Tue, 16 Apr 2019

Package SPUTNIK updated to version 1.1.2 with previous version 1.1.1 dated 2018-10-25

Title: SPatially aUTomatic deNoising for Ims toolKit
Description: A set of tools for the peak filtering of mass spectrometry imaging data (MSI or IMS) based on spatial distribution of signal. Given a region-of-interest (ROI), representing the spatial region where the informative signal is expected to be localized, a series of filters determine which peak signals are characterized by an implausible spatial distribution. The filters reduce the dataset dimensionality and increase its information vs noise ratio, improving the quality of the unsupervised analysis results, reducing data dimensionality and simplifying the chemical interpretation.
Author: Paolo Inglese [aut, cre], Goncalo Correia [aut, ctb]
Maintainer: Paolo Inglese <p.inglese14@imperial.ac.uk>

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Package discSurv updated to version 1.4.0 with previous version 1.3.4 dated 2018-08-01

Title: Discrete Time Survival Analysis
Description: Provides data transformations, estimation utilities, predictive evaluation measures and simulation functions for discrete time survival analysis.
Author: Thomas Welchowski <welchow@imbie.meb.uni-bonn.de> and Matthias Schmid <matthias.schmid@imbie.uni-bonn.de>
Maintainer: Thomas Welchowski <welchow@imbie.meb.uni-bonn.de>

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Package statVisual updated to version 1.0.9 with previous version 1.0.5 dated 2019-03-15

Title: Statistical Visualization Tools
Description: Visualization functions in the applications of translational medicine (TM) and biomarker (BM) development to compare groups by statistically visualizing data and/or results of analyses, such as visualizing data by displaying in one figure different groups' histograms, boxplots, densities, scatter plots, error-bar plots, or trajectory plots, by displaying scatter plots of top principal components or dendrograms with data points colored based on group information, or visualizing volcano plots to check the results of whole genome analyses for gene differential expression.
Author: Wenfei Zhang [aut, cre], Weiliang Qiu [aut, ctb], Xuan Lin [aut, ctb], Donghui Zhang [aut, ctb]
Maintainer: Wenfei Zhang <Wenfei.Zhang@sanofi.com>

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Package pct updated to version 0.1.2 with previous version 0.1.1 dated 2019-03-29

Title: Propensity to Cycle Tool
Description: Functions and example data to teach and increase the reproducibility of the methods and code underlying the Propensity to Cycle Tool (PCT), a research project and web application hosted at <https://www.pct.bike/>. For an academic paper on the methods, see Lovelace et al (2017) <doi:10.5198/jtlu.2016.862>.
Author: Robin Lovelace [aut, cre] (<https://orcid.org/0000-0001-5679-6536>), Layik Hama [aut] (<https://orcid.org/0000-0003-1912-4890>)
Maintainer: Robin Lovelace <rob00x@gmail.com>

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Package tuneRanger updated to version 0.5 with previous version 0.4 dated 2019-01-22

Title: Tune Random Forest of the 'ranger' Package
Description: Tuning random forest with one line. The package is mainly based on the packages 'ranger' and 'mlrMBO'.
Author: Philipp Probst [aut, cre], Simon Klau [ctb]
Maintainer: Philipp Probst <philipp_probst@gmx.de>

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Package traitdataform updated to version 0.5.3 with previous version 0.5.2 dated 2018-12-30

Title: Formatting and Harmonizing Ecological Trait-Data
Description: Assistance for handling ecological trait data and applying the Ecological Trait-Data Standard terminology (Schneider et al. 2018 <doi:10.1101/328302>). There are two major use cases: (1) preparation of own trait datasets for upload into public data bases, and (2) harmonizing trait datasets from different sources by re-formatting them into a unified format. See 'traitdataform' website for full documentation.
Author: Florian D. Schneider [aut, cre] (<https://orcid.org/0000-0002-1494-5684>), Caterina Penone [ctb] (<https://orcid.org/0000-0002-8170-6659>), Andreas Ostrowski [ctb] (<https://orcid.org/0000-0002-2033-779X>), Dennis Heimann [ctb], Felix Neff [ctb], Markus J. Ankenbrand [ctb]
Maintainer: Florian D. Schneider <florian.dirk.schneider@gmail.com>

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Package tidytransit updated to version 0.4.0 with previous version 0.3.8 dated 2019-03-04

