Wed, 18 Jul 2018

New package rzeit2 with initial version 0.1.0
Package: rzeit2
Type: Package
Title: Client for the ZEIT ONLINE Content API
Version: 0.1.0
Authors@R: person("Jan", "Dix", email = "jan.dix@uni-konstanz.de", role = c("aut", "cre"))
Description: Interface to gather newspaper articles from 'DIE ZEIT' and 'ZEIT ONLINE', based on a multilevel query <http://developer.zeit.de/>. A personal API key is required for usage.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.2.0)
BugReports: https://github.com/jandix/rzeit2/issues
LazyData: true
RoxygenNote: 6.0.1
Imports: anytime, ggplot2, httr, jsonlite, rvest, stringr, xml2
Suggests: dplyr, ggthemes, knitr, rmarkdown, robotstxt, tidytext
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-07-11 08:04:20 UTC; jan
Author: Jan Dix [aut, cre]
Maintainer: Jan Dix <jan.dix@uni-konstanz.de>
Repository: CRAN
Date/Publication: 2018-07-18 23:00:03 UTC

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Package microplot updated to version 1.0-41 with previous version 1.0-40 dated 2018-07-15

Title: Microplots (Sparklines) in 'LaTeX', 'Word', 'HTML', 'Excel'
Description: The microplot function writes a set of R graphics files to be used as microplots (sparklines) in tables in either 'LaTeX', 'HTML', 'Word', or 'Excel' files. For 'LaTeX', we provide methods for the Hmisc::latex() generic function to construct 'latex' tabular environments which include the graphs. These can be used directly with the operating system 'pdflatex' or 'latex' command, or by using one of 'Sweave', 'knitr', 'rmarkdown', or 'Emacs org-mode' as an intermediary. For 'MS Word', the msWord() function uses the 'flextable' package to construct 'Word' tables which include the graphs. There are several distinct approaches for constructing HTML files. The simplest is to use the msWord() function with argument filetype="html". Alternatively, use either 'Emacs org-mode' or the htmlTable::htmlTable() function to construct an 'HTML' file containing tables which include the graphs. See the documentation for our as.htmlimg() function. For 'Excel' use on 'Windows', the file examples/irisExcel.xls includes 'VBA' code which brings the individual panels into individual cells in the spreadsheet. Examples in the examples and demo subdirectories are shown with 'lattice' graphics, 'ggplot2' graphics, and 'base' graphics. Examples for 'LaTeX' include 'Sweave' (both 'LaTeX'-style and 'Noweb'-style), 'knitr', 'emacs org-mode', and 'rmarkdown' input files and their 'pdf' output files. Examples for 'HTML' include 'org-mode' and 'Rmd' input files and their webarchive 'HTML' output files. In addition, the as.orgtable() function can display a data.frame in an 'org-mode' document. The examples for 'MS Word' (with either filetype="docx" or filetype="html") work with all operating systems. The package does not require the installation of 'LaTeX' or 'MS Word' to be able to write '.tex' or '.docx' files.
Author: Richard M. Heiberger, with contributions from Karen Byron and Nooreen Dabbish.
Maintainer: Richard M. Heiberger <rmh@temple.edu>

Diff between microplot versions 1.0-40 dated 2018-07-15 and 1.0-41 dated 2018-07-18

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Package LS2Wstat updated to version 2.1-1 with previous version 2.1 dated 2018-05-21

Title: A Multiscale Test of Spatial Stationarity for LS2W Processes
Description: Wavelet-based methods for testing stationarity and quadtree segmenting of images, see Taylor et al (2014) <doi:10.1080/00401706.2013.823890>.
Author: Sarah Taylor [aut], Matt Nunes [aut, cre], Idris Eckley [ctb, ths]
Maintainer: Matt Nunes <nunesrpackages@gmail.com>

Diff between LS2Wstat versions 2.1 dated 2018-05-21 and 2.1-1 dated 2018-07-18

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New package IntNMF with initial version 1.2.0
Package: IntNMF
Type: Package
Title: Integrative Clustering of Multiple Genomic Dataset
Version: 1.2.0
Date: 2018-07-17
Author: Prabhakar Chalise, Rama Raghavan, Brooke Fridley
Maintainer: Prabhakar Chalise <pchalise@kumc.edu>
Description: Carries out integrative clustering analysis using multiple types of genomic dataset using integrative Non-negative Matrix factorization.
License: GPL-2
Depends: R (>= 3.5), MASS, NMF, mclust, cluster, InterSIM
NeedsCompilation: no
Packaged: 2018-07-18 15:39:55 UTC; pchalise
Repository: CRAN
Date/Publication: 2018-07-18 22:40:19 UTC
RoxygenNote: 6.0.1

