Fri, 30 Jul 2021

Package RcppAnnoy updated to version 0.0.19 with previous version 0.0.18 dated 2020-12-15

Title: 'Rcpp' Bindings for 'Annoy', a Library for Approximate Nearest Neighbors
Description: 'Annoy' is a small C++ library for Approximate Nearest Neighbors written for efficient memory usage as well an ability to load from / save to disk. This package provides an R interface by relying on the 'Rcpp' package, exposing the same interface as the original Python wrapper to 'Annoy'. See <https://github.com/spotify/annoy> for more on 'Annoy'. 'Annoy' is released under Version 2.0 of the Apache License. Also included is a small Windows port of 'mmap' which is released under the MIT license.
Author: Dirk Eddelbuettel
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package bndovb updated to version 1.1 with previous version 1.0 dated 2021-06-21

Title: Bounding Omitted Variable Bias Using Auxiliary Data
Description: Functions to implement a Hwang(2021) <doi:10.2139/ssrn.3866876> estimator, which bounds an omitted variable bias using auxiliary data.
Author: Yujung Hwang [aut, cre] (<https://orcid.org/0000-0002-8136-8987>)
Maintainer: Yujung Hwang <yujungghwang@gmail.com>

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Package postcards updated to version 0.2.1 with previous version 0.2.0 dated 2021-01-06

Title: Create Beautiful, Simple Personal Websites
Description: A collection of R Markdown templates for creating simple and easy to personalize single page websites.
Author: Sean Kross [aut, cre] (<https://orcid.org/0000-0001-5215-0316>)
Maintainer: Sean Kross <sean@seankross.com>

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Package micemd updated to version 1.7.0 with previous version 1.6.0 dated 2019-07-09

Title: Multiple Imputation by Chained Equations with Multilevel Data
Description: Addons for the 'mice' package to perform multiple imputation using chained equations with two-level data. Includes imputation methods dedicated to sporadically and systematically missing values. Imputation of continuous, binary or count variables are available. Following the recommendations of Audigier, V. et al (2018) <doi:10.1214/18-STS646>, the choice of the imputation method for each variable can be facilitated by a default choice tuned according to the structure of the incomplete dataset. Allows parallel calculation and overimputation for 'mice'.
Author: Vincent Audigier [aut, cre] (CNAM MSDMA team), Matthieu Resche-Rigon [aut] (INSERM ECSTRA team)
Maintainer: Vincent Audigier <vincent.audigier@cnam.fr>

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Package AtmChile updated to version 0.1.2 with previous version 0.1.1 dated 2021-07-13

Title: Download Air Quality and Meteorological Information of Chile
Description: Download air quality and meteorological information of Chile from the National Air Quality System (S.I.N.C.A.)<https://sinca.mma.gob.cl/> dependent on the Ministry of the Environment and the Meteorological Directorate of Chile (D.M.C.)<http://www.meteochile.gob.cl/> dependent on the Directorate General of Civil Aeronautics.
Author: Francisco Catalan Meyer [aut, cre] (<https://orcid.org/0000-0003-3506-5376>), Manuel Leiva [aut] (<https://orcid.org/0000-0001-8891-0399>), Richard Toro [aut]
Maintainer: Francisco Catalan Meyer <francisco.catalan@ug.uchile.cl>

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Package dssd updated to version 0.3.0 with previous version 0.2.2 dated 2021-02-25

Title: Distance Sampling Survey Design
Description: Creates survey designs for distance sampling surveys. These designs can be assessed for various effort and coverage statistics. Once the user is satisfied with the design characteristics they can generate a set of transects to use in their distance sampling survey. Many of the designs implemented in this R package were first made available in our 'Distance' for Windows software and are detailed in Chapter 7 of Advanced Distance Sampling, Buckland et. al. (2008, ISBN-13: 978-0199225873). Find out more about estimating animal/plant abundance with distance sampling at <http://distancesampling.org/>.
Author: Laura Marshall [aut, cre], Rexstad Eric [ctb]
Maintainer: Laura Marshall <lhm@st-andrews.ac.uk>

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Package dataRetrieval updated to version 2.7.9 with previous version 2.7.8 dated 2021-06-26

