Thu, 25 Apr 2019

Package smooth updated to version 2.5.0 with previous version 2.4.7 dated 2018-12-02

Title: Forecasting Using State Space Models
Description: Functions implementing Single Source of Error state space models for purposes of time series analysis and forecasting. The package includes Exponential Smoothing, SARIMA, Complex Exponential Smoothing, Simple Moving Average, Vector Exponential Smoothing in state space forms, several simulation functions and intermittent demand state space models.
Author: Ivan Svetunkov [aut, cre] (Lecturer at Centre for Marketing Analytics and Forecasting, Lancaster University, UK)
Maintainer: Ivan Svetunkov <ivan@svetunkov.ru>

Diff between smooth versions 2.4.7 dated 2018-12-02 and 2.5.0 dated 2019-04-25

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Package sf updated to version 0.7-4 with previous version 0.7-3 dated 2019-02-21

Title: Simple Features for R
Description: Support for simple features, a standardized way to encode spatial vector data. Binds to 'GDAL' for reading and writing data, to 'GEOS' for geometrical operations, and to 'PROJ' for projection conversions and datum transformations.
Author: Edzer Pebesma [aut, cre] (<https://orcid.org/0000-0001-8049-7069>), Roger Bivand [ctb] (<https://orcid.org/0000-0003-2392-6140>), Etienne Racine [ctb], Michael Sumner [ctb], Ian Cook [ctb], Tim Keitt [ctb], Robin Lovelace [ctb], Hadley Wickham [ctb], Jeroen Ooms [ctb] (<https://orcid.org/0000-0002-4035-0289>), Kirill Müller [ctb], Thomas Lin Pedersen [ctb]
Maintainer: Edzer Pebesma <edzer.pebesma@uni-muenster.de>

Diff between sf versions 0.7-3 dated 2019-02-21 and 0.7-4 dated 2019-04-25

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Package pcalg updated to version 2.6-2 with previous version 2.6-0 dated 2018-06-04

Title: Methods for Graphical Models and Causal Inference
Description: Functions for causal structure learning and causal inference using graphical models. The main algorithms for causal structure learning are PC (for observational data without hidden variables), FCI and RFCI (for observational data with hidden variables), and GIES (for a mix of data from observational studies (i.e. observational data) and data from experiments involving interventions (i.e. interventional data) without hidden variables). For causal inference the IDA algorithm, the Generalized Backdoor Criterion (GBC), the Generalized Adjustment Criterion (GAC) and some related functions are implemented. Functions for incorporating background knowledge are provided.
Author: Markus Kalisch [aut, cre], Alain Hauser [aut], Martin Maechler [aut], Diego Colombo [ctb], Doris Entner [ctb], Patrik Hoyer [ctb], Antti Hyttinen [ctb], Jonas Peters [ctb], Nicoletta Andri [ctb], Emilija Perkovic [ctb], Preetam Nandy [ctb], Philipp Ruetimann [ctb], Daniel Stekhoven [ctb], Manuel Schuerch [ctb], Marco Eigenmann [ctb]
Maintainer: Markus Kalisch <kalisch@stat.math.ethz.ch>

Diff between pcalg versions 2.6-0 dated 2018-06-04 and 2.6-2 dated 2019-04-25

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Package mpt updated to version 0.6-0 with previous version 0.5-4 dated 2016-09-08

Title: Multinomial Processing Tree Models
Description: Fitting and testing multinomial processing tree (MPT) models, a class of nonlinear models for categorical data. The parameters are the link probabilities of a tree-like graph and represent the latent cognitive processing steps executed to arrive at observable response categories (Batchelder & Riefer, 1999 <doi:10.3758/bf03210812>; Erdfelder et al., 2009 <doi:10.1027/0044-3409.217.3.108>; Riefer & Batchelder, 1988 <doi:10.1037/0033-295x.95.3.318>).
Author: Florian Wickelmaier [aut, cre], Achim Zeileis [aut] (<https://orcid.org/0000-0003-0918-3766>)
Maintainer: Florian Wickelmaier <wickelmaier@web.de>

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Package metaplot updated to version 0.8.3 with previous version 0.8.2 dated 2019-02-04

Title: Data-Driven Plot Design
Description: Designs plots in terms of core structure. See 'example(metaplot)'. Primary arguments are (unquoted) column names; order and type (numeric or not) dictate the resulting plot. Specify any y variables, x variable, any groups variable, and any conditioning variables to metaplot() to generate density plots, boxplots, mosaic plots, scatterplots, scatterplot matrices, or conditioned plots. Use multiplot() to arrange plots in grids. Wherever present, scalar column attributes 'label' and 'guide' are honored, producing fully annotated plots with minimal effort. Attribute 'guide' is typically units, but may be encoded() to provide interpretations of categorical values (see '?encode'). Utility unpack() transforms scalar column attributes to row values and pack() does the reverse, supporting tool-neutral storage of metadata along with primary data. The package supports customizable aesthetics such as such as reference lines, unity lines, smooths, log transformation, and linear fits. The user may choose between trellis and ggplot output. Compact syntax and integrated metadata promote workflow scalability.
Author: Tim Bergsma
Maintainer: Tim Bergsma <bergsmat@gmail.com>

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Package estudy2 updated to version 0.9.0 with previous version 0.8.5 dated 2018-07-03

Title: An Implementation of Parametric and Nonparametric Event Study
Description: An implementation of a most commonly used event study methodology, including both parametric and nonparametric tests. It contains variety aspects of the rate of return estimation (the core calculation is done in C++), as well as three classical for event study market models: mean adjusted returns, market adjusted returns and single-index market models. There are 6 parametric and 6 nonparametric tests provided, which examine cross-sectional daily abnormal return (see the documentation of the functions for more information). Parametric tests include tests proposed by Brown and Warner (1980) <DOI:10.1016/0304-405X(80)90002-1>, Brown and Warner (1985) <DOI:10.1016/0304-405X(85)90042-X>, Boehmer et al. (1991) <DOI:10.1016/0304-405X(91)90032-F>, Patell (1976) <DOI:10.2307/2490543>, and Lamb (1995) <DOI:10.2307/253695>. Nonparametric tests covered in estudy2 are tests described in Corrado and Zivney (1992) <DOI:10.2307/2331331>, McConnell and Muscarella (1985) <DOI:10.1016/0304-405X(85)90006-6>, Boehmer et al. (1991) <DOI:10.1016/0304-405X(91)90032-F>, Cowan (1992) <DOI:10.1007/BF00939016>, Corrado (1989) <DOI:10.1016/0304-405X(89)90064-0>, Campbell and Wasley (1993) <DOI:10.1016/0304-405X(93)90025-7>, Savickas (2003) <DOI:10.1111/1475-6803.00052>, Kolari and Pynnonen (2010) <DOI:10.1093/rfs/hhq072>. Furthermore, tests for the cumulative abnormal returns proposed by Brown and Warner (1985) <DOI:10.1016/0304-405X(85)90042-X> and Lamb (1995) <DOI:10.2307/253695> are included.
Author: Iegor Rudnytskyi [aut, cre]
Maintainer: Iegor Rudnytskyi <iegor.rudnytskyi@gmail.com>

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Package childesr updated to version 0.1.1 with previous version 0.1.0 dated 2018-05-18

Title: Accessing the 'CHILDES' Database
Description: Tools for connecting to 'CHILDES', an open repository for transcripts of parent-child interaction. For more information on the underlying data, see <http://childes-db.stanford.edu>.
Author: Mika Braginsky [aut, cre], Alessandro Sanchez [aut, ctb], Daniel Yurovsky [aut], Kyle MacDonald [ctb], Stephan Meylan [ctb]
Maintainer: Mika Braginsky <mika.br@gmail.com>

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Package mlr updated to version 2.14.0 with previous version 2.13 dated 2018-08-28

Title: Machine Learning in R
Description: Interface to a large number of classification and regression techniques, including machine-readable parameter descriptions. There is also an experimental extension for survival analysis, clustering and general, example-specific cost-sensitive learning. Generic resampling, including cross-validation, bootstrapping and subsampling. Hyperparameter tuning with modern optimization techniques, for single- and multi-objective problems. Filter and wrapper methods for feature selection. Extension of basic learners with additional operations common in machine learning, also allowing for easy nested resampling. Most operations can be parallelized.
Author: Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>), Michel Lang [aut] (<https://orcid.org/0000-0001-9754-0393>), Lars Kotthoff [aut], Julia Schiffner [aut], Jakob Richter [aut], Zachary Jones [aut], Giuseppe Casalicchio [aut] (<https://orcid.org/0000-0001-5324-5966>), Mason Gallo [aut], Patrick Schratz [aut, cre] (<https://orcid.org/0000-0003-0748-6624>), Jakob Bossek [ctb] (<https://orcid.org/0000-0002-4121-4668>), Erich Studerus [ctb] (<https://orcid.org/0000-0003-4233-0182>), Leonard Judt [ctb], Tobias Kuehn [ctb], Pascal Kerschke [ctb] (<https://orcid.org/0000-0003-2862-1418>), Florian Fendt [ctb], Philipp Probst [ctb] (<https://orcid.org/0000-0001-8402-6790>), Xudong Sun [ctb] (<https://orcid.org/0000-0003-3269-2307>), Janek Thomas [ctb] (<https://orcid.org/0000-0003-4511-6245>), Bruno Vieira [ctb], Laura Beggel [ctb] (<https://orcid.org/0000-0002-8872-8535>), Quay Au [ctb] (<https://orcid.org/0000-0002-5252-8902>), Martin Binder [ctb], Florian Pfisterer [ctb], Stefan Coors [ctb], Steve Bronder [ctb], Alexander Engelhardt [ctb], Christoph Molnar [ctb]
Maintainer: Patrick Schratz <patrick.schratz@gmail.com>