Title: Read, Validate, Analyze, and Map Files in the General Transit Feed Specification
Description: Read General Transit Feed Specification (GTFS) zipfiles into a list of R dataframes. Perform validation of the data structure against the specification. Analyze the headways and frequencies at routes and stops. Create maps and perform spatial analysis on the routes and stops. Please see the GTFS documentation here for more detail: <http://gtfs.org/>.
Author: Tom Buckley [aut, cre], Flavio Poletti [aut], Danton Noriega-Goodwin [aut], Mark Padgham [aut], Angela Li [ctb], Elaine McVey [ctb], Charles Hans Thompson [ctb], Michael Sumner [ctb], Patrick Hausmann [ctb], Bob Rudis [ctb], Kearey Smith [ctb], Dave Vautin [ctb], Kyle Walker [ctb]
Maintainer: Tom Buckley <tom@tbuckl.com>

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Package TCIApathfinder updated to version 1.0.5 with previous version 1.0.4 dated 2019-03-21

Title: Client for the Cancer Imaging Archive REST API
Description: A wrapper for The Cancer Imaging Archive's REST API. The Cancer Imaging Archive (TCIA) hosts de-identified medical images of cancer available for public download, as well as rich metadata for each image series. TCIA provides a REST API for programmatic access to the data. This package provides simple functions to access each API endpoint. For more information, see <https://github.com/pamelarussell/TCIApathfinder> and TCIA's website.
Author: Pamela Russell [aut, cre]
Maintainer: Pamela Russell <pamela.russell@gmail.com>

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Package radtools updated to version 1.0.5 with previous version 1.0.4 dated 2019-03-13

Title: Utilities for Convenient Extraction of Medical Image Metadata
Description: A collection of utilities for navigating medical image data. The DICOM and NIfTI formats are supported. Functions provide simple interfaces to the data and metadata contained in these formats. A particular emphasis on metadata allows simple conversion of image metadata to familiar R data structures such as lists and data frames. Where possible, generic functions can silently process either DICOM or NIfTI data. Additionally, image data can be extracted and viewed.
Author: Pamela Russell [aut, cre]
Maintainer: Pamela Russell <pamela.russell@gmail.com>

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Package geostatsp updated to version 1.7.8 with previous version 1.7.7 dated 2019-03-06

Title: Geostatistical Modelling with Likelihood and Bayes
Description: Geostatistical modelling facilities using Raster and SpatialPoints objects are provided. Non-Gaussian models are fit using INLA, and Gaussian geostatistical models use Maximum Likelihood Estimation. For details see Brown (2015) <doi:10.18637/jss.v063.i12>.
Author: Patrick Brown <patrick.brown@utoronto.ca>[aut, cre], Robert Hijmans [ctb]
Maintainer: Patrick Brown <patrick.brown@utoronto.ca>

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Package catnet updated to version 1.15.5 with previous version 1.15.3 dated 2017-10-26

Title: Categorical Bayesian Network Inference
Description: Structure learning and parameter estimation of discrete Bayesian networks using likelihood-based criteria. Exhaustive search for fixed node orders and stochastic search of optimal orders via simulated annealing algorithm are implemented.
Author: Nikolay Balov, Peter Salzman
Maintainer: Nikolay Balov <nhbalov@gmail.com>

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Package BART updated to version 2.4 with previous version 2.3 dated 2019-03-28

Title: Bayesian Additive Regression Trees
Description: Bayesian Additive Regression Trees (BART) provide flexible nonparametric modeling of covariates for continuous, binary, categorical and time-to-event outcomes. For more information on BART, see Chipman, George and McCulloch (2010) <doi:10.1214/09-AOAS285> and Sparapani, Logan, McCulloch and Laud (2016) <doi:10.1002/sim.6893>.
Author: Robert McCulloch [aut], Rodney Sparapani [aut, cre], Robert Gramacy [aut], Charles Spanbauer [aut], Matthew Pratola [aut], Martyn Plummer [ctb], Nicky Best [ctb], Kate Cowles [ctb], Karen Vines [ctb]
Maintainer: Rodney Sparapani <rsparapa@mcw.edu>

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Package survtmle updated to version 1.1.1 with previous version 1.1.0 dated 2018-04-13