Title: Retrieval Functions for USGS and EPA Hydrologic and Water Quality Data
Description: Collection of functions to help retrieve U.S. Geological Survey (USGS) and U.S. Environmental Protection Agency (EPA) water quality and hydrology data from web services. USGS web services are discovered from National Water Information System (NWIS) <https://waterservices.usgs.gov/> and <https://waterdata.usgs.gov/nwis>. Both EPA and USGS water quality data are obtained from the Water Quality Portal <https://www.waterqualitydata.us/>.
Author: Laura DeCicco [aut, cre] (<https://orcid.org/0000-0002-3915-9487>), Robert Hirsch [aut] (<https://orcid.org/0000-0002-4534-075X>), David Lorenz [aut], Jordan Read [ctb], Jordan Walker [ctb], Lindsay Carr [ctb], David Watkins [aut] (<https://orcid.org/0000-0002-7544-0700>), David Blodgett [ctb], Mike Johnson [aut] (<https://orcid.org/0000-0002-5288-8350>)
Maintainer: Laura DeCicco <ldecicco@usgs.gov>

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New package apsimx with initial version 1.998
Package: apsimx
Title: Inspect, Read, Edit and Run 'APSIM' "Next Generation" and 'APSIM' Classic
Version: 1.998
Description: The functions in this package inspect, read, edit and run files for 'APSIM' "Next Generation" ('JSON') and 'APSIM' "Classic" ('XML'). The files with an 'apsim' extension correspond to 'APSIM' Classic (7.x) - Windows only - and the ones with an 'apsimx' extension correspond to 'APSIM' "Next Generation". For more information about 'APSIM' see (<https://www.apsim.info/>) and for 'APSIM' next generation (<https://apsimnextgeneration.netlify.app/>).
Depends: R (>= 3.5.0)
License: GPL-3
Encoding: UTF-8
VignetteBuilder: knitr
BugReports: https://github.com/femiguez/apsimx/issues
Imports: DBI, jsonlite, knitr, RSQLite, tools, utils, xml2
Suggests: BayesianTools, datasets, daymetr, FedData, ggplot2, GSODR, listviewer, maps, mvtnorm, nasapower, nloptr, raster, reactR, rmarkdown, soilDB, sp, spData, sf
LazyData: true
NeedsCompilation: no
Packaged: 2021-07-29 19:45:55 UTC; fernandomiguez
Author: Fernando Miguez [aut, cre] (<https://orcid.org/0000-0002-4627-8329>)
Maintainer: Fernando Miguez <femiguez@iastate.edu>
Repository: CRAN
Date/Publication: 2021-07-30 15:00:06 UTC

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Package lidaRtRee updated to version 3.1.0 with previous version 3.0.2 dated 2021-04-10

Title: Forest Analysis with Airborne Laser Scanning (LiDAR) Data
Description: Provides functions for forest analysis using airborne laser scanning (LiDAR remote sensing) data: tree detection (method 1 in Eysn et al. (2015) <doi:10.3390/f6051721>) and segmentation; forest parameters estimation and mapping with the area-based approach. It includes complementary steps for forest mapping: co-registration of field plots with LiDAR data (Monnet and Mermin (2014) <doi:10.3390/f5092307>); extraction of both physical (gaps, edges, trees) and statistical features from LiDAR data useful for e.g. habitat suitability modeling (Glad et al. (2020) <doi:10.1002/rse2.117>); model calibration with ground reference, and maps export.
Author: Jean-Matthieu Monnet [aut, cre], Pascal Obstétar [ctb]
Maintainer: Jean-Matthieu Monnet <jean-matthieu.monnet@inrae.fr>

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New package iccCounts with initial version 1.0.3
Package: iccCounts
Title: Intraclass Correlation Coefficient for Count Data
Version: 1.0.3
Author: Josep L. Carrasco <jlcarrasco@ub.edu>
Maintainer: Josep L. Carrasco <jlcarrasco@ub.edu>
Depends: R (>= 4.0)
Imports: glmmTMB, ggplot2, Deriv, gridExtra, VGAM, dplyr
Suggests: knitr, rmarkdown
Description: Estimates the intraclass correlation coefficient (ICC) for count data to assess repeatability (intra-methods concordance) and concordance (between-method concordance). In the concordance setting, the ICC is equivalent to the concordance correlation coefficient estimated by variance components. The ICC is estimated using the estimates from generalized linear mixed models. The within-subjects distributions considered are: Poisson; Negative Binomial with additive and proportional extradispersion; Zero-Inflated Poisson; and Zero-Inflated Negative Binomial with additive and proportional extradispersion. The statistical methodology used to estimate the ICC with count data can be found in Carrasco (2010) <doi:10.1111/j.1541-0420.2009.01335.x>.
VignetteBuilder: knitr
Encoding: UTF-8
License: GPL (>= 2)
LazyData: true
NeedsCompilation: no
Packaged: 2021-07-30 08:12:59 UTC; hexac
Repository: CRAN
Date/Publication: 2021-07-30 13:00:02 UTC