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New package binman with initial version 0.1.1
Package: binman
Title: A Binary Download Manager
Version: 0.1.1
Authors@R: c( person("John", "Harrison", , "johndharrison0@gmail.com", role = "aut", comment = "original author"), person("Ju Yeong", "Kim", , "jkim2345@fredhutch.org", role = "cre", comment = "rOpenSci maintainer"))
Description: Tools and functions for managing the download of binary files. Binary repositories are defined in 'YAML' format. Defining new pre-download, download and post-download templates allow additional repositories to be added.
Depends: R (>= 3.3)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Suggests: testthat, covr, knitr, rmarkdown
Imports: rappdirs, yaml, httr, jsonlite, xml2, utils, stats, assertthat, semver
URL: https://github.com/ropensci/binman
URLNote: https://github.com/ropensci/binman
BugReports: https://github.com/ropensci/binman/issues
RoxygenNote: 6.0.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-07-17 23:07:40 UTC; jkim
Author: John Harrison [aut] (original author), Ju Yeong Kim [cre] (rOpenSci maintainer)
Maintainer: Ju Yeong Kim <jkim2345@fredhutch.org>
Repository: CRAN
Date/Publication: 2018-07-18 22:40:08 UTC

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Package binhf updated to version 1.0-3 with previous version 1.0-2 dated 2018-06-07

Title: Haar-Fisz Functions for Binomial Data
Description: Binomial Haar-Fisz transforms for Gaussianization as in Nunes and Nason (2009).
Author: Matt Nunes <nunesrpackages@gmail.com>
Maintainer: Matt Nunes <nunesrpackages@gmail.com>

Diff between binhf versions 1.0-2 dated 2018-06-07 and 1.0-3 dated 2018-07-18

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Package robotstxt updated to version 0.6.2 with previous version 0.6.0 dated 2018-02-11

Title: A 'robots.txt' Parser and 'Webbot'/'Spider'/'Crawler' Permissions Checker
Description: Provides functions to download and parse 'robots.txt' files. Ultimately the package makes it easy to check if bots (spiders, crawler, scrapers, ...) are allowed to access specific resources on a domain.
Author: Peter Meissner [aut, cre], Oliver Keys [ctb], Rich Fitz John [ctb]
Maintainer: Peter Meissner <retep.meissner@gmail.com>

Diff between robotstxt versions 0.6.0 dated 2018-02-11 and 0.6.2 dated 2018-07-18

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Package maditr updated to version 0.5.2 with previous version 0.5.1 dated 2018-05-10

Title: Pipe-Style Interface for 'data.table'
Description: Package provides pipe-style interface for 'data.table'. It preserves all 'data.table' features without significant impact on performance. 'let' and 'take' functions are simplified interfaces for most common data manipulation tasks. For example, you can write 'mtcars %>% take(mean(mpg), by = am)' for aggregation or 'mtcars %>% let(hp_wt = hp/wt, hp_wt_mpg = hp_wt/mpg)' for modification. Use 'take_if/let_if' for conditional aggregation/modification. 'query_if' function translates its arguments one-to-one to '[.data.table' method. Additionally there are some conveniences such as automatic 'data.frame' conversion to 'data.table'.
Author: Gregory Demin [aut, cre]
Maintainer: Gregory Demin <gdemin@gmail.com>

Diff between maditr versions 0.5.1 dated 2018-05-10 and 0.5.2 dated 2018-07-18

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Package future.batchtools updated to version 0.7.1 with previous version 0.7.0 dated 2018-05-06

Title: A Future API for Parallel and Distributed Processing using 'batchtools'
Description: Implementation of the Future API on top of the 'batchtools' package. This allows you to process futures, as defined by the 'future' package, in parallel out of the box, not only on your local machine or ad-hoc cluster of machines, but also via high-performance compute ('HPC') job schedulers such as 'LSF', 'OpenLava', 'Slurm', 'SGE', and 'TORQUE' / 'PBS', e.g. 'y <- future.apply::future_lapply(files, FUN = process)'.
Author: Henrik Bengtsson [aut, cre, cph]
Maintainer: Henrik Bengtsson <henrikb@braju.com>

Diff between future.batchtools versions 0.7.0 dated 2018-05-06 and 0.7.1 dated 2018-07-18

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Package NlinTS updated to version 1.3.3 with previous version 1.3.2 dated 2018-03-16

Title: Non Linear Time Series Analysis
Description: Models for time series forecasting and causality detection. The main functionalities of this package consist of a neural network Vector Auto-Regressive model, the classical Granger causality test C.W.J.Granger (1980) <doi:10.1016/0165-1889(80)90069-X>, and a non-linear version of it based on feedforward neural networks.
Author: Youssef Hmamouche [aut, cre], Sylvain Barthelemy [cph]
Maintainer: Youssef Hmamouche <hmamoucheyussef@gmail.com>

Diff between NlinTS versions 1.3.2 dated 2018-03-16 and 1.3.3 dated 2018-07-18

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 15 files changed, 58 insertions(+), 57 deletions(-)

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Package nanotime updated to version 0.2.2 with previous version 0.2.1 dated 2018-07-01

Title: Nanosecond-Resolution Time for R
Description: Full 64-bit resolution date and time support with resolution up to nanosecond granularity is provided, with easy transition to and from the standard 'POSIXct' type.
Author: Dirk Eddelbuettel and Leonardo Silvestri
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between nanotime versions 0.2.1 dated 2018-07-01 and 0.2.2 dated 2018-07-18

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Package perccalc updated to version 1.0.2 with previous version 1.0.1 dated 2018-03-30

Title: Estimate Percentiles from an Ordered Categorical Variable
Description: An implementation of two functions that estimate values for percentiles from an ordered categorical variable as described by Reardon (2011, isbn:978-0-87154-372-1). One function estimates percentile differences from two percentiles while the other returns the values for every percentile from 1 to 100.
Author: Jorge Cimentada [aut, cre]
Maintainer: Jorge Cimentada <cimentadaj@gmail.com>

