Sun, 16 Sep 2018

Package hIRT updated to version 0.1.3 with previous version 0.1.2 dated 2017-08-01

Title: Hierarchical Item Response Theory Models
Description: Implementation of a class of hierarchical item response theory (IRT) models where both the mean and the variance of latent preferences (ability parameters) may depend on observed covariates. The current implementation includes both the two-parameter latent trait model for binary data and the graded response model for ordinal data. Both are fitted via the Expectation-Maximization (EM) algorithm. Asymptotic standard errors are derived from the observed information matrix.
Author: Xiang Zhou [aut, cre]
Maintainer: Xiang Zhou <xiang_zhou@fas.harvard.edu>

Diff between hIRT versions 0.1.2 dated 2017-08-01 and 0.1.3 dated 2018-09-16

 DESCRIPTION |   10 +++++-----
 MD5         |   11 ++++++-----
 NEWS.md     |only
 R/hgrm.R    |   25 ++++++++++++-------------
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 7 files changed, 41 insertions(+), 44 deletions(-)

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Package filling updated to version 0.2.0 with previous version 0.1.0 dated 2017-12-11

Title: Matrix Completion, Imputation, and Inpainting Methods
Description: Filling in the missing entries of a partially observed data is one of fundamental problems in various disciplines of mathematical science. For many cases, data at our interests have canonical form of matrix in that the problem is posed upon a matrix with missing values to fill in the entries under preset assumptions and models. We provide a collection of methods from multiple disciplines under Matrix Completion, Imputation, and Inpainting. See Davenport and Romberg (2016) <doi:10.1109/JSTSP.2016.2539100> for an overview of the topic.
Author: Kisung You [aut, cre] (<https://orcid.org/0000-0002-8584-459X>)
Maintainer: Kisung You <kyou@nd.edu>

Diff between filling versions 0.1.0 dated 2017-12-11 and 0.2.0 dated 2018-09-16

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 NAMESPACE              |    2 ++
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 R/auxiliary_visible.R  |    2 --
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 R/fill_nuclear.R       |    3 ++-
 R/filling-package.R    |   19 +++++++++++++++++++
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 inst/REFERENCES.bib    |   16 +++++++++++++++-
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 man/fill_SoftImpute.Rd |    3 ++-
 man/fill_nuclear.Rd    |    3 ++-
 man/filling-package.Rd |   13 +++++++++++++
 src/Makevars           |    4 ++--
 src/Makevars.win       |    4 ++--
 src/RcppExports.cpp    |   26 +++++++++++++-------------
 19 files changed, 103 insertions(+), 51 deletions(-)

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Package bWGR updated to version 1.5.5 with previous version 1.5.4 dated 2018-08-08

Title: Bayesian Whole-Genome Regression
Description: Whole-genome regression methods on Bayesian framework fitted via EM or Gibbs sampling, with optional sampling techniques and kernel term.
Author: Alencar Xavier, William Muir, Shizhong Xu, Katy Rainey.
Maintainer: Alencar Xavier <alenxav@gmail.com>

Diff between bWGR versions 1.5.4 dated 2018-08-08 and 1.5.5 dated 2018-09-16

 bWGR-1.5.4/bWGR/src/wgr20180808.cpp |only
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 bWGR-1.5.5/bWGR/man/mix.Rd          |    5 +
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 bWGR-1.5.5/bWGR/src/RcppExports.cpp |  118 +++++++++++++++++++++++++++++-------
 bWGR-1.5.5/bWGR/src/wgr20180916.cpp |only
 14 files changed, 170 insertions(+), 56 deletions(-)

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Package tvR updated to version 0.3.0 with previous version 0.2.0 dated 2018-05-15

Title: Total Variation Regularization
Description: Provides tools for denoising noisy signal and images via Total Variation Regularization. Reducing the total variation of the given signal is known to remove spurious detail while preserving essential structural details. For the seminal work on the topic, see Rudin et al (1992) <doi:10.1016/0167-2789(92)90242-F>.
Author: Kisung You [aut, cre] (<https://orcid.org/0000-0002-8584-459X>)
Maintainer: Kisung You <kyou@nd.edu>