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Package ThresholdROC updated to version 2.9.0 with previous version 2.8.3 dated 2020-09-28

Title: Optimum Threshold Estimation
Description: Functions that provide point and interval estimations of optimum thresholds for continuous diagnostic tests. The methodology used is based on minimizing an overall cost function in the two- and three-state settings. We also provide functions for sample size determination and estimation of diagnostic accuracy measures. We also include graphical tools. The statistical methodology used here can be found in Perez-Jaume et al (2017) <doi:10.18637/jss.v082.i04>.
Author: Sara Perez-Jaume, Natalia Pallares, Konstantina Skaltsa
Maintainer: Sara Perez-Jaume <spjaume@gmail.com>

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Package gimms updated to version 1.2.1 with previous version 1.2.0 dated 2021-04-16

Title: Download and Process GIMMS NDVI3g Data
Description: This is a set of functions to retrieve information about GIMMS NDVI3g files currently available online; download (and re-arrange, in the case of NDVI3g.v0) the half-monthly data sets; import downloaded files from ENVI binary (NDVI3g.v0) or NetCDF format (NDVI3g.v1) directly into R based on the widespread 'raster' package; conduct quality control; and generate monthly composites (e.g., maximum values) from the half-monthly input data. As a special gimmick, a method is included to conveniently apply the Mann-Kendall trend test upon 'Raster*' images, optionally featuring trend-free pre-whitening to account for lag-1 autocorrelation.
Author: Florian Detsch [cre, aut]
Maintainer: Florian Detsch <fdetsch@web.de>

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Package gginnards updated to version 0.1.0-1 with previous version 0.1.0 dated 2021-05-27

Title: Explore the Innards of 'ggplot2' Objects
Description: Extensions to 'ggplot2' providing low-level debug tools: statistics and geometries echoing their data argument. Layer manipulation: deletion, insertion, extraction and reordering of layers. Deletion of unused variables from the data object embedded in "ggplot" objects.
Author: Pedro J. Aphalo [aut, cre] (<https://orcid.org/0000-0003-3385-972X>)
Maintainer: Pedro J. Aphalo <pedro.aphalo@helsinki.fi>

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Package ADP updated to version 0.1.5 with previous version 0.1.3 dated 2021-07-28

Title: Adoption Probability, Triers and Users Rate of a New Product
Description: Calculate users prevalence of a product based on the prevalence of triers in the population. The measurement of triers is relatively easy. It is just a question of whether a person tried a product even once in his life or not. On the other hand, The measurement of people who also adopt it as part of their life is more complicated since adopting an innovative product is a subjective view of the individual. Mickey Kislev and Shira Kislev developed a formula to calculate the prevalence of a product's users to overcome this difficulty. The current package assists in calculating the users prevalence of a product based on the prevalence of triers in the population. See for: Kislev, M. M., and S. Kislev (2020) <doi:10.5539/ijms.v12n4p63>.
Author: Mickey Kislev [cre], Shira Kislev [aut]
Maintainer: Mickey Kislev <mickeykislev@researchgap.ac>

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Package openSkies updated to version 1.1.2 with previous version 1.1.1 dated 2021-04-17

Title: An R Package to Retrieve, Analyze and Visualize Air Traffic Data
Description: Provides functionalities and data structures to retrieve, analyze and visualize aviation data. It includes a client interface to the 'OpenSky' API <https://opensky-network.org>. It allows retrieval of flight information, as well as aircraft state vectors.
Author: Rafael Ayala, Daniel Ayala, David Ruiz, Aleix Sellés, Lara Sellés Vidal
Maintainer: Rafael Ayala <rafael.ayala@oist.jp>

