-87>, similarity index (SiD) Zhou et al (2013) <doi:10.1371/journal.pone.0077239>, synonymous codon usage orderliness (SCUO) Wan et al (2004) <doi:10.1186/1471-2148-4-19> and, relative synonymous codon usage (RSCU) Sharp et al (1986) <doi:10.1093/nar/14.13.5125>. Also, it provides a statistical dinucleotide over- and underrepresentation with three different models. Implement several methods for visualization of codon usage as ENc.GC3plot() and PR2.plot().
License: GPL-3
Encoding: UTF-8
LazyData: true
biocViews:
Imports: Biostrings, coRdon , ggplot2, seqinr, stringr
RoxygenNote: 6.1.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-11-07 17:12:46 UTC; ali
Repository: CRAN
Date/Publication: 2019-11-15 12:00:02 UTC

More information about vhcub at CRAN
Permanent link

New package VancouvR with initial version 0.1.1
Package: VancouvR
Type: Package
Title: Access the 'City of Vancouver' Open Data API
Version: 0.1.1
Author: Jens von Bergmann
Maintainer: Jens von Bergmann <jens@mountainmath.ca>
Description: Wrapper around the 'City of Vancouver' Open Data API <https://opendata.vancouver.ca/api/v2/console> to simplify and standardize access to 'City of Vancouver' open data. Functionality to list the data catalogue and access data and geographic records.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
RoxygenNote: 6.1.1
Imports: dplyr, httr, rlang, urltools, readr, digest, sf, tibble, purrr
Suggests: knitr, rmarkdown, ggplot2, lwgeom, tidyr
VignetteBuilder: knitr
URL: https://github.com/mountainMath/VancouvR, https://mountainmath.github.io/VancouvR/
BugReports: https://github.com/mountainMath/VancouvR/issues
Packaged: 2019-11-10 21:34:39 UTC; jens
Repository: CRAN
Date/Publication: 2019-11-15 12:00:08 UTC

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New package ToxicoGx with initial version 0.0.1
Package: ToxicoGx
Type: Package
Title: Analysis of Large-Scale Toxico-Genomic Data
Version: 0.0.1
Date: 2019-10-22
Authors@R: c( person("Sisira","Nair", email = "sisira.nair@uhnresearch.ca", role = c("aut")), person("Esther","Yoo", email = "yk.yoo@mail.utoronto.ca", role = c("aut")), person("Christopher","Eeles", email = "christopher.eeles@uhnresearch.ca", role = c("aut")), person("Amy", "Tang", email = "amy.tang@queensu.ca", role = c("aut")), person("Nehme", "El-Hachem1", email = "hachemn@gmail.com", role = c("aut")), person("Petr","Smirnov", email = "petr.smirnov@uhnresearch.ca", role = c("aut")), person("Benjamin","Haibe-Kains", email = "benjamin.haibe.kains@utoronto.ca", role = c("aut","cre")) )
Description: Contains a set of functions to perform large-scale analysis of toxicogenomic data. A member of the Benjamin Haibe-Kains (BHK) lab's genomics (Gx) suite of software, this package provides a standardized data structure to hold information relevant to annotation, visualization and statistical analysis of toxico-genomic data. This package is in early release, and more features will be added over the next few months. For more information please see the included documentation, vignette, as well as: Ruede-Zarate, H.A. et al (2017) <doi:10.1371/journal.pone.0176284>, Caiment, F. et al (2014) <doi:10.1093/carcin/bgt278>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0), CoreGx
Imports: SummarizedExperiment, Biobase, RColorBrewer, caTools, magicaxis, methods, reshape2, scales
RoxygenNote: 6.1.1
VignetteBuilder: knitr
Suggests: testthat (>= 2.1.0), rmarkdown, knitr, knitcitations, tinytex, devtools, PharmacoGx, xtable
NeedsCompilation: no
Packaged: 2019-11-06 14:44:07 UTC; ceeles
Author: Sisira Nair [aut], Esther Yoo [aut], Christopher Eeles [aut], Amy Tang [aut], Nehme El-Hachem1 [aut], Petr Smirnov [aut], Benjamin Haibe-Kains [aut, cre]
Maintainer: Benjamin Haibe-Kains <benjamin.haibe.kains@utoronto.ca>
Repository: CRAN
Date/Publication: 2019-11-15 11:50:04 UTC