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Package gstat updated to version 2.0-1 with previous version 2.0-0 dated 2019-02-28

Title: Spatial and Spatio-Temporal Geostatistical Modelling, Prediction and Simulation
Description: Variogram modelling; simple, ordinary and universal point or block (co)kriging; spatio-temporal kriging; sequential Gaussian or indicator (co)simulation; variogram and variogram map plotting utility functions; supports sf and stars.
Author: Edzer Pebesma [aut, cre] (<https://orcid.org/0000-0001-8049-7069>), Benedikt Graeler [aut]
Maintainer: Edzer Pebesma <edzer.pebesma@uni-muenster.de>

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Package pct updated to version 0.1.3 with previous version 0.1.2 dated 2019-04-16

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 ordinal updated to version 2019.4-25 with previous version 2019.3-9 dated 2019-03-09

Title: Regression Models for Ordinal Data
Description: Implementation of cumulative link (mixed) models also known as ordered regression models, proportional odds models, proportional hazards models for grouped survival times and ordered logit/probit/... models. Estimation is via maximum likelihood and mixed models are fitted with the Laplace approximation and adaptive Gauss-Hermite quadrature. Multiple random effect terms are allowed and they may be nested, crossed or partially nested/crossed. Restrictions of symmetry and equidistance can be imposed on the thresholds (cut-points/intercepts). Standard model methods are available (summary, anova, drop-methods, step, confint, predict etc.) in addition to profile methods and slice methods for visualizing the likelihood function and checking convergence.
Author: Rune Haubo Bojesen Christensen [aut, cre]
Maintainer: Rune Haubo Bojesen Christensen <rune.haubo@gmail.com>

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Package GeneCycle updated to version 1.1.4 with previous version 1.1.3 dated 2019-04-18

Title: Identification of Periodically Expressed Genes
Description: The GeneCycle package implements the approaches of Wichert et al. (2004) <doi.org/10.1093/bioinformatics/btg364>, Ahdesmaki et al. (2005) <DOI:10.1186/1471-2105-6-117> and Ahdesmaki et al. (2007) <DOI:10.1186/1471-2105-8-233> for detecting periodically expressed genes from gene expression time series data.
Author: Miika Ahdesmaki, Konstantinos Fokianos, and Korbinian Strimmer.
Maintainer: Miika Ahdesmaki <miika.ahdesmaki@gmail.com>

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Package err updated to version 0.2.0 with previous version 0.0.1 dated 2018-10-28

Title: Customizable Object Sensitive Messages
Description: Messages should provide users with readable information about R objects without flooding their console. 'cc()' concatenates vector and data frame values into a grammatically correct string using commas, an ellipsis and conjunction. 'cn()' allows the user to define a string which varies based on a count. 'co()' combines the two to produce a customizable object aware string. The package further facilitates this process by providing five 'sprintf'-like types such as '%n' for the length of an object and '%o' for its name as well as wrappers for pasting objects and issuing errors, warnings and messages.
Author: Joe Thorley [aut, cre] (<https://orcid.org/0000-0002-7683-4592>), James Dunham [aut]
Maintainer: Joe Thorley <joe@poissonconsulting.ca>

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Package rsimsum updated to version 0.5.2 with previous version 0.5.1 dated 2019-03-15

Title: Analysis of Simulation Studies Including Monte Carlo Error
Description: Summarise results from simulation studies and compute Monte Carlo standard errors of commonly used summary statistics. This package is modelled on the 'simsum' user-written command in 'Stata' (See White I.R., 2010 <http://www.stata-journal.com/article.html?article=st0200>).
Author: Alessandro Gasparini [aut, cre] (<https://orcid.org/0000-0002-8319-7624>), Ian R. White [aut]
Maintainer: Alessandro Gasparini <ag475@leicester.ac.uk>

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Package Phase123 updated to version 2.1 with previous version 2.0 dated 2018-11-09

Title: Simulating and Conducting Phase 123 Trials
Description: Contains three simulation functions for implementing the entire Phase 123 trial and the separate Eff-Tox and Phase 3 portions of the trial, which may be beneficial for use on clusters. The functions AssignEffTox() and RandomizeEffTox() assign doses to patient cohorts during phase 12 and Reoptimize() determines the optimal dose to continue with during Phase 3. The functions ReturnMeansAgent() and ReturnMeanControl() gives the true mean survival for the agent doses and control and ReturnOCS() gives the operating characteristics of the design.
Author: Andrew G Chapple
Maintainer: Andrew G Chapple <achapp@lsuhsc.edu>

Diff between Phase123 versions 2.0 dated 2018-11-09 and 2.1 dated 2019-04-25

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New package tinytest with initial version 0.9.2
Package: tinytest
Maintainer: Mark van der Loo <mark.vanderloo@gmail.com>
License: GPL-3
Title: Lightweight but Feature Complete Unit Testing Framework
LazyData: no
Type: Package
LazyLoad: yes
Authors@R: c( person("Mark", "van der Loo", role=c("aut","cre"),email="mark.vanderloo@gmail.com"))
Description: Provides a lightweight (zero-dependency) and easy to use unit testing framework. Main features: easily install tests with the package. Test results are treated as data that can be stored and manipulated. Test files are R scripts interspersed with test commands, that can be programmed over. Fully automated build-install-test sequence for packages. Skip tests when not run locally (e.g. on CRAN). Flexible and configurable output printing. Compare computed output with output stored with the package.
Version: 0.9.2
URL: https://github.com/markvanderloo/tinytest
BugReports: https://github.com/markvanderloo/tinytest/issues
Imports: utils
RoxygenNote: 6.1.1
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-04-23 14:48:58 UTC; mark
Author: Mark van der Loo [aut, cre]
Repository: CRAN
Date/Publication: 2019-04-25 16:20:04 UTC

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New package mcStats with initial version 0.1.0
Package: mcStats
Title: Visualize Results of Statistical Hypothesis Tests
Version: 0.1.0
Authors@R: c(person("Michael", "Czekanski", email = "mczekanski@middlebury.edu", role = c("aut", "cre")), person("Alex", "Lyford", email = "alyford@middlebury.edu", role = "aut"))
Description: Provides functionality to produce graphs of sampling distributions of test statistics from a variety of common statistical tests. With only a few keystrokes, the user can conduct a hypothesis test and visualize the test statistic and corresponding p-value through the shading of its sampling distribution. Initially created for statistics at Middlebury College.
Depends: R (>= 3.4.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: dplyr, ggplot2, ggthemes, gridExtra, magrittr, tidyr
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-04-25 14:59:34 UTC; michael
Author: Michael Czekanski [aut, cre], Alex Lyford [aut]
Maintainer: Michael Czekanski <mczekanski@middlebury.edu>
Repository: CRAN
Date/Publication: 2019-04-25 16:30:03 UTC

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Package httk updated to version 1.9.2 with previous version 1.9.1 dated 2019-04-17

Title: High-Throughput Toxicokinetics
Description: Functions and data tables for simulation and statistical analysis of chemical toxicokinetics ("TK") as in Pearce et al. (2017) <doi:10.18637/jss.v079.i04>. Chemical-specific in vitro data have been obtained from relatively high throughput experiments. Both physiologically-based ("PBTK") and empirical (e.g., one compartment) "TK" models can be parameterized for several hundred chemicals and multiple species. These models are solved efficiently, often using compiled (C-based) code. A Monte Carlo sampler is included for simulating biological variability (Ring et al., 2017 <doi:10.1016/j.envint.2017.06.004>) and measurement limitations. Calibrated methods are included for predicting tissue:plasma partition coefficients and volume of distribution (Pearce et al., 2017 <doi:10.1007/s10928-017-9548-7>). These functions and data provide a set of tools for in vitro-in vivo extrapolation ("IVIVE") of high throughput screening data (e.g., Tox21, ToxCast) to real-world exposures via reverse dosimetry (also known as "RTK") (Wetmore et al., 2015 <doi:10.1093/toxsci/kfv171>).
Author: John Wambaugh [aut, cre], Robert Pearce [aut], Caroline Ring [aut], Greg Honda [aut], Jimena Davis [ctb], Nisha Sipes [ctb], Barbara Wetmore [ctb], Woodrow Setzer [ctb]
Maintainer: John Wambaugh <wambaugh.john@epa.gov>