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New package semtree with initial version 0.9.17
Package: semtree
Title: Recursive Partitioning for Structural Equation Models
Author: Andreas M. Brandmaier [aut, cre], John J. Prindle [aut], Manuel Arnold [aut]
Maintainer: Andreas M. Brandmaier <andy@brandmaier.de>
Depends: R (>= 2.10), OpenMx (>= 2.6.9),
Imports: bitops, sets, digest, rpart, rpart.plot (>= 3.0.6), plotrix, cluster, stringr, lavaan, ggplot2, tidyr, methods, strucchange, sandwich, zoo, crayon, clisymbols, future.apply
Suggests: knitr, rmarkdown, viridis, MASS, psychTools, testthat
Description: SEM Trees and SEM Forests -- an extension of model-based decision trees and forests to Structural Equation Models (SEM). SEM trees hierarchically split empirical data into homogeneous groups each sharing similar data patterns with respect to a SEM by recursively selecting optimal predictors of these differences. SEM forests are an extension of SEM trees. They are ensembles of SEM trees each built on a random sample of the original data. By aggregating over a forest, we obtain measures of variable importance that are more robust than measures from single trees. A description of the method was published by Brandmaier, von Oertzen, McArdle, & Lindenberger (2013; <doi:10.1037/a0030001>) and Arnold, Voelkle, & Brandmaier (2020; <doi:10.3389/fpsyg.2020.564403>).
License: GPL-3
Encoding: UTF-8
LazyLoad: yes
Version: 0.9.17
Date: 2021-07-27
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-07-29 17:27:37 UTC; brandmaier
Repository: CRAN
Date/Publication: 2021-07-30 08:10:02 UTC

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New package ndtv with initial version 0.13.1
Package: ndtv
Title: Network Dynamic Temporal Visualizations
Version: 0.13.1
Date: 2021-07-29
Depends: R (>= 3.0), network (>= 1.13),networkDynamic (>= 0.9),animation (>= 2.4),sna
Imports: MASS, statnet.common, jsonlite, base64
Suggests: tergm (>= 3.6), tsna, testthat, knitr, htmlwidgets, scatterplot3d
Description: Renders dynamic network data from 'networkDynamic' objects as movies, interactive animations, or other representations of changing relational structures and attributes.
License: GPL-3 + file LICENSE
URL: https://github.com/statnet/ndtv
NeedsCompilation: no
Packaged: 2021-07-30 05:27:59 UTC; skyebend
Author: Skye Bender-deMoll [cre, aut], Martina Morris [ctb]
Maintainer: Skye Bender-deMoll <skyebend@uw.edu>
Repository: CRAN
Date/Publication: 2021-07-30 08:20:02 UTC

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New package mvoutlier with initial version 2.1.1
Package: mvoutlier
Version: 2.1.1
Date: 2021-07-29
Title: Multivariate Outlier Detection Based on Robust Methods
Author: Peter Filzmoser <P.Filzmoser@tuwien.ac.at> and Moritz Gschwandtner <e0125439@student.tuwien.ac.at>
Maintainer: P. Filzmoser <P.Filzmoser@tuwien.ac.at>
Depends: sgeostat, R (>= 3.1)
Imports: robustbase
Description: Various methods for multivariate outlier detection: arw, a Mahalanobis-type method with an adaptive outlier cutoff value; locout, a method incorporating local neighborhood; pcout, a method for high-dimensional data; mvoutlier.CoDa, a method for compositional data. References are provided in the corresponding help files.
LazyData: TRUE
License: GPL (>= 3)
URL: http://cstat.tuwien.ac.at/filz/
Packaged: 2021-07-29 17:14:43 UTC; filz
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2021-07-30 08:10:05 UTC

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New package mcvis with initial version 1.0.8
Package: mcvis
Title: Multi-Collinearity Visualization
Version: 1.0.8
Description: Visualize the relationship between linear regression variables and causes of multi-collinearity. Implements the method in Lin et. al. (2020) <doi:10.1080/10618600.2020.1779729>.
Encoding: UTF-8
Imports: assertthat, igraph, ggplot2, purrr, magrittr, reshape2, shiny, dplyr, psych, rlang
License: GPL-3
Suggests: testthat (>= 2.1.0), covr, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-07-30 02:56:36 UTC; kevinwang
Author: Kevin Wang [aut, cre], Chen Lin [aut], Samuel Mueller [aut]
Maintainer: Kevin Wang <kevin.wang09@gmail.com>
Repository: CRAN
Date/Publication: 2021-07-30 08:20:05 UTC

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Package graphsim updated to version 1.0.2 with previous version 1.0.1 dated 2020-07-17