More information about ToxicoGx at CRAN
Permanent link

Package taxize updated to version 0.9.91 with previous version 0.9.9 dated 2019-10-17

Title: Taxonomic Information from Around the Web
Description: Interacts with a suite of web 'APIs' for taxonomic tasks, such as getting database specific taxonomic identifiers, verifying species names, getting taxonomic hierarchies, fetching downstream and upstream taxonomic names, getting taxonomic synonyms, converting scientific to common names and vice versa, and more.
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>), Eduard Szoecs [aut], Zachary Foster [aut], Zebulun Arendsee [aut], Carl Boettiger [ctb], Karthik Ram [ctb], Ignasi Bartomeus [ctb], John Baumgartner [ctb], James O'Donnell [ctb], Jari Oksanen [ctb], Bastian Greshake Tzovaras [ctb], Philippe Marchand [ctb], Vinh Tran [ctb], Maëlle Salmon [ctb], Gaopeng Li [ctb], Matthias Grenié [ctb], rOpenSci [fnd] (https://ropensci.org/)
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

Diff between taxize versions 0.9.9 dated 2019-10-17 and 0.9.91 dated 2019-11-15

 DESCRIPTION                                           |   11 
 MD5                                                   |  227 +++--
 NEWS.md                                               |   23 
 R/children.R                                          |   11 
 R/classification.R                                    |   20 
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 R/comm2sci.R                                          |    8 
 R/downstream.R                                        |    5 
 R/genbank2uid.R                                       |    6 
 R/get_colid.R                                         |    7 
 R/get_ids.R                                           |   31 
 R/get_uid.R                                           |   11 
 R/id2name.R                                           |   13 
 R/lowest_common.R                                     |    1 
 R/ncbi_children.R                                     |   17 
 R/ncbi_get_taxon_summary.R                            |    7 
 R/onload.R                                            |only
 R/ping.R                                              |    6 
 R/sci2comm.R                                          |   11 
 R/synonyms.R                                          |    6 
 R/tax_agg.R                                           |    6 
 R/tax_rank.R                                          |    7 
 R/taxize-package.R                                    |    8 
 R/upstream.R                                          |    2 
 R/zzz.R                                               |   13 
 README.md                                             |    2 
 man/children.Rd                                       |    7 
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 man/col_search_paginate.Rd                            |    5 
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 man/get_colid.Rd                                      |    9 
 man/get_ids.Rd                                        |   15 
 man/get_uid.Rd                                        |    6 
 man/id2name.Rd                                        |    6 
 man/ncbi_children.Rd                                  |    6 
 man/ncbi_get_taxon_summary.Rd                         |    6 
 man/ping.Rd                                           |    6 
 man/progressor.Rd                                     |    2 
 man/sci2comm.Rd                                       |    6 
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 man/tax_rank.Rd                                       |    2 
 man/taxize-package.Rd                                 |   10 
 tests/fixtures/children_ambiguous_ncbi.yml            |only
 tests/fixtures/children_warn_on_db_mismatch.yml       |only
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 tests/testthat/Rplots.pdf                             |binary
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 tests/testthat/test-classification-pow.R              |    7 
 tests/testthat/test-classification.R                  |   14 
 tests/testthat/test-col_children.R                    |    2 
 tests/testthat/test-col_downstream.R                  |    2 
 tests/testthat/test-col_search.R                      |   22 
 tests/testthat/test-col_search_paginate.R             |   36 
 tests/testthat/test-comm2sci.R                        |   11 
 tests/testthat/test-downstream.R                      |   19 
 tests/testthat/test-eubon.R                           |    1 
 tests/testthat/test-fungorum.R                        |    5 
 tests/testthat/test-gbif_downstream.R                 |    3 
 tests/testthat/test-gbif_parse.R                      |    1 
 tests/testthat/test-get_boldid.R                      |    7 
 tests/testthat/test-get_colid.R                       |   10 
 tests/testthat/test-get_gbifid.R                      |    7 
 tests/testthat/test-get_ids.R                         |   14 
 tests/testthat/test-get_natservid.R                   |    4 
 tests/testthat/test-get_pow.R                         |    2 
 tests/testthat/test-get_tsn.R                         |    2 
 tests/testthat/test-get_wormsid.R                     |    5 
 tests/testthat/test-gni_details.R                     |    1 
 tests/testthat/test-gni_parse.R                       |    1 
 tests/testthat/test-gni_search.R                      |    1 
 tests/testthat/test-gnr_datasources.R                 |    1 
 tests/testthat/test-gnr_resolve.R                     |    4 
 tests/testthat/test-id2name.R                         |    9 
 tests/testthat/test-ion.R                             |    2 
 tests/testthat/test-ipni_search.R                     |    3 
 tests/testthat/test-itis_acceptname.R                 |    2 
 tests/testthat/test-itis_downstream.R                 |    3 
 tests/testthat/test-itis_getrecord.R                  |    1 
 tests/testthat/test-itis_hierarchy.R                  |    1 
 tests/testthat/test-itis_kingdomnames.R               |    3 
 tests/testthat/test-itis_lsid.R                       |    1 
 tests/testthat/test-itis_native.R                     |    1 
 tests/testthat/test-itis_ping.R                       |    2 
 tests/testthat/test-itis_refs.R                       |    1 
 tests/testthat/test-itis_taxrank.R                    |    1 
 tests/testthat/test-itis_terms.R                      |    1 
 tests/testthat/test-iucn_id.R                         |    1 
 tests/testthat/test-iucn_summary.R                    |    2 
 tests/testthat/test-lowest_common.R                   |    4 
 tests/testthat/test-ncbi_children.R                   |   18 
 tests/testthat/test-ping.R                            |   36 
 tests/testthat/test-plantminer.R                      |    2 
 tests/testthat/test-pow_search.R                      |    3 
 tests/testthat/test-sci2comm.R                        |    9 
 tests/testthat/test-synonyms.R                        |   13 
 tests/testthat/test-tax_agg.R                         |   10 
 tests/testthat/test-tax_name.R                        |    1 
 tests/testthat/test-tax_rank.R                        |    1 
 tests/testthat/test-tnrs.R                            |    2 
 tests/testthat/test-tnrs_sources.R                    |    1 
 tests/testthat/test-upstream.R                        |only
 tests/testthat/test-utils.R                           |only
 tests/testthat/test-vascan_search.r                   |    1 
 tests/testthat/test-worms_downstream.R                |    3 
 121 files changed, 1549 insertions(+), 452 deletions(-)