Diff between perccalc versions 1.0.1 dated 2018-03-30 and 1.0.2 dated 2018-07-18

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Package foreign updated to version 0.8-70.2 with previous version 0.8-70.1 dated 2018-07-13

Title: Read Data Stored by 'Minitab', 'S', 'SAS', 'SPSS', 'Stata', 'Systat', 'Weka', 'dBase', ...
Description: Reading and writing data stored by some versions of 'Epi Info', 'Minitab', 'S', 'SAS', 'SPSS', 'Stata', 'Systat', 'Weka', and for reading and writing some 'dBase' files.
Author: R Core Team [aut, cph, cre], Roger Bivand [ctb, cph], Vincent J. Carey [ctb, cph], Saikat DebRoy [ctb, cph], Stephen Eglen [ctb, cph], Rajarshi Guha [ctb, cph], Swetlana Herbrandt [ctb], Nicholas Lewin-Koh [ctb, cph], Mark Myatt [ctb, cph], Ben Pfaff [ctb], Brian Quistorff [ctb], Frank Warmerdam [ctb, cph], Stephen Weigand [ctb, cph], Free Software Foundation, Inc. [cph]
Maintainer: R Core Team <R-core@R-project.org>

Diff between foreign versions 0.8-70.1 dated 2018-07-13 and 0.8-70.2 dated 2018-07-18

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 5 files changed, 16 insertions(+), 14 deletions(-)

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New package TaxicabCA with initial version 0.1.0
Package: TaxicabCA
Type: Package
Title: Taxicab Correspondence Analysis
Version: 0.1.0
Suggests: GA, testthat
Imports: grDevices, graphics, stats, utils
Author: Jacques Allard and Vartan Choulakian
Maintainer: Jacques Allard <jacques.allard@gmail.com>
Description: Computation and visualization of Taxicab Correspondence Analysis, Choulakian (2006) <doi:10.1007/s11336-004-1231-4>. Classical correspondence analysis (CA) is a statistical method to analyse 2-dimensional tables of positive numbers and is typically applied to contingency tables (Benzecri, J.-P. (1973). L'Analyse des Donnees. Volume II. L'Analyse des Correspondances. Paris, France: Dunod). Classical CA is based on the Euclidean distance. Taxicab CA is like classical CA but is based on the Taxicab or Manhattan distance. For some tables, Taxicab CA gives more informative results than classical CA.
License: GPL (>= 2)
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-07-12 14:53:20 UTC; Jacques
Repository: CRAN
Date/Publication: 2018-07-18 15:20:03 UTC

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New package TangPoemR with initial version 0.1.0
Package: TangPoemR
Type: Package
Title: Write Chinese Tang Poems
Version: 0.1.0
Author: Yanni Li, Yongyuan Liang
Maintainer: Yongyuan Liang <charlotte9762@hotmail.com>
Description: Write Chinese Tang Poems automatically.
Imports: jiebaR
License: GPL (>= 2)
Depends: R (>= 3.0)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-07-11 11:01:22 UTC; LYN
Repository: CRAN
Date/Publication: 2018-07-18 13:10:13 UTC

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New package RPS with initial version 1.0.0
Package: RPS
Type: Package
Title: Resistant Procrustes Superimposition
Version: 1.0.0
Authors@R: c(person("Guillermo Andres", "Pacheco", email = "guillermopacheco.exa@gmail.com", role = c("aut", "cre")), person("Sebastian", "Torcida", email = "unisebas@gmail.com", role = "aut"), person("Viviana", "Ferragine", email = "viviana.ferraggine@gmail.com", role = "aut"), person("Federico", "Lotto", email = "federicolotto@gmail.com@gmail.com", role = "aut"))
Maintainer: Guillermo Andres Pacheco <guillermopacheco.exa@gmail.com>
Description: Based on RPS tools, a rather complete resistant shape analysis of 2D and 3D datasets based on landmarks can be performed. In addition, landmark-based resistant shape analysis of individual asymmetry in 2D for matching or object symmetric structures is also possible.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Imports: geomorph, MASS, igraph, ape, matlab, Gmedian
NeedsCompilation: no
Packaged: 2018-07-12 00:27:36 UTC; Guillermo
Author: Guillermo Andres Pacheco [aut, cre], Sebastian Torcida [aut], Viviana Ferragine [aut], Federico Lotto [aut]
Repository: CRAN
Date/Publication: 2018-07-18 13:50:03 UTC

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Package rmpw updated to version 0.0.4 with previous version 0.0.3 dated 2018-01-04

Title: Causal Mediation Analysis Using Weighting Approach
Description: We implement causal mediation analysis using the methods proposed by Hong (2010) and Hong, Deutsch & Hill (2015) <doi:10.3102/1076998615583902>. It allows the estimation and hypothesis testing of causal mediation effects through ratio of mediator probability weights (RMPW). This strategy conveniently relaxes the assumption of no treatment-by-mediator interaction while greatly simplifying the outcome model specification without invoking strong distributional assumptions. We also implement a sensitivity analysis by extending the RMPW method to assess potential bias in the presence of omitted pretreatment or posttreatment covariates. The sensitivity analysis strategy was proposed by Hong, Qin, and Yang (2018) <doi:10.3102/1076998617749561>.
Author: Xu Qin, Guanglei Hong, and Fan Yang
Maintainer: Xu Qin <xuqin@uchicago.edu>