Diff between tvR versions 0.2.0 dated 2018-05-15 and 0.3.0 dated 2018-09-16

 tvR-0.2.0/tvR/R/package-tvR.R     |only
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 tvR-0.3.0/tvR/R/RcppExports.R     |    4 ----
 tvR-0.3.0/tvR/R/denoise1.R        |    1 -
 tvR-0.3.0/tvR/R/denoise2.R        |    1 -
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 tvR-0.3.0/tvR/man/tvR-package.Rd  |    2 +-
 tvR-0.3.0/tvR/src/Makevars        |    2 +-
 tvR-0.3.0/tvR/src/Makevars.win    |    4 ++--
 tvR-0.3.0/tvR/src/RcppExports.cpp |   11 -----------
 19 files changed, 26 insertions(+), 43 deletions(-)

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Package sparr updated to version 2.2-13 with previous version 2.2-12 dated 2018-07-22

Title: Spatial and Spatiotemporal Relative Risk
Description: Provides functions to estimate kernel-smoothed spatial and spatio-temporal densities and relative risk functions, and perform subsequent inference. Methodological details can be found in the accompanying tutorial: Davies et al. (2018) <DOI:10.1002/sim.7577>.
Author: Tilman M. Davies [aut, cre], Jonathan C. Marshall [aut]
Maintainer: Tilman M. Davies <tdavies@maths.otago.ac.nz>

Diff between sparr versions 2.2-12 dated 2018-07-22 and 2.2-13 dated 2018-09-16

 DESCRIPTION               |   10 ++++----
 MD5                       |   54 +++++++++++++++++++++++-----------------------
 NEWS                      |   19 ++++++++++++++++
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 R/bivariate.density.R     |    2 -
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 man/printsparr.Rd         |    4 ---
 man/risk.Rd               |    4 +--
 man/sparr-package.Rd      |    6 ++---
 man/summarysparr.Rd       |    4 ---
 man/tolerance.Rd          |    7 +++--
 28 files changed, 142 insertions(+), 94 deletions(-)

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Package aiRthermo updated to version 1.2.1 with previous version 1.2 dated 2018-07-02

Title: Atmospheric Thermodynamics and Visualization
Description: Deals with many computations related to the thermodynamics of atmospheric processes. It includes many functions designed to consider the density of air with varying degrees of water vapour in it, saturation pressures and mixing ratios, conversion of moisture indices, computation of atmospheric states of parcels subject to dry or pseudoadiabatic vertical evolutions and atmospheric instability indices that are routinely used for operational weather forecasts or meteorological diagnostics.
Author: Jon Sáenz, Santos J. González-Rojí, Sheila Carreno-Madinabeitia and Gabriel Ibarra-Berastegi
Maintainer: Santos J. González-Rojí <santosjose.gonzalez@ehu.eus>

Diff between aiRthermo versions 1.2 dated 2018-07-02 and 1.2.1 dated 2018-09-16

 DESCRIPTION                  |    8 
 MD5                          |   22 +-
 NEWS.md                      |    6 
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 12 files changed, 443 insertions(+), 396 deletions(-)

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Package voteogram updated to version 0.3.1 with previous version 0.2.0 dated 2017-11-27

Title: United States House and Senate Voting Cartogram Generators
Description: 'ProPublica' <https://projects.propublica.org/represent/> makes United States Congress member votes available and has developed their own unique cartogram to visually represent this data. Tools are provided to retrieve voting data, prepare voting data for plotting with 'ggplot2', create vote cartograms and theme them.
Author: Bob Rudis [aut, cre] (<https://orcid.org/0000-0001-5670-2640>), ProPublica [cph] (Cartogram SVGs used to make the plot data.frames), GovTrack [cph] (Cartogram SVG used to make the plot data.frame)
Maintainer: Bob Rudis <bob@rud.is>