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Package sur updated to version 1.0.2 with previous version 1.0.1 dated 2019-11-14

Title: Companion to "Statistics Using R: An Integrative Approach"
Description: Access to the datasets and many of the functions used in "Statistics Using R: An Integrative Approach". These datasets include a subset of the National Education Longitudinal Study, the Framingham Heart Study, as well as several simulated datasets used in the examples throughout the textbook. The functions included in the package reproduce some of the functionality of 'Stata' that is not directly available in 'R'. The package also contains a tutorial on basic data frame management, including how to handle missing data.
Author: Daphna Harel [cre, aut], Sharon Weinberg [ctb], Sarah Abramowitz [ctb]
Maintainer: Daphna Harel <daphna.harel@gmail.com>

Diff between sur versions 1.0.1 dated 2019-11-14 and 1.0.2 dated 2019-11-15

 DESCRIPTION                           |    6 
 MD5                                   |    6 
 inst/tutorials/R_Basics/R_Basics.Rmd  |   22 +--
 inst/tutorials/R_Basics/R_Basics.html |  218 +++++++++++++++++-----------------
 4 files changed, 126 insertions(+), 126 deletions(-)

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New package reactable with initial version 0.1.0
Package: reactable
Type: Package
Title: Interactive Data Tables Based on 'React Table'
Version: 0.1.0
Authors@R: c( person("Greg", "Lin", email = "glin@glin.io", role = c("aut", "cre")), person("Tanner", "Linsley", role = c("ctb", "cph"), comment = "React Table library") )
Description: Interactive data tables for R, based on the 'React Table' JavaScript library. Provides an HTML widget that can be used in 'R Markdown' documents and 'Shiny' applications, or viewed from an R console.
License: MIT + file LICENSE
URL: https://glin.github.io/reactable, https://github.com/glin/reactable
BugReports: https://github.com/glin/reactable/issues
Depends: R (>= 3.1)
Imports: digest, htmltools, htmlwidgets, jsonlite, reactR
Suggests: covr, dplyr, rmarkdown, shiny, sparkline, testthat
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-11-10 22:14:16 UTC; greg
Author: Greg Lin [aut, cre], Tanner Linsley [ctb, cph] (React Table library)
Maintainer: Greg Lin <glin@glin.io>
Repository: CRAN
Date/Publication: 2019-11-15 12:00:05 UTC