Diff between rmpw versions 0.0.3 dated 2018-01-04 and 0.0.4 dated 2018-07-18

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 NAMESPACE         |    1 
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Package revengc updated to version 1.0.2 with previous version 1.0.1 dated 2018-07-17

Title: Reverse Engineering Decoupled and Censored Data
Description: An issue occurs when authors do not reveal clear information. Decoupled variables (e.g. separate averages) and numeric censoring (e.g. between ages 10-15) are reoccurring instances found in areas ranging from demographic and epidemiological data to ecological inference problems. Decoupled variables provide no availability for cross tabulations while censoring obscures the true underlying values. The revengc R package was developed to reverse engineer this unclear information that is continually reported by many well-established organizations (e.g. World Health Organization (WHO), Centers for Disease Control and Prevention (CDC), World Bank, and various national censuses). There are two main functions in revengc and both fit data to a Poisson or Quasi-Poisson distribution. The estimated_lambda function takes a univariate censored frequency table and approximates its lambda (average) value. The rec function calculates an uncensored bivariate table from decoupled and summarized arguments.
Author: Samantha Duchscherer [aut, cre], UT-Battelle, LLC [cph]
Maintainer: Samantha Duchscherer <sam.duchscherer@gmail.com>

Diff between revengc versions 1.0.1 dated 2018-07-17 and 1.0.2 dated 2018-07-18

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 inst/doc/duchscherer-stewart-urban.ltx  |    2 +-
 inst/doc/duchscherer-stewart-urban.pdf  |binary
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New package r4lineups with initial version 0.1.1
Package: r4lineups
Title: Statistical Inference on Lineup Fairness
Version: 0.1.1
Authors@R: c( person("Colin", "Tredoux", email = "colin.tredoux@uct.ac.za", role = c("aut", "cre")), person("Tamsyn", "Naylor", email = "tmnaylor@outlook.com", role = "aut"))
Maintainer: Colin Tredoux <colin.tredoux@uct.ac.za>
Description: Since the early 1970s eyewitness testimony researchers have recognised the importance of estimating properties such as lineup bias (is the lineup biased against the suspect, leading to a rate of choosing higher than one would expect by chance?), and lineup size (how many reasonable choices are in fact available to the witness? A lineup is supposed to consist of a suspect and a number of additional members, or foils, whom a poor-quality witness might mistake for the perpetrator). Lineup measures are descriptive, in the first instance, but since the earliest articles in the literature researchers have recognised the importance of reasoning inferentially about them. This package contains functions to compute various properties of laboratory or police lineups, and is intended for use by researchers in forensic psychology and/or eyewitness testimony research. Among others, the r4lineups package includes functions for calculating lineup proportion, functional size, various estimates of effective size, diagnosticity ratio, homogeneity of the diagnosticity ratio, ROC curves for confidence x accuracy data and the degree of similarity of faces in a lineup.
Depends: R (>= 3.4.0)
Imports: boot, dplyr, ggplot2, ggrepel, here, magick, magrittr, pROC, psych, purrr, stats, utils
License: CC0
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1.9000
Suggests: knitr, rmarkdown, pander
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-07-12 07:42:53 UTC; Tamsyn Naylor
Author: Colin Tredoux [aut, cre], Tamsyn Naylor [aut]
Repository: CRAN
Date/Publication: 2018-07-18 13:20:02 UTC

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New package evian with initial version 2.0.0
Package: evian
Type: Package
Title: Evidential Analysis of Genetic Association Data
Version: 2.0.0
Depends: R (>= 3.2.5), ProfileLikelihood, sandwich, foreach, doParallel
Author: Dr. Lisa J Strug <lisa.strug@utoronto.ca>; Dr. Zeynep Baskurt <zeynep.baskurt@sickkids.ca>; Bowei Xiao <bowei.xiao@sickkids.ca>; Ted Chiang <theodorechiang@gmail.com>
Maintainer: Bowei Xiao <bowei.xiao@sickkids.ca>
Description: Evidential regression analysis for dichotomous and quantitative outcome data. The following references described the methods in this package: Strug, L. J., Hodge, S. E., Chiang, T., Pal, D. K., Corey, P. N., & Rohde, C. (2010) <doi:10.1038/ejhg.2010.47>. Strug, L. J., & Hodge, S. E. (2006) <doi:10.1159/000094709>. Royall, R. (1997) <ISBN:0-412-04411-0>.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-07-11 16:22:17 UTC; bowei
Repository: CRAN
Date/Publication: 2018-07-18 13:10:06 UTC

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Package dynutils updated to version 1.0.0 with previous version 0.1.0 dated 2018-06-24

Title: Common Functionality for the 'dynverse' Packages
Description: Provides common functionality for the 'dynverse' packages. 'dynverse' is created to support the development, execution, and benchmarking of trajectory inference methods. For more information, check out <https://github.com/dynverse/dynverse>.
Author: Robrecht Cannoodt [aut, cre] (<https://orcid.org/0000-0003-3641-729X>, rcannood), Wouter Saelens [aut] (<https://orcid.org/0000-0002-7114-6248>, zouter)
Maintainer: Robrecht Cannoodt <rcannood@gmail.com>