Title: Compute Targeted Minimum Loss-Based Estimates in Right-Censored Survival Settings
Description: Targeted estimates of marginal cumulative incidence in survival settings with and without competing risks, including estimators that respect bounds (Benkeser, Carone, and Gilbert. Statistics in Medicine, 2017. <doi:10.1002/sim.7337>).
Author: David Benkeser [aut, cre, cph] (<https://orcid.org/0000-0002-1019-8343>), Nima Hejazi [aut] (<https://orcid.org/0000-0002-7127-2789>)
Maintainer: David Benkeser <benkeser@emory.edu>

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Package BMSC updated to version 0.2.0 with previous version 0.1.1 dated 2018-10-18

Title: Bayesian Model Selection under Constraints
Description: A Bayesian regression package supporting constrained coefficient estimation and variable selection using Stan. This includes a robust variable selection algorithm by a horseshoe prior (<doi:10.1093/biomet/asq017>) that finds the optimal model considering main effects, interactions as well as powers of given variables under potential parameter constraints.
Author: Marcus Groß [aut, cre], Ricardo Fernandes [aut], Mira Celine Klein [ctb]
Maintainer: Marcus Groß <marcus.gross@inwt-statistics.de>

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Package PTXQC updated to version 0.92.6 with previous version 0.92.5 dated 2019-03-15

Title: Quality Report Generation for MaxQuant Results
Description: Generates Proteomics (PTX) quality control (QC) reports for shotgun LC-MS data analyzed with the MaxQuant software suite. Reports are customizable (target thresholds, subsetting) and available in HTML or PDF format. Published in J. Proteome Res., Proteomics Quality Control: Quality Control Software for MaxQuant Results (2015) 'doi:10.1021/acs.jproteome.5b00780'.
Author: Chris Bielow <chris.bielow@bsc.fu-berlin.de>
Maintainer: Chris Bielow <chris.bielow@bsc.fu-berlin.de>

Diff between PTXQC versions 0.92.5 dated 2019-03-15 and 0.92.6 dated 2019-04-16

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Package tsfeatures updated to version 1.0.1 with previous version 1.0.0 dated 2019-02-06

Title: Time Series Feature Extraction
Description: Methods for extracting various features from time series data. The features provided are those from Hyndman, Wang and Laptev (2013) <doi:10.1109/ICDMW.2015.104>, Kang, Hyndman and Smith-Miles (2017) <doi:10.1016/j.ijforecast.2016.09.004> and from Fulcher, Little and Jones (2013) <doi:10.1098/rsif.2013.0048>. Features include spectral entropy, autocorrelations, measures of the strength of seasonality and trend, and so on. Users can also define their own feature functions.
Author: Rob Hyndman [aut, cre] (<https://orcid.org/0000-0002-2140-5352>), Yanfei Kang [aut] (<https://orcid.org/0000-0001-8769-6650>), Pablo Montero-Manso [aut], Thiyanga Talagala [aut] (<https://orcid.org/0000-0002-0656-9789>), Earo Wang [aut] (<https://orcid.org/0000-0001-6448-5260>), Yangzhuoran Yang [aut], Mitchell O'Hara-Wild [aut] (<https://orcid.org/0000-0001-6729-7695>), Souhaib Ben Taieb [ctb], Cao Hanqing [ctb], D K Lake [ctb], Nikolay Laptev [ctb], J R Moorman [ctb]
Maintainer: Rob Hyndman <Rob.Hyndman@monash.edu>

Diff between tsfeatures versions 1.0.0 dated 2019-02-06 and 1.0.1 dated 2019-04-16

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Package forecast updated to version 8.6 with previous version 8.5 dated 2019-01-18

Title: Forecasting Functions for Time Series and Linear Models
Description: Methods and tools for displaying and analysing univariate time series forecasts including exponential smoothing via state space models and automatic ARIMA modelling.
Author: Rob Hyndman [aut, cre, cph] (<https://orcid.org/0000-0002-2140-5352>), George Athanasopoulos [aut], Christoph Bergmeir [aut] (<https://orcid.org/0000-0002-3665-9021>), Gabriel Caceres [aut], Leanne Chhay [aut], Mitchell O'Hara-Wild [aut] (<https://orcid.org/0000-0001-6729-7695>), Fotios Petropoulos [aut] (<https://orcid.org/0000-0003-3039-4955>), Slava Razbash [aut], Earo Wang [aut], Farah Yasmeen [aut] (<https://orcid.org/0000-0002-1479-5401>), R Core Team [ctb, cph], Ross Ihaka [ctb, cph], Daniel Reid [ctb], David Shaub [ctb], Yuan Tang [ctb] (<https://orcid.org/0000-0001-5243-233X>), Zhenyu Zhou [ctb]
Maintainer: Rob Hyndman <Rob.Hyndman@monash.edu>