Title: Simulate Expression Data from 'igraph' Networks
Description: Functions to develop simulated continuous data (e.g., gene expression) from a sigma covariance matrix derived from a graph structure in 'igraph' objects. Intended to extend 'mvtnorm' to take 'igraph' structures rather than sigma matrices as input. This allows the use of simulated data that correctly accounts for pathway relationships and correlations. This allows the use of simulated data that correctly accounts for pathway relationships and correlations. Here we present a versatile statistical framework to simulate correlated gene expression data from biological pathways, by sampling from a multivariate normal distribution derived from a graph structure. This package allows the simulation of biological pathways from a graph structure based on a statistical model of gene expression. For example methods to infer biological pathways and gene regulatory networks from gene expression data can be tested on simulated datasets using this framework. This also allows for pathway structures to be considered as a confounding variable when simulating gene expression data to test the performance of genomic analyses.
Author: S. Thomas Kelly [aut, cre], Michael A. Black [aut, ths], Robrecht Cannoodt [ctb], Jason Cory Brunson [ctb]
Maintainer: S. Thomas Kelly <tomkellygenetics@gmail.com>

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Package cmfrec updated to version 3.2.2 with previous version 3.2.1 dated 2021-07-29

Title: Collective Matrix Factorization for Recommender Systems
Description: Collective matrix factorization (a.k.a. multi-view or multi-way factorization, Singh, Gordon, (2008) <doi:10.1145/1401890.1401969>) tries to approximate a matrix 'X' as the product of two low-dimensional matrices aided with secondary information matrices about rows and/or columns of 'X' which are also factorized using the same latent components. The intended usage is for recommender systems, dimensionality reduction, and missing value imputation. Implements extensions of the original model (Cortes, (2018) <arXiv:1809.00366>) and can produce different factorizations such as the weighted 'implicit-feedback' model (Hu, Koren, Volinsky, (2008) <doi:10.1109/ICDM.2008.22>), the 'weighted-lambda-regularization' model, (Zhou, Wilkinson, Schreiber, Pan, (2008) <doi:10.1007/978-3-540-68880-8_32>), or the enhanced model with 'implicit features' (Rendle, Zhang, Koren, (2019) <arXiv:1905.01395>), with or without side information. Can use gradient-based procedures or alternating-least squares procedures (Koren, Bell, Volinsky, (2009) <doi:10.1109/MC.2009.263>), with either a Cholesky solver, a faster conjugate gradient solver (Takacs, Pilaszy, Tikk, (2011) <doi:10.1145/2043932.2043987>), or a non-negative coordinate descent solver (Franc, Hlavac, Navara, (2005) <doi:10.1007/11556121_50>), providing efficient methods for sparse and dense data, and mixtures thereof. Supports L1 and L2 regularization in the main models, offers alternative most-popular and content-based models, and implements functionality for cold-start recommendations and imputation of 2D data.
Author: David Cortes [aut, cre, cph], Jorge Nocedal [cph] (Copyright holder of included LBFGS library), Naoaki Okazaki [cph] (Copyright holder of included LBFGS library), David Blackman [cph] (Copyright holder of original Xoshiro code), Sebastiano Vigna [cph] (Copyright holder of original Xoshiro code)
Maintainer: David Cortes <david.cortes.rivera@gmail.com>

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Package iForecast updated to version 1.0.3 with previous version 1.0.2 dated 2021-02-21

Title: Machine Learning Time Series Forecasting
Description: Compute both static and recursive time series forecasts of machine learning models.
Author: Ho Tsung-wu
Maintainer: Ho Tsung-wu <tsungwu@ntnu.edu.tw>

Diff between iForecast versions 1.0.2 dated 2021-02-21 and 1.0.3 dated 2021-07-30

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Package ggrisk (with last version 1.2) was removed from CRAN

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

2020-08-10 1.2
2020-02-09 1.0

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Package fastStat (with last version 1.4) was removed from CRAN

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

2020-09-17 1.4
2019-11-22 1.3

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Package SC.MEB (with last version 1.0) was removed from CRAN

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

2021-07-16 1.0

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Package emayili updated to version 0.4.15 with previous version 0.4.12 dated 2021-07-13