Diff between voteogram versions 0.2.0 dated 2017-11-27 and 0.3.1 dated 2018-09-16

 DESCRIPTION                      |   16 +
 MD5                              |   12 -
 build/vignette.rds               |binary
 inst/doc/intro_to_voteogram.R    |    4 
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 7 files changed, 222 insertions(+), 134 deletions(-)

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Package graphon updated to version 0.3.0 with previous version 0.2.0 dated 2017-11-08

Title: A Collection of Graphon Estimation Methods
Description: Provides a not-so-comprehensive list of methods for estimating graphon, a symmetric measurable function, from a single or multiple of observed networks. For a detailed introduction on graphon and popular estimation techniques, see the paper by Orbanz, P. and Roy, D.M.(2014) <doi:10.1109/TPAMI.2014.2334607>. It also contains several auxiliary functions for generating sample networks using various network models and graphons.
Author: Kisung You [aut, cre] (<https://orcid.org/0000-0002-8584-459X>)
Maintainer: Kisung You <kyou@nd.edu>

Diff between graphon versions 0.2.0 dated 2017-11-08 and 0.3.0 dated 2018-09-16

 graphon-0.2.0/graphon/man/graphon.Rd         |only
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 graphon-0.3.0/graphon/R/cv.SBA.R             |   18 ++++-----
 graphon-0.3.0/graphon/R/est.LG.R             |   21 +++++------
 graphon-0.3.0/graphon/R/est.SBA.R            |   21 +++++------
 graphon-0.3.0/graphon/R/est.USVT.R           |   10 ++---
 graphon-0.3.0/graphon/R/est.completion.R     |   12 +++---
 graphon-0.3.0/graphon/R/est.nbdsmooth.R      |   10 +++--
 graphon-0.3.0/graphon/R/gmodel.ER.R          |   17 ++++-----
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 graphon-0.3.0/graphon/R/gmodel.preset.R      |   13 ++++---
 graphon-0.3.0/graphon/R/graphon-package.R    |   25 ++-----------
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 graphon-0.3.0/graphon/man/est.USVT.Rd        |    9 ++--
 graphon-0.3.0/graphon/man/est.completion.Rd  |   11 +++--
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 graphon-0.3.0/graphon/man/graphon-package.Rd |only
 28 files changed, 176 insertions(+), 190 deletions(-)

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New package VBTree with initial version 0.1.0
Package: VBTree
Type: Package
Title: Vector Binary Tree to Make Your Data Management More Efficient
Version: 0.1.0
Date: 2018-09-05
Author: ZHANG Chen
Maintainer: ZHANG Chen <447974102@qq.com>
Description: Provides a new data structure, vector binary tree, to make your data visiting and management more efficient. if your data has very structurized column names with specific connecting pattern, it can read, split, and factorize these names, then build the mapping from all string objects to an array or tensor, through vector binary tree, by which the batched data processing can be implemented easily. The methods of array and tensor are also applicable.
Imports: tensorA
Depends: R (>= 2.10)
License: GPL-3
URL: https://github.com/CubicZebra/VBTree
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-10 12:06:20 UTC; chen_zhang
Repository: CRAN
Date/Publication: 2018-09-16 18:10:09 UTC

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New package taxotools with initial version 0.0.3
Package: taxotools
Type: Package
Title: Tools to Handle Taxonomic Lists
Version: 0.0.3
Date: 2018-09-10
Authors@R: c( person("Vijay", "Barve", ,"vijay.barve@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4852-2567")))
Maintainer: Vijay Barve <vijay.barve@gmail.com>
Description: Some tools to work with taxonomic name lists.
License: CC0
Imports: taxize, wikitaxa
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
BugReports: https://github.com/vijaybarve/taxotools/issues
NeedsCompilation: no
Packaged: 2018-09-10 14:44:36 UTC; vijaybarve
Author: Vijay Barve [aut, cre] (<https://orcid.org/0000-0002-4852-2567>)
Repository: CRAN
Date/Publication: 2018-09-16 18:20:03 UTC