Diff between httk versions 1.9.1 dated 2019-04-17 and 1.9.2 dated 2019-04-25

 DESCRIPTION                                                             |    8 
 MD5                                                                     |   78 ++--
 NEWS                                                                    |binary
 R/Parameterize_SteadyState.R                                            |    3 
 R/calc_analytic_css.R                                                   |    4 
 R/calc_mc_css.R                                                         |   49 +--
 R/convert_httk.R                                                        |   19 +
 R/draw_fup_clint.R                                                      |    6 
 R/get_cheminfo.R                                                        |    4 
 R/modelinfo_3compss.R                                                   |    1 
 build/partial.rdb                                                       |binary
 inst/doc/Pearce_2017_partitioning_plots.html                            |    4 
 inst/doc/Ring_2017_supplemental_vignette_age_dist.html                  |    4 
 inst/doc/Ring_2017_supplemental_vignette_globalsensitivityanalysis.html |    4 
 inst/doc/Ring_2017_supplemental_vignette_globalsensitivityplot.html     |    4 
 inst/doc/Ring_2017_supplemental_vignette_heightweight_splines_kde.html  |    4 
 inst/doc/Ring_2017_supplemental_vignette_hematocrit_splines.html        |    4 
 inst/doc/Ring_2017_supplemental_vignette_plot_css95.html                |    4 
 inst/doc/Ring_2017_supplemental_vignette_serumcreat_splines_kde.html    |    4 
 inst/doc/Ring_2017_vignette01_subpopulations.html                       |    4 
 inst/doc/Ring_2017_vignette02_evalmodelsubpop.html                      |    4 
 inst/doc/Ring_2017_vignette03_paper_fig2.html                           |    4 
 inst/doc/Ring_2017_vignette04_paper_fig3.html                           |    4 
 inst/doc/Ring_2017_vignette05b_plothowgatejohnson.html                  |    4 
 inst/doc/Ring_2017_vignette06_aerplotting.html                          |    4 
 inst/doc/Ring_2017_vignette_05a_virtualstudypops.html                   |    4 
 inst/doc/Wambaugh_2018_Figures.html                                     |    4 
 tests/1comp_test.R                                                      |   58 +++
 tests/1comp_test.Rout.save                                              |  157 ++++++----
 tests/3comp_test.R                                                      |   57 +++
 tests/3comp_test.Rout.save                                              |  142 ++++++---
 tests/3compss_test.R                                                    |   50 ++-
 tests/3compss_test.Rout.save                                            |   67 +++-
 tests/adddata_test.Rout.save                                            |   14 
 tests/cheminfo_test.Rout.save                                           |    6 
 tests/ivive_test.R                                                      |   70 ++--
 tests/ivive_test.Rout.save                                              |   81 ++---
 tests/other_tests.Rout.save                                             |   14 
 tests/pbtk_test.R                                                       |   57 +++
 tests/pbtk_test.Rout.save                                               |  133 ++++++--
 40 files changed, 794 insertions(+), 348 deletions(-)

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New package stcos with initial version 0.1.0
Package: stcos
Type: Package
Title: Space-Time Change of Support
Version: 0.1.0
Date: 2019-04-23
Authors@R: c( person(c("Andrew", "M."), "Raim", email = "andrew.raim@gmail.com", role = c("aut", "cre")), person(c("Scott", "H."), "Holan", role = c("aut", "res")), person(c("Jonathan", "R."), "Bradley", role = c("aut", "res")), person(c("Christopher", "K."), "Wikle", role = c("aut", "res")))
Author: Andrew M. Raim [aut, cre], Scott H. Holan [aut, res], Jonathan R. Bradley [aut, res], Christopher K. Wikle [aut, res]
Maintainer: Andrew M. Raim <andrew.raim@gmail.com>
URL: https://github.com/holans/ST-COS
Description: Spatio-temporal change of support (STCOS) methods are designed for statistical inference on geographic and/or time domains that differ from those on which the data were observed. 'stcos' implements a parsimonious class of Bayesian hierarchical spatio-temporal models for STCOS with Gaussian outcomes introduced by Bradley, Wikle, and Holan <doi:10.1002/sta4.94>.
License: GPL (>= 2)
Imports: R6
Depends: R (>= 3.3), Rcpp, Matrix, sf
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 6.1.1
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
Packaged: 2019-04-23 19:27:38 UTC; araim
Repository: CRAN
Date/Publication: 2019-04-25 16:00:03 UTC

More information about stcos at CRAN
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Package spant updated to version 0.13.0 with previous version 0.12.0 dated 2018-11-05

Title: MR Spectroscopy Analysis Tools
Description: Tools for reading, visualising and processing Magnetic Resonance Spectroscopy data.
Author: Martin Wilson [cre, aut], John Muschelli [ctb]
Maintainer: Martin Wilson <martin@pipegrep.co.uk>

Diff between spant versions 0.12.0 dated 2018-11-05 and 0.13.0 dated 2019-04-25

 spant-0.12.0/spant/man/diff.mrs_data.Rd               |only
 spant-0.13.0/spant/DESCRIPTION                        |   10 
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 spant-0.13.0/spant/R/amp_scaling.R                    |  374 -
 spant-0.13.0/spant/R/basis_set.R                      |  548 +-
 spant-0.13.0/spant/R/data.R                           |    4 
 spant-0.13.0/spant/R/fit_display.R                    |  585 +-
 spant-0.13.0/spant/R/fitting.R                        | 1094 ++---
 spant-0.13.0/spant/R/fp_corr_td.R                     |  143 
 spant-0.13.0/spant/R/image_reg.R                      |  374 -
 spant-0.13.0/spant/R/interactive_plotting.R           |  332 -
 spant-0.13.0/spant/R/mol_parameters.R                 | 1655 +++----
 spant-0.13.0/spant/R/mrs_data_display.R               | 1049 ++--
 spant-0.13.0/spant/R/mrs_data_io.R                    |  533 +-
 spant-0.13.0/spant/R/mrs_data_proc.R                  | 3840 +++++++++---------
 spant-0.13.0/spant/R/mrs_read_ima.R                   |   62 
 spant-0.13.0/spant/R/mrs_read_list_data.R             |  204 
 spant-0.13.0/spant/R/mrs_read_paravis.R               |  132 
 spant-0.13.0/spant/R/mrs_read_pfile.R                 |  380 -
 spant-0.13.0/spant/R/mrs_read_rda.R                   |  116 
 spant-0.13.0/spant/R/mrs_read_spar_sdat.R             |  350 -
 spant-0.13.0/spant/R/mrs_read_twix.R                  |  573 +-
 spant-0.13.0/spant/R/pulse_sequences.R                | 1068 ++---
 spant-0.13.0/spant/R/pulse_shapes.R                   |   24 
 spant-0.13.0/spant/R/qm_simulation.R                  |  906 ++--
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 spant-0.13.0/spant/R/spant.R                          |  284 -
 spant-0.13.0/spant/R/utils.R                          |  693 +--
 spant-0.13.0/spant/R/varpro.R                         |  502 +-
 spant-0.13.0/spant/R/varpro_3_para.R                  |  448 +-
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New package RMKL with initial version 1.0
Package: RMKL
Type: Package
Title: Multiple Kernel Learning for Classification or Regression Problems
Version: 1.0
Date: 2019-04-11
Author: Christopher Wilson, Kaiqiao Li
Maintainer: Christopher Wilson <cwilso6@clemson.edu>
Description: Provides R and C++ function that enable the user to conduct multiple kernel learning (MKL) and cross validation for support vector machine (SVM) models. Cross validation can be used to identify kernel shapes and hyperparameter combinations that can be used as candidate kernels for MKL. There are three implementations provided in this package, namely SimpleMKL Alain Rakotomamonjy et. al (2008), Simple and Efficient MKL Xu et. al (2010), and Dual augmented Lagrangian MKL Suzuki and Tomioka (2011) <doi:10.1007/s10994-011-5252-9>. These methods identify the convex combination of candidate kernels to construct an optimal hyperplane.
License: GPL-3
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 1.0.0), caret, kernlab, stats, e1071
LinkingTo: Rcpp, RcppArmadillo
LazyData: true
LazyLoad: yes
Encoding: UTF-8
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-04-24 14:53:19 UTC; 4468179
Repository: CRAN
Date/Publication: 2019-04-25 15:20:03 UTC

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Package openEBGM updated to version 0.8.2 with previous version 0.8.1 dated 2019-02-28

Title: EBGM Disproportionality Scores for Adverse Event Data Mining
Description: An implementation of DuMouchel's (1999) <doi:10.1080/00031305.1999.10474456> Bayesian data mining method for the market basket problem. Calculates Empirical Bayes Geometric Mean (EBGM) and quantile scores from the posterior distribution using the Gamma-Poisson Shrinker (GPS) model to find unusually large cell counts in large, sparse contingency tables. Can be used to find unusually high reporting rates of adverse events associated with products. In general, can be used to mine any database where the co-occurrence of two variables or items is of interest. Also calculates relative and proportional reporting ratios. Builds on the work of the 'PhViD' package, from which much of the code is derived. Some of the added features include stratification to adjust for confounding variables and data squashing to improve computational efficiency. Now includes an implementation of the EM algorithm for hyperparameter estimation loosely derived from the 'mederrRank' package.
Author: John Ihrie [cre, aut], Travis Canida [aut], Ismaïl Ahmed [ctb] (author of 'PhViD' package (derived code)), Antoine Poncet [ctb] (author of 'PhViD'), Sergio Venturini [ctb] (author of 'mederrRank' package (derived code)), Jessica Myers [ctb] (author of 'mederrRank')
Maintainer: John Ihrie <John.Ihrie@fda.hhs.gov>

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Package SparkR updated to version 2.4.2 with previous version 2.4.1 dated 2019-04-04