Title: Send Email Messages
Description: A light, simple tool for sending emails with minimal dependencies.
Author: Andrew B. Collier [aut, cre], Matt Dennis [ctb], Antoine Bichat [ctb] (<https://orcid.org/0000-0001-6599-7081>), Daniel Fahey [ctb], Johann R. Kleinbub [ctb], Panagiotis Moulos [ctb]
Maintainer: Andrew B. Collier <andrew.b.collier@gmail.com>

Diff between emayili versions 0.4.12 dated 2021-07-13 and 0.4.15 dated 2021-07-30

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More information about emayili at CRAN
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Package UCSCXenaShiny updated to version 1.1.1 with previous version 1.1.0 dated 2021-07-16

Title: Interactive Analysis of UCSC Xena Data
Description: Provides functions and a Shiny application for downloading, analyzing and visualizing datasets from UCSC Xena (<http://xena.ucsc.edu/>), which is a collection of UCSC-hosted public databases such as TCGA, ICGC, TARGET, GTEx, CCLE, and others.
Author: Shixiang Wang [aut, cre] (<https://orcid.org/0000-0001-9855-7357>), Yi Xiong [aut] (<https://orcid.org/0000-0002-4370-9824>), Longfei Zhao [aut] (<https://orcid.org/0000-0002-6277-0137>), Kai Gu [aut] (<https://orcid.org/0000-0002-0177-0774>), Yin Li [aut], Fei Zhao [aut]
Maintainer: Shixiang Wang <w_shixiang@163.com>

Diff between UCSCXenaShiny versions 1.1.0 dated 2021-07-16 and 1.1.1 dated 2021-07-30

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More information about UCSCXenaShiny at CRAN
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Package RawHummus updated to version 0.1.5 with previous version 0.1.0 dated 2021-07-19

Title: Raw Data Quality Control Tool for LC-MS System
Description: Assess LC–MS system performance by visualizing instrument log files and monitoring raw quality control samples within a project.
Author: Yonghui Dong
Maintainer: Yonghui Dong <yonghui.dong@gmail.com>

Diff between RawHummus versions 0.1.0 dated 2021-07-19 and 0.1.5 dated 2021-07-30

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More information about RawHummus at CRAN
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Package logr updated to version 1.2.5 with previous version 1.2.4 dated 2021-06-16

Title: Creates Log Files
Description: Contains functions to help create log files. The package aims to overcome the difficulty of the base R sink() command. The log_print() function will print to both the console and the file log, without interfering in other write operations.
Author: David Bosak [aut, cre]
Maintainer: David Bosak <dbosak01@gmail.com>

Diff between logr versions 1.2.4 dated 2021-06-16 and 1.2.5 dated 2021-07-30

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More information about logr at CRAN
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Package epiR updated to version 2.0.33 with previous version 2.0.31 dated 2021-07-19

Title: Tools for the Analysis of Epidemiological Data
Description: Tools for the analysis of epidemiological and surveillance data. Contains functions for directly and indirectly adjusting measures of disease frequency, quantifying measures of association on the basis of single or multiple strata of count data presented in a contingency table, computation of confidence intervals around incidence risk and incidence rate estimates and sample size calculations for cross-sectional, case-control and cohort studies. Surveillance tools include functions to calculate an appropriate sample size for 1- and 2-stage representative freedom surveys, functions to estimate surveillance system sensitivity and functions to support scenario tree modelling analyses.
Author: Mark Stevenson <mark.stevenson1@unimelb.edu.au> and Evan Sergeant <evansergeant@gmail.com> with contributions from Telmo Nunes, Cord Heuer, Jonathon Marshall, Javier Sanchez, Ron Thornton, Jeno Reiczigel, Jim Robison-Cox, Paola Sebastiani, Peter Solymos, Kazuki Yoshida, Geoff Jones, Sarah Pirikahu, Simon Firestone, Ryan Kyle, Johann Popp, Mathew Jay, Charles Reynard, Allison Cheung and Nagendra Singanallur.
Maintainer: Mark Stevenson <mark.stevenson1@unimelb.edu.au>

Diff between epiR versions 2.0.31 dated 2021-07-19 and 2.0.33 dated 2021-07-30

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More information about epiR at CRAN
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Package echarty updated to version 0.3.1 with previous version 0.2.0 dated 2021-06-13