Diff between forecast versions 8.5 dated 2019-01-18 and 8.6 dated 2019-04-16

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Package cdcsis updated to version 2.0.1 with previous version 2.0.0 dated 2019-01-09

Title: Conditional Distance Correlation Based Feature Screening and Conditional Independence Inference
Description: Conditional distance correlation <doi:10.1080/01621459.2014.993081> is a novel conditional dependence measurement of two multivariate random variables given a confounding variable. This package provides conditional distance correlation, performs the conditional distance correlation sure independence screening procedure for ultrahigh dimensional data <doi:10.5705/ss.202014.0117>, and conducts conditional distance covariance test for conditional independence assumption of two multivariate variable.
Author: Wenhao Hu, Mian Huang, Wenliang Pan, Xueqin Wang, Canhong Wen, Yuan Tian, Heping Zhang, Jin Zhu
Maintainer: Jin Zhu <zhuj37@mail2.sysu.edu.cn>

Diff between cdcsis versions 2.0.0 dated 2019-01-09 and 2.0.1 dated 2019-04-16

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Package BoolNet updated to version 2.1.5 with previous version 2.1.4 dated 2018-06-07

Title: Construction, Simulation and Analysis of Boolean Networks
Description: Provides methods to reconstruct and generate synchronous, asynchronous, probabilistic and temporal Boolean networks, and to analyze and visualize attractors in Boolean networks.
Author: Christoph Müssel [aut], Martin Hopfensitz [aut], Dao Zhou [aut], Hans A. Kestler [aut, cre], Armin Biere [ctb] (contributed PicoSAT code), Troy D. Hanson [ctb] (contributed uthash macros)
Maintainer: Hans A. Kestler <hans.kestler@uni-ulm.de>

Diff between BoolNet versions 2.1.4 dated 2018-06-07 and 2.1.5 dated 2019-04-16

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New package holodeck with initial version 0.2.0
Package: holodeck
Title: A Tidy Interface for Simulating Multivariate Data
Version: 0.2.0
Authors@R: person(given = "Eric", family = "Scott", role = c("aut", "cre"), email = "scottericr@gmail.com")
Description: Provides pipe-friendly (%>%) functions to create simulated multivariate data sets with groups of variables with different degrees of variance, covariance, and effect size.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
biocViews:
Imports: dplyr, tibble, MASS, purrr, rlang, assertthat
RoxygenNote: 6.1.1
URL: https://github.com/Aariq/holodeck
BugReports: https://github.com/Aariq/holodeck/issues
Suggests: testthat, covr, knitr, rmarkdown, iheatmapr, mice, ropls, ggplot2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-15 19:56:19 UTC; scottericr
Author: Eric Scott [aut, cre]
Maintainer: Eric Scott <scottericr@gmail.com>
Repository: CRAN
Date/Publication: 2019-04-16 12:12:40 UTC

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New package HDMT with initial version 1.0
Package: HDMT
Type: Package
Title: A Multiple Testing Procedure for High-Dimensional Mediation Hypotheses
Version: 1.0
Date: 2019-04-07
Authors@R: c(person("James", "Dai", role = c("aut", "cre"), email = "jdai@fredhutch.org"), person("Xiaoyu", "Wang", role = c("aut")))
Author: James Dai [aut, cre], Xiaoyu Wang [aut]
Maintainer: James Dai <jdai@fredhutch.org>
Description: A multiple-testing procedure for high-dimensional mediation hypotheses. Mediation analysis is of rising interest in epidemiology and clinical trials. Among existing methods for mediation analyses, the popular joint significance (JS) test yields an overly conservative type I error rate and therefore low power. In the R package 'HDMT' we implement a multiple-testing procedure that accurately controls the family-wise error rate (FWER) and the false discovery rate (FDR) when using JS for testing high-dimensional mediation hypotheses. The core of our procedure is based on estimating the proportions of three component null hypotheses and deriving the corresponding mixture distribution of null p-values. Results of the data examples include better-behaved quantile-quantile plots and improved detection of novel mediation relationships on the role of DNA methylation in genetic regulation of gene expression. With increasing interest in mediation by molecular intermediaries such as gene expression and epigenetic markers, the proposed method addresses an unmet methodological challenge.
Depends: R (>= 3.4.0)
Imports: cp4p,fdrtool
LazyLoad: no
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2019-04-15 20:16:02 UTC; xwang234
Repository: CRAN
Date/Publication: 2019-04-16 12:42:43 UTC