More information about reactable at CRAN
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Package pathfindR updated to version 1.4.1 with previous version 1.4.0 dated 2019-11-08

Title: Enrichment Analysis Utilizing Active Subnetworks
Description: Enrichment analysis enables researchers to uncover mechanisms underlying a phenotype. However, conventional methods for enrichment analysis do not take into account protein-protein interaction information, resulting in incomplete conclusions. pathfindR is a tool for enrichment analysis utilizing active subnetworks. The main function identifies active subnetworks in a protein-protein interaction network using a user-provided list of genes and associated p values. It then performs enrichment analyses on the identified subnetworks, identifying enriched terms (i.e. pathways or, more broadly, gene sets) that possibly underlie the phenotype of interest. pathfindR also offers functionalities to cluster the enriched terms and identify representative terms in each cluster, to score the enriched terms per sample and to visualize analysis results. The enrichment, clustering and other methods implemented in pathfindR are described in detail in Ulgen E, Ozisik O, Sezerman OU. 2019. pathfindR: An R Package for Comprehensive Identification of Enriched Pathways in Omics Data Through Active Subnetworks. Front. Genet. <doi:10.3389/fgene.2019.00858>.
Author: Ege Ulgen [cre] (<https://orcid.org/0000-0003-2090-3621>), Ozan Ozisik [aut] (<https://orcid.org/0000-0001-5980-8002>)
Maintainer: Ege Ulgen <egeulgen@gmail.com>

Diff between pathfindR versions 1.4.0 dated 2019-11-08 and 1.4.1 dated 2019-11-15

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 NAMESPACE                                     |    1 
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 R/java_ver_check.R                            |only
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 inst/rmd/enriched_terms.Rmd                   |    8 +-
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 man/enrichment.Rd                             |   11 ++-
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 man/input_processing.Rd                       |    3 
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 man/plot_scores.Rd                            |   13 ++-
 man/run_pathfindR.Rd                          |   54 +++++++++++----
 man/score_terms.Rd                            |   10 ++
 man/summarize_enrichment_results.Rd           |    3 
 man/term_gene_graph.Rd                        |    9 ++
 man/visualize_hsa_KEGG.Rd                     |   17 ++++
 man/visualize_terms.Rd                        |    9 ++
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 tests/testthat/test-visualization_functions.R |   43 +++++++++++-
 vignettes/manual_execution.Rmd                |    2 
 43 files changed, 450 insertions(+), 221 deletions(-)

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Package ohtadstats updated to version 2.1.1 with previous version 2.1.0 dated 2019-03-18

Title: Tomoka Ohta D Statistics
Description: Calculate's Tomoka Ohta's partitioning of linkage disequilibrium, deemed D-statistics, for pairs of loci. Petrowski et al. (2019) <doi:10.5334/jors.250>.
Author: Paul F. Petrowski <pfpetrowski@gmail.com> & Timothy M. Beissinger <timbeissinger@gmail.com>
Maintainer: Paul F. Petrowski <pfpetrowski@gmail.com>

Diff between ohtadstats versions 2.1.0 dated 2019-03-18 and 2.1.1 dated 2019-11-15

 DESCRIPTION      |   14 +++++++-------
 MD5              |    6 +++---
 R/dparallel.R    |    7 +++++--
 man/dparallel.Rd |    2 +-
 4 files changed, 16 insertions(+), 13 deletions(-)