Title: Minimal R/Shiny Interface to JavaScript Library 'ECharts'
Description: The goal is to deliver the full functionality of 'ECharts' with minimal overhead. 'ECharts' is based on data structures and 'echarty' users build R lists for these same data structures. One to three 'echarty' commands are usually sufficient to produce any chart.
Author: Larry Helgason [aut, cre, cph], John Coene [aut, cph]
Maintainer: Larry Helgason <larry@helgasoft.com>

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Package dlookr updated to version 0.5.0 with previous version 0.4.5 dated 2021-05-29

Title: Tools for Data Diagnosis, Exploration, Transformation
Description: A collection of tools that support data diagnosis, exploration, and transformation. Data diagnostics provides information and visualization of missing values and outliers and unique and negative values to help you understand the distribution and quality of your data. Data exploration provides information and visualization of the descriptive statistics of univariate variables, normality tests and outliers, correlation of two variables, and relationship between target variable and predictor. Data transformation supports binning for categorizing continuous variables, imputates missing values and outliers, resolving skewness. And it creates automated reports that support these three tasks.
Author: Choonghyun Ryu [aut, cre]
Maintainer: Choonghyun Ryu <choonghyun.ryu@gmail.com>

Diff between dlookr versions 0.4.5 dated 2021-05-29 and 0.5.0 dated 2021-07-30

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 dlookr-0.5.0/dlookr/DESCRIPTION                                                         |   18 
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 dlookr-0.5.0/dlookr/NEWS                                                                |   57 
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 dlookr-0.5.0/dlookr/inst/report/dlookr.svg                                              |only
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 dlookr-0.5.0/dlookr/inst/report/eda_temp.Rmd                                            |only
 dlookr-0.5.0/dlookr/inst/report/header_temp.html                                        |only
 dlookr-0.5.0/dlookr/inst/report/transformation_paged_temp.Rmd                           |only
 dlookr-0.5.0/dlookr/inst/report/transformation_temp.Rmd                                 |only
 dlookr-0.5.0/dlookr/inst/resources                                                      |only
 dlookr-0.5.0/dlookr/man/describe.data.frame.Rd                                          |   12 
 dlookr-0.5.0/dlookr/man/describe.tbl_dbi.Rd                                             |   18 
 dlookr-0.5.0/dlookr/man/diagnose_category.data.frame.Rd                                 |    6 
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 dlookr-0.5.0/dlookr/man/diagnose_paged_report.tbl_dbi.Rd                                |only
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 dlookr-0.5.0/dlookr/man/diagnose_web_report.tbl_dbi.Rd                                  |only
 dlookr-0.5.0/dlookr/man/dlookr_orange_paged.Rd                                          |only
 dlookr-0.5.0/dlookr/man/dlookr_templ_html.Rd                                            |only
 dlookr-0.5.0/dlookr/man/eda_paged_report.data.frame.Rd                                  |only
 dlookr-0.5.0/dlookr/man/eda_paged_report.tbl_dbi.Rd                                     |only
 dlookr-0.5.0/dlookr/man/eda_web_report.data.frame.Rd                                    |only
 dlookr-0.5.0/dlookr/man/eda_web_report.tbl_dbi.Rd                                       |only
 dlookr-0.5.0/dlookr/man/find_class.Rd                                                   |    7 
 dlookr-0.5.0/dlookr/man/overview.Rd                                                     |   15 
 dlookr-0.5.0/dlookr/man/plot.optimal_bins.Rd                                            |    8 
 dlookr-0.5.0/dlookr/man/plot_box_numeric.data.frame.Rd                                  |    6 
 dlookr-0.5.0/dlookr/man/plot_hist_numeric.data.frame.Rd                                 |only
 dlookr-0.5.0/dlookr/man/plot_na_pareto.Rd                                               |    4 
 dlookr-0.5.0/dlookr/man/summary.overview.Rd                                             |    5 
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 dlookr-0.5.0/dlookr/man/transformation_web_report.Rd                                    |only
 dlookr-0.5.0/dlookr/vignettes/EDA.Rmd                                                   |  289 ++---
 dlookr-0.5.0/dlookr/vignettes/diagonosis.Rmd                                            |  240 ++--
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 dlookr-0.5.0/dlookr/vignettes/introduce.Rmd                                             |    9 
 dlookr-0.5.0/dlookr/vignettes/transformation.Rmd                                        |  163 ++
 102 files changed, 3022 insertions(+), 1469 deletions(-)

More information about dlookr at CRAN
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Built and running on Debian GNU/Linux using R, littler and blosxom. Styled with Bootstrap.