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Package gllvm updated to version 1.1.3 with previous version 1.1.2 dated 2019-01-02

Title: Generalized Linear Latent Variable Models
Description: Analysis of multivariate data using generalized linear latent variable models (gllvm). Estimation is performed using either Laplace approximation method or variational approximation method implemented via TMB (Kristensen et al., (2016), <doi:10.18637/jss.v070.i05>). Details for gllvm, see Hui et al. (2015) <doi:10.1111/2041-210X.12236> and (2017) <doi:10.1080/10618600.2016.1164708> and Niku et al. (2017) <doi:10.1007/s13253-017-0304-7>.
Author: Jenni Niku, Wesley Brooks, Riki Herliansyah, Francis K.C. Hui, Sara Taskinen, David I. Warton
Maintainer: Jenni Niku <jenni.m.e.niku@jyu.fi>

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Package BIFIEsurvey updated to version 3.2-25 with previous version 3.1-33 dated 2019-03-20

Title: Tools for Survey Statistics in Educational Assessment
Description: Contains tools for survey statistics (especially in educational assessment) for datasets with replication designs (jackknife, bootstrap, replicate weights; see Kolenikov, 2010; Pfefferman & Rao, 2009a, 2009b, <doi:10.1016/S0169-7161(09)70003-3>, <doi:10.1016/S0169-7161(09)70037-9>); Shao, 1996, <doi:10.1080/02331889708802523>). Descriptive statistics, linear and logistic regression, path models for manifest variables with measurement error correction and two-level hierarchical regressions for weighted samples are included. Statistical inference can be conducted for multiply imputed datasets and nested multiply imputed datasets and is in particularly suited for the analysis of plausible values (for details see George, Oberwimmer & Itzlinger-Bruneforth, 2016; Bruneforth, Oberwimmer & Robitzsch, 2016; Robitzsch, Pham & Yanagida, 2016; <doi:10.17888/fdb-demo:bistE813I-16a>). The package development was supported by BIFIE (Federal Institute for Educational Research, Innovation and Development of the Austrian School System; Salzburg, Austria).
Author: BIFIE [aut], Alexander Robitzsch [aut, cre], Konrad Oberwimmer [aut]
Maintainer: Alexander Robitzsch <robitzsch@ipn.uni-kiel.de>

Diff between BIFIEsurvey versions 3.1-33 dated 2019-03-20 and 3.2-25 dated 2019-04-16

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Package mdmb updated to version 1.3-18 with previous version 1.2-4 dated 2019-01-11

Title: Model Based Treatment of Missing Data
Description: Contains model-based treatment of missing data for regression models with missing values in covariates or the dependent variable using maximum likelihood or Bayesian estimation (Ibrahim et al., 2005; <doi:10.1198/016214504000001844>). The regression model can be nonlinear (e.g., interaction effects, quadratic effects or B-spline functions). Multilevel models with missing data in predictors are available for Bayesian estimation. Substantive-model compatible multiple imputation can be also conducted.
Author: Alexander Robitzsch [aut, cre], Oliver Luedtke [aut]
Maintainer: Alexander Robitzsch <robitzsch@ipn.uni-kiel.de>

Diff between mdmb versions 1.2-4 dated 2019-01-11 and 1.3-18 dated 2019-04-16

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Package fastNaiveBayes updated to version 1.1.2 with previous version 1.1.1 dated 2019-03-31

Title: Extremely Fast Implementation of a Naive Bayes Classifier
Description: This is an extremely fast implementation of a Naive Bayes classifier. This package is currently the only package that supports a Bernoulli distribution, a Multinomial distribution, and a Gaussian distribution, making it suitable for both binary features, frequency counts, and numerical features. Another feature is the support of a mix of different event models. Only numerical variables are allowed, however, categorical variables can be transformed into dummies and used with the Bernoulli distribution. This implementation offers a huge performance gain compared to other implementations in R. The execution times were compared on a data set of tweets and this package was found to be around 283 to 34,841 times faster for the Bernoulli event models and 17 to 60 times faster for the Multinomial model. See the vignette for more details. For the Gaussian distribution this package was found to be between 2.8 and 1679 times faster. The implementation is largely based on the paper "A comparison of event models for Naive Bayes anti-spam e-mail filtering" written by K.M. Schneider (2003) <doi:10.3115/1067807>. Any issues can be submitted to: <https://github.com/mskogholt/fastNaiveBayes/issues>.
Author: Martin Skogholt
Maintainer: Martin Skogholt <m.skogholt@gmail.com>