Diff between dynutils versions 0.1.0 dated 2018-06-24 and 1.0.0 dated 2018-07-18

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 dynutils-1.0.0/dynutils/NAMESPACE                                 |   20 ++
 dynutils-1.0.0/dynutils/R/RcppExports.R                           |   28 +++
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 dynutils-1.0.0/dynutils/R/random_time_string.R                    |    3 
 dynutils-1.0.0/dynutils/R/scaling.R                               |    8 
 dynutils-1.0.0/dynutils/R/tibble.R                                |   58 ++++++-
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 48 files changed, 529 insertions(+), 185 deletions(-)

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New package CliftLRD with initial version 0.1-1
Package: CliftLRD
Type: Package
Title: Complex-Valued Wavelet Lifting Estimators of the Hurst Exponent for Irregularly Sampled Time Series
Version: 0.1-1
Date: 2018-07-09
Author: Matt Nunes [aut, cre], Marina Knight [aut]
Authors@R: c(person("Matt", "Nunes", role=c("aut","cre"),email="nunesrpackages@gmail.com"), person("Marina", "Knight", role="aut"))
Maintainer: Matt Nunes <nunesrpackages@gmail.com>
Description: Implementation of Hurst exponent estimators based on complex-valued lifting wavelet energy from Knight, M. I and Nunes, M. A. (2018) <doi:10.1007/s11222-018-9820-8>.
License: GPL-2
Depends: CNLTreg, liftLRD
Suggests: fracdiff
NeedsCompilation: no
Packaged: 2018-07-12 09:14:38 UTC; nunes
Repository: CRAN
Date/Publication: 2018-07-18 14:00:03 UTC

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Package CASMAP updated to version 0.6.0 with previous version 0.5.9 dated 2018-07-05

Title: Detection of Statistically Significant Combinations of SNPs in Association Mapping
Description: A significant pattern mining-based toolbox for region-based genome-wide association studies and higher-order epistasis analyses, implementing the methods described in Llinares-López et al. (2017) <doi:10.1093/bioinformatics/btx071>.
Author: Felipe Llinares-López [aut, cph], Laetitia Papaxanthos [aut, cph], Damian Roqueiro [aut, cph], Matthew Baker [ctr], Mikołaj Rybiński [ctr], Uwe Schmitt [ctr], Dean Bodenham [aut, cre, cph], Karsten Borgwardt [aut, fnd, cph]
Maintainer: Dean Bodenham <deanbodenhambsse@gmail.com>

Diff between CASMAP versions 0.5.9 dated 2018-07-05 and 0.6.0 dated 2018-07-18

 DESCRIPTION                                |    6 +++---
 MD5                                        |    8 ++++----
 inst/include/Summary.h                     |    3 ++-
 src/SignificantFeaturesSearchTaroneCmh.cpp |    3 ++-
 src/pval.cpp                               |   10 ++++++++--
 5 files changed, 19 insertions(+), 11 deletions(-)

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Package VCA updated to version 1.3.4 with previous version 1.3.3 dated 2017-07-12

Title: Variance Component Analysis
Description: ANOVA and REML estimation of linear mixed models is implemented, once following Searle et al. (1991, ANOVA for unbalanced data), once making use of the 'lme4' package. The primary objective of this package is to perform a variance component analysis (VCA) according to CLSI EP05-A3 guideline "Evaluation of Precision of Quantitative Measurement Procedures" (2014). There are plotting methods for visualization of an experimental design, plotting random effects and residuals. For ANOVA type estimation two methods for computing ANOVA mean squares are implemented (SWEEP and quadratic forms). The covariance matrix of variance components can be derived, which is used in estimating confidence intervals. Linear hypotheses of fixed effects and LS means can be computed. LS means can be computed at specific values of covariables and with custom weighting schemes for factor variables. See ?VCA for a more comprehensive description of the features.
Author: Andre Schuetzenmeister [aut, cre], Florian Dufey [ctb]
Maintainer: Andre Schuetzenmeister <andre.schuetzenmeister@roche.com>

Diff between VCA versions 1.3.3 dated 2017-07-12 and 1.3.4 dated 2018-07-18

 DESCRIPTION                   |    8 
 MD5                           |   21 -
 NAMESPACE                     |    1 
 R/plot.R                      |  565 ++++++++++++++++++++++++++++++++++--------
 R/vca.R                       |  132 ++++-----
 inst/ChangeLog.txt            |   12 
 inst/UnitTests/runit.remlMM.R |   11 
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 12 files changed, 674 insertions(+), 263 deletions(-)