Title: R Front End for 'Apache Spark'
Description: Provides an R Front end for 'Apache Spark' <https://spark.apache.org>.
Author: Shivaram Venkataraman [aut, cre], Xiangrui Meng [aut], Felix Cheung [aut], The Apache Software Foundation [aut, cph]
Maintainer: Shivaram Venkataraman <shivaram@cs.berkeley.edu>

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Package geojsonio updated to version 0.7.0 with previous version 0.6.0 dated 2018-03-30

Title: Convert Data from and to 'GeoJSON' or 'TopoJSON'
Description: Convert data to 'GeoJSON' or 'TopoJSON' from various R classes, including vectors, lists, data frames, shape files, and spatial classes. 'geojsonio' does not aim to replace packages like 'sp', 'rgdal', 'rgeos', but rather aims to be a high level client to simplify conversions of data from and to 'GeoJSON' and 'TopoJSON'.
Author: Scott Chamberlain [aut, cre], Andy Teucher [aut]
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

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Package BEDMatrix updated to version 1.5.0 with previous version 1.4.1 dated 2018-08-06

Title: Extract Genotypes from a PLINK .bed File
Description: A matrix-like data structure that allows for efficient, convenient, and scalable subsetting of binary genotype/phenotype files generated by PLINK (<https://www.cog-genomics.org/plink2>), the whole genome association analysis toolset, without loading the entire file into memory.
Author: Alexander Grueneberg [aut, cre], Lian Lian [ctb], Gustavo de los Campos [ctb]
Maintainer: Alexander Grueneberg <alexander.grueneberg@googlemail.com>

Diff between BEDMatrix versions 1.4.1 dated 2018-08-06 and 1.5.0 dated 2019-04-25

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Package rmumps updated to version 5.1.2-6 with previous version 5.1.2-5 dated 2018-12-18

Title: Wrapper for MUMPS Library
Description: Some basic features of MUMPS (Multifrontal Massively Parallel sparse direct Solver) are wrapped in a class whose methods can be used for sequentially solving a sparse linear system (symmetric or not) with one or many right hand sides (dense or sparse). There is a possibility to do separately symbolic analysis, LU (or LDL^t) factorization and system solving. Third part ordering libraries are included and can be used: PORD, METIS, SCOTCH. MUMPS method was first described in Amestoy et al. (2001) <doi:10.1137/S0895479899358194> and Amestoy et al. (2006) <doi:10.1016/j.parco.2005.07.004>.
Author: Serguei Sokol [aut, cre], Emmanuel Agullo [ctb], Patrick Amestoy [ctb], Maurice Bremond [ctb], Alfredo Buttari [ctb], Philippe Combes [ctb], Marie Durand [ctb], Aurelia Fevre [ctb], Abdou Guermouche [ctb], Guillaume Joslin [ctb], Jacko Koster [ctb], Jean-Yves L'Excellent [ctb], Stephane Pralet [ctb], Chiara Puglisi [ctb], Francois-Henry Rouet [ctb], Wissam Sid-Lakhdar [ctb], Tzvetomila Slavova [ctb], Bora Ucar [ctb], Clement Weisbecker [ctb], Juergen Schulze [ctb], George Karypis [ctb], Douglas C. Schmidt [ctb], Isamu Hasegawa [ctb], Alexander Chemeris [ctb], Makoto Matsumoto [ctb], Takuji Nishimura [ctb], Francois Pellegrini [ctb], David Goudin [ctb], Pascal Henon [ctb], Pierre Ramet [ctb], Sebastien Fourestier [ctb], Jun-Ho Her [ctb], Cedric Chevalier [ctb], Timothy A. Davis [ctb], Iain S. Duff [ctb], John K. Reid [ctb], Richard Stallman [ctb], Samuel Thibault [ctb]
Maintainer: Serguei Sokol <sokol@insa-toulouse.fr>

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Package pedquant updated to version 0.1.1 with previous version 0.1.0 dated 2019-03-15

Title: Public Economic Data and Quantitative Analysis
Description: Provides an interface to access public economic and financial data for economic research and quantitative analysis. The data sources including NBS, FRED, Yahoo Finance, 163 Finance and etc.
Author: Shichen Xie [aut, cre]
Maintainer: Shichen Xie <xie@shichen.name>

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Package mombf updated to version 2.2.2 with previous version 2.2.1 dated 2019-04-08

Title: Bayesian Model Selection and Averaging for Non-Local and Local Priors
Description: Bayesian model selection and averaging for regression and mixtures for non-local and selected local priors.
Author: David Rossell, John D. Cook, Donatello Telesca, P. Roebuck
Maintainer: David Rossell <rosselldavid@gmail.com>

Diff between mombf versions 2.2.1 dated 2019-04-08 and 2.2.2 dated 2019-04-25

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Package landscapemetrics updated to version 1.1 with previous version 1.0 dated 2019-03-15

Title: Landscape Metrics for Categorical Map Patterns
Description: Calculates landscape metrics for categorical landscape patterns in a tidy workflow. 'landscapemetrics' reimplements the most common metrics from 'FRAGSTATS' (<https://www.umass.edu/landeco/research/fragstats/fragstats.html>) and new ones from the current literature on landscape metrics. This package supports 'raster' spatial objects and takes RasterLayer, RasterStacks, RasterBricks or lists of RasterLayer from the 'raster' package as input arguments. It further provides utility functions to visualize patches, select metrics and building blocks to develop new metrics.
Author: Maximillian H.K. Hesselbarth [aut, cre] (<https://orcid.org/0000-0003-1125-9918>), Marco Sciaini [aut] (<https://orcid.org/0000-0002-3042-5435>), Jakub Nowosad [aut] (<https://orcid.org/0000-0002-1057-3721>), Sebastian Hanss [aut] (<https://orcid.org/0000-0002-3990-4897>), Laura J. Graham [ctb] (Input on package structure), Jeffrey Hollister [ctb] (Input on package structure), Kimberly A. With [ctb] (Input on package structure), Florian Privé [ctb] (Original author of underlying C++ code for get_nearestneighbour() function), Jeremy VanDerWal [ctb] (Original author of underlying C code for get_patches() function), Matt Strimas-Mackey [ctb] (Bugfix in sample_metrics())
Maintainer: Maximillian H.K. Hesselbarth <maximilian.hesselbarth@uni-goettingen.de>

Diff between landscapemetrics versions 1.0 dated 2019-03-15 and 1.1 dated 2019-04-25

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 landscapemetrics-1.1/landscapemetrics/R/lsm_c_pd.R                                   |  314 +--
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 landscapemetrics-1.1/landscapemetrics/R/lsm_c_shape_cv.R                             |  302 +--
 landscapemetrics-1.1/landscapemetrics/R/lsm_c_shape_mn.R                             |  302 +--
 landscapemetrics-1.1/landscapemetrics/R/lsm_c_shape_sd.R                             |  302 +--
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 landscapemetrics-1.1/landscapemetrics/R/lsm_l_contig_sd.R                            |  314 +--
 landscapemetrics-1.1/landscapemetrics/R/lsm_l_core_cv.R                              |  356 +--
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 landscapemetrics-1.1/landscapemetrics/R/lsm_l_core_sd.R                              |  354 +--
 landscapemetrics-1.1/landscapemetrics/R/lsm_l_dcad.R                                 |  374 ++--
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 landscapemetrics-1.1/landscapemetrics/R/lsm_l_dcore_sd.R                             |  360 +--
 landscapemetrics-1.1/landscapemetrics/R/lsm_l_division.R                             |  306 +--
 landscapemetrics-1.1/landscapemetrics/R/lsm_l_ed.R                                   |  346 +--
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 landscapemetrics-1.1/landscapemetrics/R/lsm_l_enn_sd.R                               |  318 +--
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 landscapemetrics-1.1/landscapemetrics/R/lsm_l_gyrate_sd.R                            |  306 +--
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 landscapemetrics-1.1/landscapemetrics/R/lsm_l_pafrac.R                               |  380 ++--
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 landscapemetrics-1.1/landscapemetrics/R/lsm_l_te.R                                   |  376 ++--
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 landscapemetrics-1.1/landscapemetrics/tests/testthat/test-construct-buffer.R         |   48 
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 landscapemetrics-1.1/landscapemetrics/tests/testthat/test-get-boundaries.R           |   87 
 landscapemetrics-1.1/landscapemetrics/tests/testthat/test-get-circumscribungcircle.R |  131 -
 landscapemetrics-1.1/landscapemetrics/tests/testthat/test-get-nearestneighbour.R     |   51 
 landscapemetrics-1.1/landscapemetrics/tests/testthat/test-get-unique-values.R        |  174 +
 landscapemetrics-1.1/landscapemetrics/tests/testthat/test-list-lsm.R                 |  140 +
 landscapemetrics-1.1/landscapemetrics/tests/testthat/test-lsm-c-ai.R                 |   58 
 landscapemetrics-1.1/landscapemetrics/tests/testthat/test-lsm-c-iji.R                |   63 
 landscapemetrics-1.1/landscapemetrics/tests/testthat/test-lsm-c-pafrac.R             |   61 
 landscapemetrics-1.1/landscapemetrics/tests/testthat/test-lsm-l-contag.R             |   61 
 landscapemetrics-1.1/landscapemetrics/tests/testthat/test-lsm-l-iji.R                |   63 
 landscapemetrics-1.1/landscapemetrics/tests/testthat/test-lsm-l-pafrac.R             |   61 
 landscapemetrics-1.1/landscapemetrics/tests/testthat/test-raster-to-points.R         |   53 
 landscapemetrics-1.1/landscapemetrics/tests/testthat/test-sample-lsm.R               |  215 +-
 landscapemetrics-1.1/landscapemetrics/tests/testthat/test-show-cores.R               |  100 -
 landscapemetrics-1.1/landscapemetrics/tests/testthat/test-show-lsm.R                 |   83 
 landscapemetrics-1.1/landscapemetrics/tests/testthat/test-show-patches.R             |   74 
 landscapemetrics-1.1/landscapemetrics/tests/testthat/test-spatialize-lsm.R           |only
 landscapemetrics-1.1/landscapemetrics/tests/testthat/test-window-lsm.R               |   77 
 211 files changed, 28769 insertions(+), 26853 deletions(-)