Diff between fastNaiveBayes versions 1.1.1 dated 2019-03-31 and 1.1.2 dated 2019-04-16

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Package scatterD3 updated to version 0.9 with previous version 0.8.2 dated 2018-03-10

Title: D3 JavaScript Scatterplot from R
Description: Creates 'D3' 'JavaScript' scatterplots from 'R' with interactive features : panning, zooming, tooltips, etc.
Author: Julien Barnier [aut, cre], Kent Russell [aut, ctb], Mike Bostock [aut, cph] (d3.js library, http://d3js.org), Susie Lu [aut, cph] (d3-legend library, http://d3-legend.susielu.com/), Speros Kokenes [aut, cph] (d3-lasso-plugin library, https://github.com/skokenes/D3-Lasso-Plugin), Evan Wang [aut, cph] (d3-labeler plugin, https://github.com/tinker10/D3-Labeler)
Maintainer: Julien Barnier <julien.barnier@ens-lyon.fr>

Diff between scatterD3 versions 0.8.2 dated 2018-03-10 and 0.9 dated 2019-04-16

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Package fpeek updated to version 0.1.1 with previous version 0.1.0 dated 2018-07-22

Title: Check Text Files Content at a Glance
Description: Tools to help text files importation. It can return the number of lines; print the first and last lines; convert encoding. Operations are made without reading the entire file before starting, resulting in good performances with large files. This package provides an alternative to a simple use of the 'head', 'tail', 'wc' and 'iconv' programs that are not always available on machine where R is installed.
Author: David Gohel [aut, cre]
Maintainer: David Gohel <david.gohel@ardata.fr>

Diff between fpeek versions 0.1.0 dated 2018-07-22 and 0.1.1 dated 2019-04-16

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New package dstat with initial version 1.0.4
Package: dstat
Type: Package
Title: Conditional Sensitivity Analysis for Matched Observational Studies
Version: 1.0.4
Author: Paul R. Rosenbaum
Maintainer: Paul R. Rosenbaum <rosenbaum@wharton.upenn.edu>
Description: A d-statistic tests the null hypothesis of no treatment effect in a matched, nonrandomized study of the effects caused by treatments. A d-statistic focuses on subsets of matched pairs that demonstrate insensitivity to unmeasured bias in such an observational study, correcting for double-use of the data by conditional inference. This conditional inference can, in favorable circumstances, substantially increase the power of a sensitivity analysis (Rosenbaum (2010) <doi:10.1007/978-1-4419-1213-8_14>). There are two examples, one concerning unemployment from Lalive et al. (2006) <doi:10.1111/j.1467-937X.2006.00406.x>, the other concerning smoking and periodontal disease from Rosenbaum (2017) <doi:10.1214/17-STS621>.
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: stats
NeedsCompilation: no
Packaged: 2019-04-15 13:23:56 UTC; Rosenbaum
Repository: CRAN
Date/Publication: 2019-04-16 09:42:41 UTC

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New package cmmr with initial version 0.1.2
Package: cmmr
Type: Package
Title: CEU Mass Mediator RESTful API
Version: 0.1.2
Date: 2019-03-26
Depends: R (>= 3.1.0)
Imports: httr (>= 1.3.1), progress (>= 1.2.0), RJSONIO (>= 1.3-0)
Author: Yaoxiang Li <yl814@georgetown.edu>, Charles P. Hinzman <cph51@georgetown.edu>, Amrita K Cheema <akc27@georgetown.edu>
Maintainer: Yaoxiang Li <yl814@georgetown.edu>
Description: CEU (CEU San Pablo University) Mass Mediator is an on-line tool for aiding researchers in performing metabolite annotation. 'cmmr' (CEU Mass Mediator RESTful API) allows for programmatic access in R: batch search, batch advanced search, MS/MS (tandem mass spectrometry) search, etc. For more information about the API Endpoint please go to <https://github.com/lzyacht/cmmr>.
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/lzyacht/cmmr
RoxygenNote: 6.1.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-04-01 00:49:07 UTC; bach
Repository: CRAN
Date/Publication: 2019-04-16 09:42:44 UTC