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New package stylest with initial version 0.1.0
Package: stylest
Version: 0.1.0
Title: Estimating Speaker Style Distinctiveness
Authors@R: c( person("Leslie", "Huang", role = c("aut", "cph", "cre"), email = "lesliehuang@nyu.edu"), person(c("Patrick", "O."), "Perry", role = c("aut", "cph")), person("Arthur", "Spirling", role = c("aut", "cph")))
Depends: R (>= 2.10)
Imports: corpus, Matrix, stats
Suggests: knitr, rmarkdown, testthat, kableExtra
Description: Estimates distinctiveness in speakers' (authors') style. Fits models that can be used for predicting speakers of new texts. Methods developed in Spirling et al (2018) <doi:10.2139/ssrn.3235506> (working paper).
License: GPL-3
URL: https://github.com/leslie-huang/stylest
BugReports: https://github.com/leslie-huang/stylest/issues
LazyData: true
Encoding: UTF-8
VignetteBuilder: knitr, rmarkdown
RoxygenNote: 6.0.1.9000
NeedsCompilation: no
Packaged: 2018-09-10 12:50:57 UTC; lesliehuang
Author: Leslie Huang [aut, cph, cre], Patrick O. Perry [aut, cph], Arthur Spirling [aut, cph]
Maintainer: Leslie Huang <lesliehuang@nyu.edu>
Repository: CRAN
Date/Publication: 2018-09-16 18:10:03 UTC

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New package roundhouse with initial version 0.0.1
Package: roundhouse
Type: Package
Title: An R Wrapper to the 'ICNDb' API
Version: 0.0.1
Authors@R: person("Brandon", "Greenwell", email = "greenwell.brandon@gmail.com", role = c("aut", "cre"))
Description: An R wrapper to the 'Internet Chuck Norris database' ('ICNDb') API for generating random Chuck Norris facts.
License: GPL (>= 2)
URL: ttps://github.com/bgreenwell/roundhouse
BugReports: https://github.com/bgreenwell/roundhouse/issues
Imports: httr, jsonlite
Suggests: covr, magick, testthat
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-09-16 18:02:59 UTC; bgreenwell
Author: Brandon Greenwell [aut, cre]
Maintainer: Brandon Greenwell <greenwell.brandon@gmail.com>
Repository: CRAN
Date/Publication: 2018-09-16 18:30:02 UTC

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New package ojUtils with initial version 0.1.0
Package: ojUtils
Type: Package
Title: A Collection of Utility Functions
Version: 0.1.0
Date: 2018-08-27
Author: Owe Jessen
Maintainer: Owe Jessen <post@owejessen.de>
Description: This is a collection of utility functions. Currently, it provides alternatives to base ifelse() and base combn() functions utilizing 'Rcpp', and providing a significant speedup compared to base.
License: GPL-3
Imports: Rcpp (>= 0.11.0), testthat
LinkingTo: Rcpp
RoxygenNote: 6.1.0
NeedsCompilation: yes
Packaged: 2018-09-10 19:04:44 UTC; Owe
Repository: CRAN
Date/Publication: 2018-09-16 18:30:06 UTC

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New package NTsets with initial version 1.0
Package: NTsets
Type: Package
Title: Normality Test Sets Integrated Function and Figure Methods for Continuous Variables
Version: 1.0
Date: 2018-08-25
Author: Wenlong Ren,Jing Xiao,Yawen Zhang and Zhikai Liang
Maintainer: Wenlong Ren<wenlongren@ntu.edu.cn>
Description: Conduct normality test with nine different function methods and three different figure methods for continuous variables with a friendly GUI. For different data types, provide a more comprehensive means of judgement.
Depends: gWidgets,gWidgetsRGtk2,RGtk2Extras
Imports: RGtk2,methods,nortest,tseries,fBasics
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2018-09-02 13:01:57 UTC; 78165
Repository: CRAN
Date/Publication: 2018-09-16 18:20:06 UTC