More information about landscapemetrics at CRAN
Permanent link

New package PREPShiny with initial version 0.1.0
Package: PREPShiny
Type: Package
Title: Interactive Document for Preprocessing the Dataset
Version: 0.1.0
Author: Kartikeya Bolar
Maintainer: Kartikeya Bolar <kartikeya.bolar@tapmi.edu.in>
Description: An interactive document for preprocessing the dataset using 'rmarkdown' and 'shiny' packages. Runtime examples are provided in the package function as well as at <https://analyticmodels.shinyapps.io/PREPShiny/>.
License: GPL-2
Encoding: UTF-8
LazyData: TRUE
Depends: R (>= 3.0.3)
Imports: shiny,rmarkdown,psycho,dplyr,datasets
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2019-04-19 19:51:01 UTC; KARTIKEYA
Repository: CRAN
Date/Publication: 2019-04-25 12:30:03 UTC

More information about PREPShiny at CRAN
Permanent link

Package nonmemica updated to version 0.9.0 with previous version 0.8.6 dated 2019-02-04

Title: Create and Evaluate NONMEM Models in a Project Context
Description: Systematically creates and modifies NONMEM(R) control streams. Harvests NONMEM output, builds run logs, creates derivative data, generates diagnostics. NONMEM (ICON Development Solutions <http://www.iconplc.com/>) is software for nonlinear mixed effects modeling. See 'package?nonmemica'.
Author: Tim Bergsma
Maintainer: Tim Bergsma <bergsmat@gmail.com>

Diff between nonmemica versions 0.8.6 dated 2019-02-04 and 0.9.0 dated 2019-04-25

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 man/updated.Rd                 |    4 
 man/updated.character.Rd       |    4 
 man/updated.numeric.Rd         |    4 
 man/upper-set-.model.Rd        |    4 
 man/upper-set.Rd               |    4 
 man/upper.Rd                   |    4 
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 man/xpath.Rd                   |   10 +
 164 files changed, 1285 insertions(+), 221 deletions(-)

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New package MLDAShiny with initial version 0.1.0
Package: MLDAShiny
Type: Package
Title: Interactive Document for Working with Discriminant Analysis
Version: 0.1.0
Author: Kartikeya Bolar
Maintainer: Kartikeya Bolar <kartikeya.bolar@tapmi.edu.in>
Description: An interactive document on the topic of linear discriminant analysis using 'rmarkdown' and 'shiny' packages. Runtime examples are provided in the package function as well as at <https://analyticmodels.shinyapps.io/DiscriminantAnalysisModelling/>.
License: GPL-2
Encoding: UTF-8
LazyData: TRUE
Depends: R (>= 3.0.3)
Imports: shiny,rmarkdown,klaR,MASS,dplyr,datasets,caret,DiscriMiner,e1071,rhandsontable
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2019-04-24 09:27:16 UTC; KARTIKEYA
Repository: CRAN
Date/Publication: 2019-04-25 12:20:02 UTC

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Package encode updated to version 0.3.6 with previous version 0.3.4 dated 2018-03-28

Title: Represent Ordered Lists and Pairs as Strings
Description: Interconverts between ordered lists and compact string notation. Useful for capturing code lists, and pair-wise codes and decodes, for text storage. Analogous to factor levels and labels. Generics encode() and decode() perform interconversion, while codes() and decodes() extract components of an encoding. The function encoded() checks whether something is interpretable as an encoding. If a vector has an encoded 'guide' attribute, as_factor() uses it to coerce to factor.
Author: Tim Bergsma
Maintainer: Tim Bergsma <bergsmat@gmail.com>

Diff between encode versions 0.3.4 dated 2018-03-28 and 0.3.6 dated 2019-04-25

 DESCRIPTION              |    9 ++---
 MD5                      |   32 +++++++++---------
 NAMESPACE                |    2 +
 R/encode.R               |   83 +++++++++++++++++++++++++++++++++++++++++++++++
 man/as_factor.Rd         |only
 man/codes.Rd             |    2 +
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 man/decode.Rd            |    4 ++
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 man/encode.character.Rd  |    4 ++
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 18 files changed, 145 insertions(+), 19 deletions(-)

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Package ukbtools updated to version 0.11.2 with previous version 0.11.1 dated 2019-03-14

Title: Manipulate and Explore UK Biobank Data
Description: A set of tools to create a UK Biobank <http://www.ukbiobank.ac.uk/> dataset from a UKB fileset (.tab, .r, .html), visualize primary demographic data for a sample subset, query ICD diagnoses, retrieve genetic metadata, read and write standard file formats for genetic analyses.
Author: Ken Hanscombe [aut, cre]
Maintainer: Ken Hanscombe <ken.hanscombe@gmail.com>

Diff between ukbtools versions 0.11.1 dated 2019-03-14 and 0.11.2 dated 2019-04-25

 DESCRIPTION                    |   14 +++++++-------
 MD5                            |    8 ++++----
 NEWS.md                        |   13 +++++++++++++
 R/ukb_dataset.R                |    6 +++---
 inst/doc/explore-ukb-data.html |    4 ++--
 5 files changed, 29 insertions(+), 16 deletions(-)

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Package osmdata updated to version 0.1.0 with previous version 0.0.10 dated 2019-03-21

Title: Import 'OpenStreetMap' Data as Simple Features or Spatial Objects
Description: Download and import of 'OpenStreetMap' ('OSM') data as 'sf' or 'sp' objects. 'OSM' data are extracted from the 'Overpass' web server and processed with very fast 'C++' routines for return to 'R'.
Author: Mark Padgham [aut, cre], Bob Rudis [aut], Robin Lovelace [aut], Maëlle Salmon [aut], Andrew Smith [ctb], James Smith [ctb], Marcin Kalicinski [ctb, cph] (Author of included RapidXML code), Finkelstein Noam [ctb, cph] (Author of included stub.R code), Bartnik Lukasz [ctb, cph] (Author of included stub.R code)
Maintainer: Mark Padgham <mark.padgham@email.com>

Diff between osmdata versions 0.0.10 dated 2019-03-21 and 0.1.0 dated 2019-04-25

 DESCRIPTION                      |    9 ++++---
 MD5                              |   44 ++++++++++++++++++++++-----------------
 NAMESPACE                        |    1 
 NEWS.md                          |   10 ++++++++
 R/elevation.R                    |only
 R/get-osmdata.R                  |   16 +++++++-------
 R/getbb.R                        |    6 +++--
 R/opq.R                          |    4 +--
 R/trim-osmdata.R                 |   22 ++++++++-----------
 R/zzz.R                          |    5 ++++
 build/vignette.rds               |binary
 inst/doc/osm-sf-translation.Rmd  |    4 +--
 inst/doc/osm-sf-translation.html |    8 +++----
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 inst/doc/osmdata.html            |    6 ++---
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 tests/testthat/test-trim.R       |    5 ----
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 vignettes/osm-sf-translation.Rmd |    4 +--
 vignettes/osmdata-sc.Rmd         |only
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 26 files changed, 103 insertions(+), 69 deletions(-)

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New package streamDepletr with initial version 0.1.0
Package: streamDepletr
Title: Estimate Streamflow Depletion Due to Groundwater Pumping
Version: 0.1.0
Description: Implementation of analytical models for estimating streamflow depletion due to groundwater pumping, and other related tools. Functions are broadly split into two groups: (1) analytical streamflow depletion models, which estimate streamflow depletion for a single stream reach resulting from groundwater pumping; and (2) depletion apportionment equations, which distribute estimated streamflow depletion among multiple stream reaches within a stream network. See Zipper et al. (2018) <doi:10.1029/2018WR022707> for more information on depletion apportionment equations and Zipper et al. (2019) <doi:10.31223/osf.io/uqbd7> for more information on analytical depletion functions, which combine analytical models and depletion apportionment equations.
Authors@R: c( person("Samuel C.", "Zipper", email = "samzipper@ku.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-8735-5757")), person("Ben", "Kerr", email = "ben@foundryspatial.com", role = "ctb"), person("Tom", "Gleeson", email = "tgleeson@uvic.ca", role = "ctb", comment = c(ORCID = "0000-0001-9493-7707")), person("Qiang", "Li", email = "liqiang1205@gmail.com", role = "rev", comment = c(ORCID = "0000-0003-2221-6905")), person("Foundry Spatial Ltd.", role = "cph") )
Maintainer: Samuel C. Zipper <samzipper@ku.edu>
Copyright: Foundry Spatial Ltd.
URL: https://github.com/samzipper/streamDepletr
BugReports: https://github.com/samzipper/streamDepletr/issues
Depends: R (>= 3.5)
License: BSD_3_clause + file LICENSE
Imports: Rmpfr, dplyr, magrittr
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, dismo, sp, raster, deldir, rgeos, ggplot2, reshape2, sf, scales
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-24 18:43:34 UTC; Sam
Author: Samuel C. Zipper [aut, cre] (<https://orcid.org/0000-0002-8735-5757>), Ben Kerr [ctb], Tom Gleeson [ctb] (<https://orcid.org/0000-0001-9493-7707>), Qiang Li [rev] (<https://orcid.org/0000-0003-2221-6905>), Foundry Spatial Ltd. [cph]
Repository: CRAN
Date/Publication: 2019-04-25 10:40:03 UTC