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New package thor with initial version 1.0.1
Package: thor
Title: Interface to 'LMDB'
Version: 1.0.1
Authors@R: c(person("Rich", "FitzJohn", role = c("aut", "cre"), email = "rich.fitzjohn@gmail.com"), person("Howard", "Chu", role = "cph"), person("Symas Corporation", role = "cph"), person("Martin", "Hedenfalk", role = "cph"), person("The OpenLDAP Foundation", role = "cph"))
Description: Key-value store, implemented as a wrapper around 'LMDB'; the "lightning memory-mapped database" <https://symas.com/lmdb/>. 'LMDB' is a transactional key value store that uses a memory map for efficient access. This package wraps the entire 'LMDB' interface, providing objects for transactions and cursors.
License: MIT + file LICENSE
LazyData: true
URL: https://github.com/richfitz/thor
BugReports: https://github.com/richfitz/thor/issues
Imports: R6, storr
Suggests: ids, knitr, rmarkdown, testthat
RoxygenNote: 6.0.1
VignetteBuilder: knitr
ByteCompile: true
Encoding: UTF-8
Language: en-GB
NeedsCompilation: yes
Packaged: 2018-07-11 07:55:21 UTC; rich
Author: Rich FitzJohn [aut, cre], Howard Chu [cph], Symas Corporation [cph], Martin Hedenfalk [cph], The OpenLDAP Foundation [cph]
Maintainer: Rich FitzJohn <rich.fitzjohn@gmail.com>
Repository: CRAN
Date/Publication: 2018-07-18 13:00:03 UTC

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Package SmoothWin updated to version 2.0.0 with previous version 1.0.0 dated 2017-09-06

Title: Soft Windowing on Linear Regression
Description: The main function in the package utilizes a windowing function in the form of an exponential weighting function to linear models. The bandwidth and sharpness of the window are controlled by two parameters. Then, a series of tests are used to identify the right parameters of the window (see Charles Kervrann (2004) <doi:10.1007/978-3-540-24672-5_11>).
Author: Hamed Haselimashhadi <hamedhm@ebi.ac.uk>
Maintainer: Hamed Haselimashhadi <hamedhm@ebi.ac.uk>

Diff between SmoothWin versions 1.0.0 dated 2017-09-06 and 2.0.0 dated 2018-07-18

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New package r511 with initial version 0.1.1
Package: r511
Type: Package
Title: Work with the Bay Area Transportation Commission Application Programming Interface
Version: 0.1.1
Author: Tom Buckley
Maintainer: Tom Buckley <tom@tbuckl.com>
Description: For the 9 counties in the San Francisco Bay area the Metropolitan Transportation Commission maintains an Application Programming Interface with information on more than 20 transit operators. This package allows users to retrieve information about transit schedules in the General Transit Feed Specification as published by the Metropolitan Transportation Commission at the following url: <https://511.org/developers/list/apis/>.
License: GPL
Encoding: UTF-8
LazyData: true
Imports: dplyr, tibble, httr, xml2, assertthat
Suggests: testthat, knitr, rmarkdown
RoxygenNote: 6.0.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-07-11 01:43:39 UTC; tbuck
Repository: CRAN
Date/Publication: 2018-07-18 12:10:02 UTC

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Package liftLRD updated to version 1.0-8 with previous version 1.0-7 dated 2018-05-22

Title: Wavelet Lifting Estimators of the Hurst Exponent for Regularly and Irregularly Sampled Time Series
Description: Implementations of Hurst exponent estimators based on the relationship between wavelet lifting scales and wavelet energy of Knight et al (2017) <doi:10.1007/s11222-016-9698-2>.
Author: Marina Knight [aut], Guy Nason [ctb], Matt Nunes [aut, cre]
Maintainer: Matt Nunes <nunesrpackages@gmail.com>

Diff between liftLRD versions 1.0-7 dated 2018-05-22 and 1.0-8 dated 2018-07-18

 DESCRIPTION            |   14 +++++++-------
 MD5                    |    4 ++--
 man/liftLRD-package.Rd |    2 +-
 3 files changed, 10 insertions(+), 10 deletions(-)

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Package CNLTtsa updated to version 0.1-2 with previous version 0.1 dated 2017-03-08

Title: Complex-Valued Wavelet Lifting for Univariate and Bivariate Time Series Analysis
Description: Implementations of recent complex-valued wavelet spectral procedures for analysis of irregularly sampled signals, see Hamilton et al (2018) <doi:10.1080/00401706.2017.1281846>.
Author: Jean Hamilton [aut], Matt Nunes [aut, cre], Marina Knight [ctb], Piotr Fryzlewicz [ctb]
Maintainer: Matt Nunes <nunesrpackages@gmail.com>

Diff between CNLTtsa versions 0.1 dated 2017-03-08 and 0.1-2 dated 2018-07-18

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Package CNLTreg updated to version 0.1-2 with previous version 0.1 dated 2017-03-04

Title: Complex-Valued Wavelet Lifting for Signal Denoising
Description: Implementations of recent complex-valued wavelet shrinkage procedures for smoothing irregularly sampled signals, see Hamilton et al (2018) <doi:10.1080/00401706.2017.1281846>.
Author: Matt Nunes [aut, cre], Marina Knight [aut], Jean Hamilton [ctb], Piotr Fryzlewicz [ctb]
Maintainer: Matt Nunes <nunesrpackages@gmail.com>