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New package chk with initial version 0.2.0
Package: chk
Title: Check User-Supplied Function Arguments
Version: 0.2.0
Authors@R: c( person("Joe", "Thorley", , "joe@poissonconsulting.ca", c("aut", "cre"), comment = c(ORCID = "0000-0002-7683-4592")), person("Kirill", "M\u00fcller", role = "aut", comment = c(ORCID = "0000-0002-1416-3412")), person("Ayla", "Pearson", role = "ctb", comment = c(ORCID = "0000-0001-7388-1222")), person("Poisson Consulting", role = c("cph", "fnd")) )
Description: For developers to check user-supplied function arguments. It is designed to be simple, fast and customizable. Error messages follow the tidyverse style guide.
License: MIT + file LICENSE
URL: https://github.com/poissonconsulting/chk
BugReports: https://github.com/poissonconsulting/chk/issues
Depends: R (>= 3.3)
Imports: lifecycle, methods, rlang, tools, utils
Suggests: covr, knitr, microbenchmark, rmarkdown, testthat
VignetteBuilder: knitr
RdMacros: lifecycle
Encoding: UTF-8
Language: en-US
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-11-06 17:26:16 UTC; joe
Author: Joe Thorley [aut, cre] (<https://orcid.org/0000-0002-7683-4592>), Kirill Müller [aut] (<https://orcid.org/0000-0002-1416-3412>), Ayla Pearson [ctb] (<https://orcid.org/0000-0001-7388-1222>), Poisson Consulting [cph, fnd]
Maintainer: Joe Thorley <joe@poissonconsulting.ca>
Repository: CRAN
Date/Publication: 2019-11-15 11:50:02 UTC

More information about chk at CRAN
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New package badger with initial version 0.0.7
Package: badger
Title: Badge for R Package
Version: 0.0.7
Authors@R: c( person("Guangchuang", "Yu", email = "guangchuangyu@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-6485-8781")), person("Gregor", "de Cillia", email = "de.cillia.gregor@gmail.com", role = "ctb"), person("Dirk", "Eddelbuettel", email = "edd@debian.org", role = "ctb"), person("Maëlle", "Salmon", role = "ctb"), person("Robrecht", "Cannoodt", email = "rcannood@gmail.com", role = "ctb", comment = c(ORCID = "0000-0003-3641-729X", github = "rcannood")) )
Description: Query information and generate badge for using in README and GitHub Pages.
Depends: R (>= 3.3.0)
Imports: dlstats, rvcheck, desc
License: Artistic-2.0
ByteCompile: true
URL: https://github.com/GuangchuangYu/badger
BugReports: https://github.com/GuangchuangYu/badger/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-11-14 04:33:40 UTC; ygc
Author: Guangchuang Yu [aut, cre] (<https://orcid.org/0000-0002-6485-8781>), Gregor de Cillia [ctb], Dirk Eddelbuettel [ctb], Maëlle Salmon [ctb], Robrecht Cannoodt [ctb] (<https://orcid.org/0000-0003-3641-729X>, rcannood)
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>
Repository: CRAN
Date/Publication: 2019-11-15 11:10:10 UTC

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Package AROC updated to version 1.0-1 with previous version 1.0 dated 2018-06-10

Title: Covariate-Adjusted Receiver Operating Characteristic Curve Inference
Description: Estimates the covariate-adjusted Receiver Operating Characteristic (AROC) curve and pooled (unadjusted) ROC curve by different methods. Inacio de Carvalho, V., and Rodriguez-Alvarez, M. X. (2018) <arXiv:1806.00473>.
Author: Maria Xose Rodriguez-Alvarez [aut, cre] (<https://orcid.org/0000-0002-1329-9238>), Vanda Inacio de Carvalho [aut] (<https://orcid.org/0000-0001-8084-1616>)
Maintainer: Maria Xose Rodriguez-Alvarez <mxrodriguez@bcamath.org>

Diff between AROC versions 1.0 dated 2018-06-10 and 1.0-1 dated 2019-11-15

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More information about AROC at CRAN
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Package corporaexplorer updated to version 0.7.0 with previous version 0.6.3 dated 2019-10-06

Title: A 'Shiny' App for Exploration of Text Collections
Description: Facilitates dynamic exploration of text collections through an intuitive graphical user interface. The package contains 1) a helper function to convert a data frame to a 'corporaexplorerobject', 2) a 'Shiny' app for fast and flexible exploration of a 'corporaexplorerobject', and 3) a 'Shiny' app for simple retrieval/extraction of documents from a 'corporaexplorerobject' in a reading-friendly format.
Author: Kristian Lundby Gjerde [aut, cre]
Maintainer: Kristian Lundby Gjerde <kristian.gjerde@gmail.com>