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New package sigminer with initial version 0.1.9
Package: sigminer
Title: Capture Genomic Variation Signatures using Non-Negative Matrix Factorization
Version: 0.1.9
Authors@R: c( person("Shixiang", "Wang", email = "w_shixiang@163.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-9855-7357")), person("Geoffrey", "Macintyre", role = c("ctb")), person("Xue-Song", "Liu", role = c("ctb")))
Description: Contains functions for identification of copy number signatures (Geoffrey et al. (2018) <doi:10.1038/s41588-018-0179-8>) and mutation signatures (Alexandrov et al. (2018) <doi:10.1038/nature12477>) by non-negative matrix factorization, signature analysis and visualization. It can be used to capture signatures of genomic variation, compare genotype or phenotype features of different signatures and thus uncover the relationship between the mechanism of genomic variation and phenotypes in cancer.
URL: https://github.com/ShixiangWang/sigminer
BugReports: https://github.com/ShixiangWang/sigminer/issues
Depends: R (>= 3.5)
Imports: cluster, corrplot, cowplot, data.table, doParallel, dplyr, flexmix, foreach, ggplot2, maftools, methods, NMF, RColorBrewer, tidyr, magrittr, purrr
biocViews:
Suggests: BSgenome.Hsapiens.UCSC.hg19, cowsay, ggpubr, knitr, rmarkdown, covr, testthat, prettydoc, pheatmap
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-25 08:24:18 UTC; wsx
Author: Shixiang Wang [aut, cre] (<https://orcid.org/0000-0001-9855-7357>), Geoffrey Macintyre [ctb], Xue-Song Liu [ctb]
Maintainer: Shixiang Wang <w_shixiang@163.com>
Repository: CRAN
Date/Publication: 2019-04-25 11:00:03 UTC

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New package MEtest with initial version 1.0
Package: MEtest
Type: Package
Title: A Homogeneity Test under the Presence of Measurement Errors
Version: 1.0
Date: 2019-04-24
Author: DongHyuk Lee, Samiran Sinha
Maintainer: DongHyuk Lee <leedhyuk@gmail.com>
Depends: R (>= 3.2)
Imports: statmod
Description: Provides a function me.test() to test equality of distributions when observations are subject to measurement errors.
License: GPL-3
NeedsCompilation: yes
Packaged: 2019-04-25 03:10:21 UTC; cutri
Repository: CRAN
Date/Publication: 2019-04-25 10:10:03 UTC

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Package cliqueMS updated to version 0.3.1 with previous version 0.3.0 dated 2019-01-30

Title: Annotation of Isotopes, Adducts and Fragmentation Adducts for in-Source LC/MS Metabolomics Data
Description: Annotates data from liquid chromatography coupled to mass spectrometry (LC/MS) metabolomics experiments. Based on a network algorithm (O.Senan, A. Aguilar- Mogas, M. Navarro, O. Yanes, R.Guimerà and M. Sales-Pardo, Metabolomics Conference (2016), Dublin), 'CliqueMS' builds a weighted similarity network where nodes are features and edges are weighted according to the similarity of this features. Then it searches for the most plausible division of the similarity network into cliques (fully connected components). Finally it annotates metabolites within each clique, obtaining for each annotated metabolite the neutral mass and their features, corresponding to isotopes, ionization adducts and fragmentation adducts of that metabolite.
Author: Oriol Senan Campos [aut, cre], Antoni Aguilar-Mogas [aut], Jordi Capellades [aut], Miriam Navarro [aut], Oscar Yanes [aut], Roger Guimerà [aut], Marta Sales-Pardo [aut]
Maintainer: Oriol Senan Campos <oriol.senan@urv.cat>

Diff between cliqueMS versions 0.3.0 dated 2019-01-30 and 0.3.1 dated 2019-04-25

 DESCRIPTION                     |    8 ++++----
 MD5                             |   14 +++++++-------
 NEWS.md                         |    5 +++++
 build/vignette.rds              |binary
 inst/doc/annotate_features.R    |    8 ++++----
 inst/doc/annotate_features.Rmd  |    8 ++++----
 inst/doc/annotate_features.html |   10 +++++-----
 vignettes/annotate_features.Rmd |    8 ++++----
 8 files changed, 33 insertions(+), 28 deletions(-)

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New package BALLI with initial version 0.2.0
Package: BALLI
Type: Package
Title: Expression RNA-Seq Data Analysis Based on Linear Mixed Model
Version: 0.2.0
Author: Kyungtaek Park <qkrrudxor147@snu.ac.kr>
Maintainer: Kyungtaek Park <qkrrudxor147@snu.ac.kr>
Description: Analysis of gene expression RNA-seq data using Bartlett-Adjusted Likelihood-based LInear model (BALLI). Based on likelihood ratio test, it provides comparisons for effect of one or more variables. See Kyungtaek Park (2018) <doi:10.1101/344929> for more information.
Depends: R (>= 2.15.0), edgeR, limma, MASS, parallel, stats, methods
License: GPL
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-24 13:21:01 UTC; KyungtaekPark
Repository: CRAN
Date/Publication: 2019-04-25 10:40:07 UTC

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New package suppdata with initial version 1.1-1
Package: suppdata
Type: Package
Title: Downloading Supplementary Data from Published Manuscripts
Version: 1.1-1
Authors@R: c(person("William D.", "Pearse", email = "will.pearse@gmail.com", role = c("aut", "cre"), comment=c(ORCID="0000-0002-6241-3164")), person("Scott", "Chamberlain", role = "aut", comment=c(ORCID="0000-0003-1444-9135")), person("Daniel", "Nuest", role = "aut", comment=c(ORCID="0000-0002-0024-5046")), person("Ross", "Mounce", role = c("rev"), comment = "Ross Mounce reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/195"), person("Sarah", "Supp", role = c("rev"), comment = "Sarah Supp reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/195"))
Maintainer: William D. Pearse <will.pearse@gmail.com>
Description: Downloads data supplementary materials from manuscripts, using papers' DOIs as references. Facilitates open, reproducible research workflows: scientists re-analyzing published datasets can work with them as easily as if they were stored on their own computer, and others can track their analysis workflow painlessly. The main function suppdata() returns a (temporary) location on the user's computer where the file is stored, making it simple to use suppdata() with standard functions like read.csv().
License: MIT + file LICENSE
URL: https://github.com/ropensci/suppdata
BugReports: https://github.com/ropensci/suppdata
VignetteBuilder: knitr
LazyLoad: yes
Suggests: knitr (>= 1.6), testthat (>= 2.0.0), covr (>= 3.0.1), fulltext (>= 0.1.4.9000)
Imports: httr (>= 1.0.0), xml2 (>= 1.2.0), jsonlite (>= 1.5), rcrossref (>= 0.8.0)
Encoding: UTF-8
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-04-24 18:34:25 UTC; will
Author: William D. Pearse [aut, cre] (<https://orcid.org/0000-0002-6241-3164>), Scott Chamberlain [aut] (<https://orcid.org/0000-0003-1444-9135>), Daniel Nuest [aut] (<https://orcid.org/0000-0002-0024-5046>), Ross Mounce [rev] (Ross Mounce reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/195), Sarah Supp [rev] (Sarah Supp reviewed the package for rOpenSci, see https://github.com/ropensci/onboarding/issues/195)
Repository: CRAN
Date/Publication: 2019-04-25 09:30:02 UTC

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New package EMSNM with initial version 1.0
Package: EMSNM
Type: Package
Title: EM Algorithm for Sigmoid Normal Model
Version: 1.0
Date: 2019-04-19
Author: Linsui Deng <denglinsui@gmail.com>
Maintainer: Linsui Deng <denglinsui@gmail.com>
Description: It provides a method based on EM algorithm to estimate the parameter of a mixture model, Sigmoid-Normal Model, where the samples come from several normal distributions (also call them subgroups) whose mean is determined by co-variable Z and coefficient alpha while the variance are homogeneous. Meanwhile, the subgroup each item belongs to is determined by co-variables X and coefficient eta through Sigmoid link function which is the extension of Logistic Link function. It uses bootstrap to estimate the standard error of parameters. When sample is indeed separable, removing estimation with abnormal sigma, the estimation of alpha is quite well. I used this method to explore the subgroup structure of HIV patients and it can be used in other domains where exists subgroup structure.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2019-04-24 16:49:30 UTC; huihui
Repository: CRAN
Date/Publication: 2019-04-25 09:10:03 UTC