Diff between CNLTreg versions 0.1 dated 2017-03-04 and 0.1-2 dated 2018-07-18

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 MD5                    |   22 +++++++++++-----------
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New package adpss with initial version 0.1.0
Package: adpss
Title: Design and Analysis of Locally or Globally Efficient Adaptive Designs
Version: 0.1.0
Authors@R: person("Kosuke", "Kashiwabara", email = "kashiwabara-tky@umin.ac.jp", role = c("aut", "cre"))
Description: Provides the functions for planning and conducting a clinical trial with adaptive sample size determination. Maximal statistical efficiency will be exploited even when dramatic or multiple adaptations are made. Such a trial consists of adaptive determination of sample size at an interim analysis and implementation of frequentist statistical test at the interim and final analysis with a prefixed significance level. The required assumptions for the stage-wise test statistics are independent and stationary increments and normality. Predetermination of adaptation rule is not required.
Depends: R (>= 3.5.0)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
URL: https://github.com/ca4wa/R-adpss
LinkingTo: Rcpp (>= 0.12.17)
Imports: Rcpp (>= 0.12.17)
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2018-07-11 07:40:56 UTC; Epistat
Author: Kosuke Kashiwabara [aut, cre]
Maintainer: Kosuke Kashiwabara <kashiwabara-tky@umin.ac.jp>
Repository: CRAN
Date/Publication: 2018-07-18 13:00:07 UTC

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New package tmvmixnorm with initial version 1.0.1
Package: tmvmixnorm
Type: Package
Title: Efficient Sampling Truncated Scale of Normals with Constraints
Version: 1.0.1
Authors@R: c(person("Ting Fung (Ralph)", "Ma", email = "tingfung.ma@wisc.edu", role = c("cre", "aut")), person("Sujit K.", "Ghosh", email = "sujit_ghosh@ncsu.edu", role = "aut"), person("Yifang", "Li", role = "aut"))
Maintainer: Ting Fung (Ralph) Ma <tingfung.ma@wisc.edu>
Description: Efficient sampling of truncated multivariate (scale) mixtures of normals under linear inequality constraints is nontrivial due to the analytically intractable normalizing constant. Meanwhile, traditional methods may subject to numerical issues, especially when the dimension is high and dependence is strong. Algorithms proposed by Li and Ghosh (2015) <doi: 10.1080/15598608.2014.996690> are adopted for overcoming difficulties in simulating truncated distributed random numbers. Efficient rejection sampling for simulating truncated univariate normal distribution is included in the package, which shows superiority in terms of acceptance rate and numerical stability compared to existing methods and R packages. An efficient function for sampling from truncated multivariate normal distribution subject to convex polytope restriction regions based on Gibbs sampler for conditional truncated univariate distribution is provided. By extending the sampling method, a function for sampling truncated multivariate Student-t distribution is also developed. Moreover, the proposed method and computation remain valid for high dimensional and strong dependence scenarios. Empirical results in Li and Ghosh (2015) <doi: 10.1080/15598608.2014.996690> illustrated the superior performance in terms of various criteria (e.g. mixing and integrated auto-correlation time).
License: GPL-2
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.2.0)
Imports: stats
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-07-10 21:08:16 UTC; Ralph
Author: Ting Fung (Ralph) Ma [cre, aut], Sujit K. Ghosh [aut], Yifang Li [aut]
Repository: CRAN
Date/Publication: 2018-07-18 11:30:02 UTC

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New package tatest with initial version 1.0
Package: tatest
Type: Package
Title: Two-Group Ta-Test
Version: 1.0
Date: 2018-07-10
Author: Yuan-De Tan
Maintainer: Yuan-De Tan <tanyuande@gmail.com>
Description: The ta-test is a modified two-sample or two-group t-test of Gosset (1908). In small samples with less than 15 replicates,the ta-test significantly reduces type I error rate but has almost the same power with the t-test and hence can greatly enhance reliability or reproducibility of discoveries in biology and medicine. The ta-test can test single null hypothesis or multiple null hypotheses without needing to correct p-values.
License: GPL-3
Depends: R (>= 3.3.0), stats, base,utils
LazyLoad: yes
NeedsCompilation: no
Packaged: 2018-07-10 19:34:46 UTC; yuandet
Repository: CRAN
Date/Publication: 2018-07-18 11:30:05 UTC

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New package rhli with initial version 0.0.1
Package: rhli
Title: FIS 'MarketMap C-Toolkit'
Version: 0.0.1
Authors@R: c( person("Kevin", "Keane", email = "krkeane@qoma.io", role = c("aut", "cre")), person("Qoma", "LLC", email = "info@qoma.io", role = "cph"))
Description: Complete access from 'R' to the FIS 'MarketMap C-Toolkit' ('FAME C-HLI'). 'FAME' is a fully integrated software and database management system from FIS that provides the following capabilities: Time series and cross-sectional data management; Financial calculation, data analysis, econometrics, and forecasting; Table generation and detailed multicolor, presentation-quality report writing; Multicolor, presentation-quality graphics; "What-if" analysis; Application development and structured programming; Data transfer to and from other applications; Tools for building customized graphical user interfaces.
Depends: R (>= 3.0)
License: AGPL
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Imports: methods
Suggests: testthat
URL: https://github.com/qomaio/rhli
BugReports: https://github.com/qomaio/rhli/issues
SystemRequirements: GNU make
NeedsCompilation: yes
Packaged: 2018-07-11 00:29:09 UTC; Kevin R. Keane
Author: Kevin Keane [aut, cre], Qoma LLC [cph]
Maintainer: Kevin Keane <krkeane@qoma.io>
Repository: CRAN
Date/Publication: 2018-07-18 11:40:03 UTC