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Package arulesSequences updated to version 0.2-22 with previous version 0.2-21 dated 2019-03-04

Title: Mining Frequent Sequences
Description: Add-on for arules to handle and mine frequent sequences. Provides interfaces to the C++ implementation of cSPADE by Mohammed J. Zaki.
Author: Christian Buchta and Michael Hahsler, with contributions from Daniel Diaz
Maintainer: Christian Buchta <christian.buchta@wu.ac.at>

Diff between arulesSequences versions 0.2-21 dated 2019-03-04 and 0.2-22 dated 2019-04-16

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Package RJDemetra updated to version 0.1.2 with previous version 0.1.1 dated 2019-03-04

Title: Interface to 'JDemetra+' Seasonal Adjustment Software
Description: Interface around 'JDemetra+' (<https://github.com/jdemetra/jdemetra-app>), the seasonal adjustment software officially recommended to the members of the European Statistical System (ESS) and the European System of Central Banks. It offers full access to all options and outputs of 'JDemetra+', including the two leading seasonal adjustment methods TRAMO/SEATS+ and X-12ARIMA/X-13ARIMA-SEATS.
Author: Alain Quartier-la-Tente [aut, cre], Anna Michalek [aut], Jean Palate [aut], Raf Baeyens [aut]
Maintainer: Alain Quartier-la-Tente <alain.quartier@yahoo.fr>

Diff between RJDemetra versions 0.1.1 dated 2019-03-04 and 0.1.2 dated 2019-04-16

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Package labelled updated to version 2.2.0 with previous version 2.1.0 dated 2019-02-25

Title: Manipulating Labelled Data
Description: Work with labelled data imported from 'SPSS' or 'Stata' with 'haven' or 'foreign'. This package provides useful functions to deal with "haven_labelled" and "haven_labelled_spss" classes introduced by 'haven' package.
Author: Joseph Larmarange [aut, cre] (<https://orcid.org/0000-0001-7097-700X>), Daniel Ludecke [ctb], Hadley Wickham [ctb], Bojanowski Michal [ctb], Briatte François [ctb]
Maintainer: Joseph Larmarange <joseph@larmarange.net>

Diff between labelled versions 2.1.0 dated 2019-02-25 and 2.2.0 dated 2019-04-16

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New package frequentdirections with initial version 0.1.0
Package: frequentdirections
Type: Package
Title: Implementation of Frequent-Directions Algorithm for Efficient Matrix Sketching
Version: 0.1.0
Authors@R: c( person("Shinichi", "Takayanagi", , "shinichi.takayanagi@gmail.com", role = c("aut", "cre")), person("Nagi", "Teramo", , "teramonagi@gmail.com", role = c("aut")) )
Description: Implement frequent-directions algorithm for efficient matrix sketching. (Edo Liberty (2013) <doi:10.1145/2487575.2487623>).
URL: https://github.com/shinichi-takayanagi/frequentdirections
BugReports: https://github.com/shinichi-takayanagi/frequentdirections/issues
License: MIT + file LICENSE
Encoding: UTF-8
Imports: ggplot2,
Suggests: testthat, knitr, rmarkdown
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-04-15 13:03:42 UTC; stakaya
Author: Shinichi Takayanagi [aut, cre], Nagi Teramo [aut]
Maintainer: Shinichi Takayanagi <shinichi.takayanagi@gmail.com>
Repository: CRAN
Date/Publication: 2019-04-16 08:52:42 UTC

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Package dbparser updated to version 1.0.1 with previous version 1.0.0 dated 2018-12-17

Title: 'DrugBank' Database XML Parser
Description: This tool is for parsing the 'DrugBank' XML database <http://drugbank.ca/>. The parsed data are then returned in a proper 'R' dataframe with the ability to save them in a given database.
Author: Mohammed Ali [aut, cre], Ali Ezzat [aut]
Maintainer: Mohammed Ali <moh_fcis@yahoo.com>

Diff between dbparser versions 1.0.0 dated 2018-12-17 and 1.0.1 dated 2019-04-16

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 dbparser-1.0.1/dbparser/tests/testthat/test_drug_targets_node_parser.R |    2 
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 64 files changed, 1730 insertions(+), 1168 deletions(-)

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