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New package MPN with initial version 0.1.0
Package: MPN
Title: Most Probable Number for Serial Dilutions
Version: 0.1.0
Authors@R: c( person("Martine", "Ferguson", email = "Martine.Ferguson@fda.hhs.gov", role = "aut", comment = "original R code"), person("John", "Ihrie", email = "John.Ihrie@fda.hhs.gov", role = c("cre", "aut")))
Maintainer: John Ihrie <John.Ihrie@fda.hhs.gov>
Description: Calculates the Most Probable Number for serial dilutions to quantify the concentration (density) of microbes in a laboratory sample. Currently implements the confidence interval approach described in Jarvis (2010) <doi:10.1111/j.1365-2672.2010.04792.x>.
Depends: R (>= 3.4.0)
License: Unlimited
URL: https://mpncalc.galaxytrakr.org/
LazyData: TRUE
RoxygenNote: 6.1.0
Imports: stats (>= 3.4.0)
Suggests: knitr (>= 1.20), rmarkdown (>= 1.10), testthat (>= 2.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2018-09-04 13:54:02 UTC; John.Ihrie
Author: Martine Ferguson [aut] (original R code), John Ihrie [cre, aut]
Repository: CRAN
Date/Publication: 2018-09-16 18:20:09 UTC

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New package caMST with initial version 0.1.0
Package: caMST
Type: Package
Title: Mixed Computerized Adaptive Multistage Testing
Version: 0.1.0
Date: 2018-08-22
Authors@R: person("Anthony", "Raborn", email = "anthony.w.raborn@gmail.com", role = c("aut","cre"))
Description: Provides functions to more easily analyze computerized adaptive tests. Currently, functions for computerized adaptive tests (CAT), computer adaptive multistage tests (CMT), and mixed computer adaptive multistage tests (McaMST) utilizing CAT item-level adaptation for the initial stage and traditional MST module-level adaptation for the subsequent stages have been created, and a variation of Hybrid computer adaptive MST is planned as well. For an in-depth look at CAT and MST, see Weiss & Kingsbury (1984) <doi:10.1111/j.1745-3984.1984.tb01040.x> and Luecht & Nungester (2000) <doi:10.1007/0-306-47531-6_6> respectively.
License: LGPL (>= 2.0, < 3) | Mozilla Public License
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.2.3)
Imports: catR, mstR
Suggests: testthat, knitr, rmarkdown
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-09-10 14:45:18 UTC; chika
Author: Anthony Raborn [aut, cre]
Maintainer: Anthony Raborn <anthony.w.raborn@gmail.com>
Repository: CRAN
Date/Publication: 2018-09-16 18:10:06 UTC

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New package ahpsurvey with initial version 0.2.1
Package: ahpsurvey
Type: Package
Title: Analytic Hierarchy Process for Survey Data
Version: 0.2.1
Authors@R: person("Frankie", "Cho", email = "htcho@connect.hku.hk", role = c("aut", "cre"))
Description: The Analytic Hierarchy Process is a versatile multi-criteria decision-making tool introduced by Saaty (1987) <doi:10.1016/0270-0255(87)90473-8> that allows decision-makers to weigh attributes and evaluate alternatives presented to them. This package provides a consistent methodology for researchers to reformat data and run analytic hierarchy process in R on data that are formatted using the survey data entry mode. It is optimized for performing the analytic hierarchy process with many decision-makers, and provides tools and options for researchers to aggregate individual preferences and test multiple options. It also allows researchers to quantify, visualize and correct for inconsistency in the decision-maker's comparisons.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Imports: Rdpack, stats, magrittr, knitr, tidyr, dplyr
Suggests: ggplot2, tidyverse, scales
RdMacros: Rdpack
Collate: 'ahp_mat.R' 'ahp_aggjudge.R' 'ahp_aggpref.R' 'ahp_bweight.R' 'ahp_cr.R' 'ahp_indpref.R' 'ahp_error.R' 'ahp_harker.R' 'ahp_missing.R' 'ahp_pwerror.R' 'ahpsurvey.R' 'data.R'
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-10 16:24:00 UTC; chohinting
Author: Frankie Cho [aut, cre]
Maintainer: Frankie Cho <htcho@connect.hku.hk>
Repository: CRAN
Date/Publication: 2018-09-16 18:40:03 UTC