Diff between corporaexplorer versions 0.6.3 dated 2019-10-06 and 0.7.0 dated 2019-11-15

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Package kde1d updated to version 1.0.0 with previous version 0.4.0 dated 2019-04-11

Title: Univariate Kernel Density Estimation
Description: Provides an efficient implementation of univariate local polynomial kernel density estimators that can handle bounded and discrete data. See Geenens (2014) <arXiv:1303.4121>, Geenens and Wang (2018) <arXiv:1602.04862>, Nagler (2018a) <arXiv:1704.07457>, Nagler (2018b) <arXiv:1705.05431>.
Author: Thomas Nagler [aut, cre], Thibault Vatter [aut]
Maintainer: Thomas Nagler <mail@tnagler.com>

Diff between kde1d versions 0.4.0 dated 2019-04-11 and 1.0.0 dated 2019-11-15

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Package Rfast updated to version 1.9.6 with previous version 1.9.5 dated 2019-07-12

Title: A Collection of Efficient and Extremely Fast R Functions
Description: A collection of fast (utility) functions for data analysis. Column- and row- wise means, medians, variances, minimums, maximums, many t, F and G-square tests, many regressions (normal, logistic, Poisson), are some of the many fast functions. Reference: Tsagris M, Papadakis M. (2018). Taking R to its limits: 70+ tips. PeerJ Preprints 6:e26605v1 <doi:10.7287/peerj.preprints.26605v1>.
Author: Manos Papadakis, Michail Tsagris, Marios Dimitriadis, Stefanos Fafalios, Ioannis Tsamardinos, Matteo Fasiolo, Giorgos Borboudakis, John Burkardt, Changliang Zou, Kleanthi Lakiotaki and Christina Chatzipantsiou.
Maintainer: Manos Papadakis <rfastofficial@gmail.com>

Diff between Rfast versions 1.9.5 dated 2019-07-12 and 1.9.6 dated 2019-11-15

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More information about Rfast at CRAN
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Package glmnet updated to version 3.0-1 with previous version 3.0 dated 2019-11-09

Title: Lasso and Elastic-Net Regularized Generalized Linear Models
Description: Extremely efficient procedures for fitting the entire lasso or elastic-net regularization path for linear regression, logistic and multinomial regression models, Poisson regression and the Cox model. Two recent additions are the multiple-response Gaussian, and the grouped multinomial regression. The algorithm uses cyclical coordinate descent in a path-wise fashion, as described in the papers listed in the URL below.
Author: Jerome Friedman [aut], Trevor Hastie [aut, cre], Rob Tibshirani [aut], Balasubramanian Narasimhan [aut], Noah Simon [aut], Junyang Qian [ctb]
Maintainer: Trevor Hastie <hastie@stanford.edu>

Diff between glmnet versions 3.0 dated 2019-11-09 and 3.0-1 dated 2019-11-15

 DESCRIPTION         |   10 +++++-----
 MD5                 |   10 +++++-----
 NEWS.md             |    4 ++++
 inst/doc/Coxnet.pdf |binary
 inst/doc/glmnet.pdf |binary
 inst/doc/relax.pdf  |binary
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Permanent link

Package IRISMustangMetrics updated to version 2.3.0 with previous version 2.2.0 dated 2019-01-31

Title: Statistics and Metrics for Seismic Data
Description: Classes and functions for metrics calculation as part of the 'IRIS DMC MUSTANG' project. The functionality in this package builds upon the base classes of the 'IRISSeismic' package. Metrics include basic statistics as well as higher level 'health' metrics that can help identify problematic seismometers.
Author: Jonathan Callahan [aut], Rob Casey [aut], Mary Templeton [aut], Gillian Sharer [aut, cre]
Maintainer: Gillian Sharer <gillian@iris.washington.edu>

Diff between IRISMustangMetrics versions 2.2.0 dated 2019-01-31 and 2.3.0 dated 2019-11-15

 DESCRIPTION                       |    8 -
 MD5                               |   14 +-
 NAMESPACE                         |    1 
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 R/STALTAMetric.R                  |   14 +-
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 man/PSDMetric.Rd                  |    5 
 man/getSingleValueMetrics.Rd      |    2 
 8 files changed, 161 insertions(+), 113 deletions(-)

More information about IRISMustangMetrics at CRAN
Permanent link


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