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New package CramTest with initial version 1.5
Package: CramTest
Type: Package
Title: Univariate Cramer Test on Two Samples of Data
Version: 1.5
Date: 2019-04-24
Author: Alison Telford
Maintainer: Alison Telford <atelford7@gmail.com>
Description: Performs the univariate two-sample Cramer test to identify differences between two groups. This package provides a faster method for calculating the p-value. For further information, refer to "Properties, Advantages and a Faster p-value Calculation of the Cramer test" by Telford et al. (submitted for review).
License: GPL (>= 3)
Depends: fExtremes
Imports: Rcpp (>= 0.11.00)
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2019-04-24 19:02:16 UTC; Ali
Repository: CRAN
Date/Publication: 2019-04-25 09:30:06 UTC

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Package photobiology updated to version 0.9.27 with previous version 0.9.26 dated 2019-02-12

Title: Photobiological Calculations
Description: Definitions of classes, methods, operators and functions for use in photobiology and radiation meteorology and climatology. Calculation of effective (weighted) and not-weighted irradiances/doses, fluence rates, transmittance, reflectance, absorptance, absorbance and diverse ratios and other derived quantities from spectral data. Local maxima and minima. Conversion between energy- and photon-based units. Wavelength interpolation. Astronomical calculations related solar angles and day length. Colours and vision. This package is part of the 'r4photobiology' suite, Aphalo P. J. (2015) <doi:10.19232/uv4pb.2015.1.14>.
Author: Pedro J. Aphalo [aut, cre] (<https://orcid.org/0000-0003-3385-972X>), Titta K. Kotilainen [ctb] (<https://orcid.org/0000-0002-2822-9734>), Glenn Davis [ctb]
Maintainer: Pedro J. Aphalo <pedro.aphalo@helsinki.fi>

Diff between photobiology versions 0.9.26 dated 2019-02-12 and 0.9.27 dated 2019-04-25

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 MD5                                |  121 ++--
 NEWS                               |   14 
 R/meeus.r                          |   32 -
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 R/spct.operators.r                 |    2 
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 vignettes/userguide1-intro.Rmd     |    2 
 62 files changed, 1698 insertions(+), 984 deletions(-)

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Package icesTAF updated to version 3.0-0 with previous version 2.3-0 dated 2019-04-08

Title: Functions to Support the ICES Transparent Assessment Framework
Description: Functions to support the ICES Transparent Assessment Framework <http://taf.ices.dk> to organize data, methods, and results used in ICES assessments. ICES is an organization facilitating international collaboration in marine science.
Author: Arni Magnusson [aut, cre], Colin Millar [aut], Alexandros Kokkalis [ctb]
Maintainer: Arni Magnusson <arni.magnusson@ices.dk>

Diff between icesTAF versions 2.3-0 dated 2019-04-08 and 3.0-0 dated 2019-04-25

 icesTAF-2.3-0/icesTAF/R/utf8.to-latin1.R     |only
 icesTAF-3.0-0/icesTAF/DESCRIPTION            |   11 +--
 icesTAF-3.0-0/icesTAF/MD5                    |   54 +++++++++--------
 icesTAF-3.0-0/icesTAF/NAMESPACE              |    4 +
 icesTAF-3.0-0/icesTAF/NEWS                   |   19 ++++++
 icesTAF-3.0-0/icesTAF/R/draft.data.R         |   15 ++--
 icesTAF-3.0-0/icesTAF/R/draft.software.R     |    8 --
 icesTAF-3.0-0/icesTAF/R/ds.package.R         |    2 
 icesTAF-3.0-0/icesTAF/R/icesTAF-package.R    |    3 
 icesTAF-3.0-0/icesTAF/R/period.R             |only
 icesTAF-3.0-0/icesTAF/R/process.bib.R        |   47 +++++++++++++--
 icesTAF-3.0-0/icesTAF/R/taf.bootstrap.R      |    5 -
 icesTAF-3.0-0/icesTAF/R/taf.library.R        |   69 +++++++++-------------
 icesTAF-3.0-0/icesTAF/R/taf.png.R            |   15 ++--
 icesTAF-3.0-0/icesTAF/R/taf.skeleton.R       |   14 +---
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 icesTAF-3.0-0/icesTAF/R/zoom.R               |   83 ++++++++++++++++++---------
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 icesTAF-3.0-0/icesTAF/man/taf.png.Rd         |   15 ++--
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 icesTAF-3.0-0/icesTAF/man/zoom.Rd            |   42 +++++++++----
 30 files changed, 297 insertions(+), 204 deletions(-)

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New package DataViz with initial version 0.2
Package: DataViz
Type: Package
Title: Data Visualisation Using an HTML Page and 'D3.js'
Version: 0.2
Date: 2019-04-23
Author: Timothy Bell
Maintainer: Timothy Bell <horia.yeb@gmail.com>
Description: Gives access to data visualisation methods that are relevant from the statistician's point of view. Using 'D3''s existing data visualisation tools to empower R language and environment. The throw chart method is a line chart used to illustrate paired data sets (such as before-after, male-female).
License: GPL (>= 2)
Imports: Rcpp (>= 1.0.0)
LinkingTo: Rcpp
Depends: tibble
LazyData: true
NeedsCompilation: yes
Packaged: 2019-04-23 16:06:44 UTC; Usr
Repository: CRAN
Date/Publication: 2019-04-25 08:30:02 UTC

More information about DataViz at CRAN
Permanent link

New package AzureKusto with initial version 1.0.1
Package: AzureKusto
Title: Interface to 'Kusto'/'Azure Data Explorer'
Version: 1.0.1
Authors@R: c( person("Hong", "Ooi", , "hongooi@microsoft.com", role = c("aut", "cre")), person("Alex", "Kyllo", , "jekyllo@microsoft.com", role = "aut"), person("dbplyr development team", role="cph", comment="Original framework for dplyr/database interface"), person("Microsoft", role = "cph") )
Description: An interface to 'Azure Data Explorer', also known as 'Kusto', a fast, highly scalable data exploration service from Microsoft: <https://azure.microsoft.com/en-us/services/data-explorer/>. Includes 'DBI' and 'dplyr' interfaces, with the latter modelled after the 'dbplyr' package, whereby queries are translated from R into the native 'KQL' query language and executed lazily. On the admin side, the package extends the object framework provided by 'AzureRMR' to support creation and deletion of databases, and management of database principals.
URL: https://github.com/cloudyr/AzureKusto
BugReports: https://github.com/cloudyr/AzureKusto/issues
License: MIT + file LICENSE
Encoding: UTF-8
VignetteBuilder: knitr
Depends: R (>= 3.3)
Imports: rlang, methods, utils, httr (>= 1.3), jsonlite, R6, openssl, AzureAuth, AzureRMR (>= 2.0.0), tibble, dplyr, tidyselect (>= 0.2.4), DBI (>= 1.0.0)
Suggests: bit64, knitr, testthat, AzureGraph, AzureStor (>= 2.0.0), rmarkdown
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-04-23 21:36:58 UTC; hongo
Author: Hong Ooi [aut, cre], Alex Kyllo [aut], dbplyr development team [cph] (Original framework for dplyr/database interface), Microsoft [cph]
Maintainer: Hong Ooi <hongooi@microsoft.com>
Repository: CRAN
Date/Publication: 2019-04-25 08:50:08 UTC

More information about AzureKusto at CRAN
Permanent link

Package umx updated to version 2.10.0 with previous version 2.9.9 dated 2019-01-18

Title: Structural Equation and Twin Modeling in R
Description: Quickly create, run, and report structural equation and twin models. See '?umx' for help, and umx_open_CRAN_page("umx") for NEWS.
Author: Timothy C Bates [aut, cre] (<https://orcid.org/0000-0002-1153-9007>)
Maintainer: Timothy C Bates <timothy.c.bates@gmail.com>

Diff between umx versions 2.9.9 dated 2019-01-18 and 2.10.0 dated 2019-04-25

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New package tidymv with initial version 2.1.0
Package: tidymv
Type: Package
Title: Tidy Model Visualisation for Generalised Additive Models
Version: 2.1.0
Date: 2019-04-23
Authors@R: person("Stefano", "Coretta", email = paste0("stefano.coretta", "@", "gmail.com"), role = c("aut", "cre"))
Description: Provides functions for visualising generalised additive models and getting predicted values using tidy tools from the 'tidyverse' packages.
URL: https://github.com/stefanocoretta/tidymv
BugReports: https://github.com/stefanocoretta/tidymv/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: cowplot, dplyr, ggplot2, itsadug, magrittr, mgcv, rlang, tibble, tidyr
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Language: en_GB
NeedsCompilation: no
Packaged: 2019-04-23 13:52:10 UTC; stefano
Author: Stefano Coretta [aut, cre]
Maintainer: Stefano Coretta <stefano.coretta@gmail.com>
Repository: CRAN
Date/Publication: 2019-04-25 08:00:25 UTC

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Package excerptr updated to version 2.0.0 with previous version 1.4.1 dated 2018-06-03

Title: Excerpt Structuring Comments from Your Code File and Set a Table of Contents
Description: This is an R interface to the python package 'excerpts' (<https://pypi.python.org/pypi/excerpts>).
Author: Andreas Dominik Cullmann [aut, cre]
Maintainer: Andreas Dominik Cullmann <fvafrcu@mailbox.org>

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Package encryptr updated to version 0.1.3 with previous version 0.1.2 dated 2019-03-25