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Package nngeo updated to version 0.2.0 with previous version 0.1.8 dated 2018-05-15

Title: k-Nearest Neighbor Join for Spatial Data
Description: K-nearest neighbor search for projected and non-projected 'sf' spatial layers. Nearest neighbor search uses (1) C implementation of the Vincenty Formula for lon-lat point layers, (2) function nn2() from package 'RANN' for projected point layers, or (3) function st_distance() from package 'sf' for line or polygon layers.
Author: Michael Dorman [aut, cre], Johnathan Rush [ctb], Ian Hough [ctb], Jan Antala [ctb, cph] (Author of C code for Vincenty distance)
Maintainer: Michael Dorman <dorman@post.bgu.ac.il>

Diff between nngeo versions 0.1.8 dated 2018-05-15 and 0.2.0 dated 2018-07-18

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 LICENSE                          |    2 
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Package future.callr updated to version 0.3.1 with previous version 0.3.0 dated 2018-05-06

Title: A Future API for Parallel Processing using 'callr'
Description: Implementation of the Future API on top of the 'callr' package. This allows you to process futures, as defined by the 'future' package, in parallel out of the box, on your local (Linux, macOS, Windows, ...) machine. Contrary to backends relying on the 'parallel' package (e.g. 'future::multisession'), the 'callr' backend provided here can run more than 125 parallel R processes.
Author: Henrik Bengtsson [aut, cre, cph]
Maintainer: Henrik Bengtsson <henrikb@braju.com>

Diff between future.callr versions 0.3.0 dated 2018-05-06 and 0.3.1 dated 2018-07-18

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 NAMESPACE                 |    1 +
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Package qqplotr updated to version 0.0.3 with previous version 0.0.2 dated 2017-12-18

Title: Quantile-Quantile Plot Extensions for 'ggplot2'
Description: Extensions of 'ggplot2' Q-Q plot functionalities.
Author: Alexandre Almeida [aut, cre], Adam Loy [aut], Heike Hofmann [aut]
Maintainer: Alexandre Almeida <almeida.xan@gmail.com>

Diff between qqplotr versions 0.0.2 dated 2017-12-18 and 0.0.3 dated 2018-07-18

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Package janitor updated to version 1.1.0 with previous version 1.0.0 dated 2018-03-22

Title: Simple Tools for Examining and Cleaning Dirty Data
Description: The main janitor functions can: perfectly format data.frame column names; provide quick counts of variable combinations (i.e., frequency tables and crosstabs); and isolate duplicate records. Other janitor functions nicely format the tabulation results. These tabulate-and-report functions approximate popular features of SPSS and Microsoft Excel. This package follows the principles of the "tidyverse" and works well with the pipe function %>%. janitor was built with beginning-to-intermediate R users in mind and is optimized for user-friendliness. Advanced R users can already do everything covered here, but with janitor they can do it faster and save their thinking for the fun stuff.
Author: Sam Firke [aut, cre], Chris Haid [ctb], Ryan Knight [ctb], Bill Denney [ctb]
Maintainer: Sam Firke <samuel.firke@gmail.com>

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Package ukgasapi updated to version 0.14 with previous version 0.13 dated 2015-10-25

Title: API for UK Gas Market Information
Description: Allows users to access live UK gas market information via National Grid's API.
Author: Timothy Wong [aut, cre]
Maintainer: Timothy Wong <timothy.wong@hotmail.co.uk>

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Package rNOMADS updated to version 2.3.10 with previous version 2.3.9 dated 2018-01-14

Title: An Interface to the NOAA Operational Model Archive and Distribution System
Description: An interface to the National Oceanic and Atmospheric Administration's Operational Model Archive and Distribution System (NOMADS, see <http://nomads.ncep.noaa.gov/> for more information) that allows R users to quickly and efficiently download global and regional weather model data for processing. rNOMADS currently supports a variety of models ranging from global weather data to an altitude of over 40 km, to high resolution regional weather models, to wave and sea ice models. It can also retrieve archived NOMADS models. rNOMADS can retrieve binary data in grib format as well as import ascii data directly into R by interfacing with the GrADS-DODS system.
Author: Daniel C. Bowman [aut, cre]
Maintainer: Daniel C. Bowman <danny.c.bowman@gmail.com>

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Package emmeans updated to version 1.2.3 with previous version 1.2.2 dated 2018-06-26

Title: Estimated Marginal Means, aka Least-Squares Means
Description: Obtain estimated marginal means (EMMs) for many linear, generalized linear, and mixed models. Compute contrasts or linear functions of EMMs, trends, and comparisons of slopes. Plots and compact letter displays. Least-squares means are discussed, and the term "estimated marginal means" is suggested, in Searle, Speed, and Milliken (1980) Population marginal means in the linear model: An alternative to least squares means, The American Statistician 34(4), 216-221 <doi:10.1080/00031305.1980.10483031>.
Author: Russell Lenth [aut, cre, cph], Henrik Singmann [ctb], Jonathon Love [ctb], Paul Buerkner [ctb], Maxime Herve [ctb]
Maintainer: Russell Lenth <russell-lenth@uiowa.edu>

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