Title: Easily Encrypt and Decrypt Data Frame/Tibble Columns or Files using RSA Public/Private Keys
Description: It is important to ensure that sensitive data is protected. This straightforward package is aimed at the end-user. Strong RSA encryption using a public/private key pair is used to encrypt data frame or tibble columns. A public key can be shared to allow others to encrypt data to be sent to you. This is particularly aimed a healthcare settings so patient data can be pseudonymised.
Author: Cameron Fairfield [aut], Riinu Ots [aut], Stephen Knight [aut], Tom Drake [aut], Ewen Harrison [aut, cre]
Maintainer: Ewen Harrison <ewen.harrison@ed.ac.uk>

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Package CoRpower updated to version 1.0.1 with previous version 1.0.0 dated 2018-10-06

Title: Power Calculations for Assessing Correlates of Risk in Clinical Efficacy Trials
Description: Calculates power for assessment of intermediate biomarker responses as correlates of risk in the active treatment group in clinical efficacy trials, as described in Gilbert, Janes, and Huang, Power/Sample Size Calculations for Assessing Correlates of Risk in Clinical Efficacy Trials (2016, Statistics in Medicine). The methods differ from past approaches by accounting for the level of clinical treatment efficacy overall and in biomarker response subgroups, which enables the correlates of risk results to be interpreted in terms of potential correlates of efficacy/protection. The methods also account for inter-individual variability of the observed biomarker response that is not biologically relevant (e.g., due to technical measurement error of the laboratory assay used to measure the biomarker response), which is important because power to detect a specified correlate of risk effect size is heavily affected by the biomarker's measurement error. The methods can be used for a general binary clinical endpoint model with a univariate dichotomous, trichotomous, or continuous biomarker response measured in active treatment recipients at a fixed timepoint after randomization, with either case-cohort Bernoulli sampling or case-control without-replacement sampling of the biomarker (a baseline biomarker is handled as a trivial special case). In a specified two-group trial design, the computeN() function can initially be used for calculating additional requisite design parameters pertaining to the target population of active treatment recipients observed to be at risk at the biomarker sampling timepoint. Subsequently, the power calculation employs an inverse probability weighted logistic regression model fitted by the tps() function in the 'osDesign' package. Power results as well as the relationship between the correlate of risk effect size and treatment efficacy can be visualized using various plotting functions. To link power calculations for detecting a correlate of risk and a correlate of treatment efficacy, a baseline immunogenicity predictor (BIP) can be simulated according to a specified classification rule (for dichotomous or trichotomous BIPs) or correlation with the biomarker response (for continuous BIPs), then outputted along with biomarker response data under assignment to treatment, and clinical endpoint data for both treatment and placebo groups.
Author: Stephanie Wu [aut], Michal Juraska [aut, cre], Peter Gilbert [aut], Yunda Huang [aut]
Maintainer: Michal Juraska <mjuraska@fredhutch.org>

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Package rstatscn updated to version 1.1.3 with previous version 1.1.1 dated 2016-07-20

Title: R Interface for China National Data
Description: R interface for china national data <http://data.stats.gov.cn/>, some convenient functions for accessing the national data are provided.
Author: Xuehui YANG
Maintainer: Xuehui YANG <jianghang@bagualu.net>

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Package spec updated to version 0.1.7 with previous version 0.1.6 dated 2019-02-04

Title: A Data Specification Format and Interface
Description: Creates a data specification that describes the columns of a table (data.frame). Provides methods to read, write, and update the specification. Checks whether a table matches its specification. See specification.data.frame(),read.spec(), write.spec(), as.csv.spec(), respecify.character(), and %matches%.data.frame().
Author: Tim Bergsma
Maintainer: Tim Bergsma <bergsmat@gmail.com>

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Package rqdatatable updated to version 1.1.5 with previous version 1.1.4 dated 2019-02-25

Title: 'rquery' for 'data.table'
Description: Implements the 'rquery' piped Codd-style query algebra using 'data.table'. This allows for a high-speed in memory implementation of Codd-style data manipulation tools.
Author: John Mount [aut, cre], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

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Package ROptEst updated to version 1.2.1 with previous version 1.2.0 dated 2019-04-07

Title: Optimally Robust Estimation
Description: Optimally robust estimation in general smoothly parameterized models using S4 classes and methods.
Author: Matthias Kohl [cre, cph], Mykhailo Pupashenko [ctb] (contributed wrapper functions for diagnostic plots), Gerald Kroisandt [ctb] (contributed testing routines), Peter Ruckdeschel [aut, cph]
Maintainer: Matthias Kohl <Matthias.Kohl@stamats.de>

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Package RobAStBase updated to version 1.2.1 with previous version 1.2.0 dated 2019-04-05

Title: Robust Asymptotic Statistics
Description: Base S4-classes and functions for robust asymptotic statistics.
Author: Matthias Kohl [cre, cph, aut], Peter Ruckdeschel [aut, cph], Mykhailo Pupashenko [ctb] (contributed wrapper functions for diagnostic plots), Gerald Kroisandt [ctb] (contributed testing routines), R Core Team [ctb, cph] (for source file 'format.perc')
Maintainer: Matthias Kohl <Matthias.Kohl@stamats.de>

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Package mvSLOUCH updated to version 2.0.5 with previous version 2.0.4 dated 2019-04-11

Title: Multivariate Stochastic Linear Ornstein-Uhlenbeck Models for Phylogenetic Comparative Hypotheses
Description: Fits multivariate Ornstein-Uhlenbeck types of models to continues trait data from species related by a common evolutionary history. See K. Bartoszek, J, Pienaar, P. Mostad, S. Andersson, T. F.Hansen (2012) <doi:10.1016/j.jtbi.2012.08.005>.
Author: Krzysztof Bartoszek <krzbar@protonmail.ch>
Maintainer: Krzysztof Bartoszek <krzbar@protonmail.ch>

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Package inum updated to version 1.0-1 with previous version 1.0-0 dated 2017-12-12

Title: Interval and Enum-Type Representation of Vectors
Description: Enum-type representation of vectors and representation of intervals, including a method of coercing variables in data frames.
Author: Torsten Hothorn [aut, cre]
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

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Package finch updated to version 0.3.0 with previous version 0.2.0 dated 2018-01-25

Title: Parse Darwin Core Files
Description: Parse and create Darwin Core (<http://rs.tdwg.org/dwc/>) Simple and Archives. Functionality includes reading and parsing all the files in a Darwin Core Archive, including the datasets and metadata; read and parse simple Darwin Core files; and validation of Darwin Core Archives.
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>)
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

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Package dexter updated to version 0.8.5 with previous version 0.8.4 dated 2019-01-02

Title: Data Management and Analysis of Tests
Description: A system for the management, assessment, and psychometric analysis of data from educational and psychological tests. Developed at Cito, The Netherlands, with subsidy from the Dutch Ministry of Education, Culture, and Science.
Author: Gunter Maris, Timo Bechger, Jesse Koops, Ivailo Partchev
Maintainer: Ivailo Partchev <partchev@gmail.com>

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 dexter-0.8.5/dexter/man/fit_enorm.Rd                          |    3 
 dexter-0.8.5/dexter/vignettes/data_management.Rmd             |   10 
 26 files changed, 401 insertions(+), 289 deletions(-)

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Package wrangle updated to version 0.5.2 with previous version 0.5.1 dated 2019-02-04

Title: A Systematic Data Wrangling Idiom
Description: Supports systematic scrutiny, modification, and integration of data. The function status() counts rows that have missing values in grouping columns (returned by na() ), have non-unique combinations of grouping columns (returned by dup() ), and that are not locally sorted (returned by unsorted() ). Functions enumerate() and itemize() give sorted unique combinations of columns, with or without occurrence counts, respectively. Function ignore() drops columns in x that are present in y, and informative() drops columns in x that are entirely NA; constant() returns values that are constant, given a key. Data that have defined unique combinations of grouping values behave more predictably during merge operations.
Author: Tim Bergsma
Maintainer: Tim Bergsma <bergsmat@gmail.com>

Diff between wrangle versions 0.5.1 dated 2019-02-04 and 0.5.2 dated 2019-04-25

 DESCRIPTION                   |    7 ++---
 MD5                           |   50 +++++++++++++++++++++---------------------
 NAMESPACE                     |    4 +++
 R/wrangle.R                   |   30 +++++++++++++++++++++++++
 man/detect.Rd                 |    4 +++
 man/dup.Rd                    |    2 +
 man/dup.grouped_df.Rd         |    3 ++
 man/dupGroups.Rd              |    3 ++
 man/dupGroups.grouped_df.Rd   |    3 ++
 man/enumerate.Rd              |    4 +++
 man/informative.Rd            |    2 +
 man/informative.data.frame.Rd |    3 ++
 man/itemize.Rd                |    4 +++
 man/key.Rd                    |    3 ++
 man/key.grouped_df.Rd         |    3 ++
 man/na.Rd                     |    2 +
 man/na.grouped_df.Rd          |    3 ++
 man/naGroups.Rd               |    3 ++
 man/naGroups.grouped_df.Rd    |    3 ++
 man/static.Rd                 |    4 +++
 man/status.Rd                 |    3 ++
 man/status.grouped_df.Rd      |    2 +
 man/unsorted.Rd               |    2 +
 man/unsorted.grouped_df.Rd    |    2 +
 man/weak.Rd                   |    2 +
 man/weak.grouped_df.Rd        |    3 ++
 26 files changed, 125 insertions(+), 29 deletions(-)

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