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Package simstudy updated to version 0.1.10 with previous version 0.1.9 dated 2018-05-11

Title: Simulation of Study Data
Description: Simulates data sets in order to explore modeling techniques or better understand data generating processes. The user specifies a set of relationships between covariates, and generates data based on these specifications. The final data sets can represent data from randomized control trials, repeated measure (longitudinal) designs, and cluster randomized trials. Missingness can be generated using various mechanisms (MCAR, MAR, NMAR).
Author: Keith Goldfeld [aut, cre]
Maintainer: Keith Goldfeld <Keith.Goldfeld@nyumc.org>

Diff between simstudy versions 0.1.9 dated 2018-05-11 and 0.1.10 dated 2018-09-16

 DESCRIPTION            |   15 
 MD5                    |  125 +++----
 NAMESPACE              |    3 
 NEWS.md                |    9 
 R/addColumns.R         |    4 
 R/addCondition.R       |    6 
 R/addCorFlex.R         |   12 
 R/addCorGen.R          |  251 ++++++++++----
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Package nnTensor updated to version 0.99.4 with previous version 0.99.1 dated 2018-06-04

Title: Non-Negative Tensor Decomposition
Description: Some functions for performing non-negative matrix factorization, non-negative CANDECOMP/PARAFAC (CP) decomposition, non-negative Tucker decomposition, and generating toy model data. See Andrzej Cichock et al (2009) <doi:10.1002/9780470747278> and the reference section of GitHub README.md <https://github.com/rikenbit/nnTensor>, for details of the methods.
Author: Koki Tsuyuzaki, Manabu Ishii, Itoshi Nikaido
Maintainer: Koki Tsuyuzaki <k.t.the-answer@hotmail.co.jp>

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New package duawranglr with initial version 0.6.3
Package: duawranglr
Title: Securely Wrangle Dataset According to Data Usage Agreement
Version: 0.6.3
Authors@R: person("Benjamin", "Skinner", email = "btskinner@virginia.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-0337-7415"))
URL: https://github.com/btskinner/duawranglr
BugReports: https://github.com/btskinner/duawranglr/issues
Description: Create shareable data sets from raw data files that contain protected elements. Relying on master crosswalk files that list restricted variables, package functions warn users about possible violations of data usage agreement and prevent writing protected elements.
Depends: R (>= 3.1.2)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: haven, readxl, readr, digest, dplyr
RoxygenNote: 6.1.0
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-10 13:05:52 UTC; bts4h
Author: Benjamin Skinner [aut, cre] (<https://orcid.org/0000-0002-0337-7415>)
Maintainer: Benjamin Skinner <btskinner@virginia.edu>
Repository: CRAN
Date/Publication: 2018-09-16 18:00:02 UTC

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Package mapview updated to version 2.6.0 with previous version 2.5.0 dated 2018-08-16

Title: Interactive Viewing of Spatial Data in R
Description: Quickly and conveniently create interactive visualisations of spatial data with or without background maps. Attributes of displayed features are fully queryable via pop-up windows. Additional functionality includes methods to visualise true- and false-color raster images, bounding boxes, small multiples and 3D raster data cubes.
Author: Tim Appelhans [cre, aut], Florian Detsch [aut], Christoph Reudenbach [aut], Stefan Woellauer [aut], Spaska Forteva [ctb], Thomas Nauss [ctb], Edzer Pebesma [ctb], Kenton Russell [ctb], Michael Sumner [ctb], Jochen Darley [ctb], Pierre Roudier [ctb], Patrick Schratz [ctb], Environmental Informatics Marburg [ctb]
Maintainer: Tim Appelhans <tim.appelhans@gmail.com>

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Package knockoff updated to version 0.3.2 with previous version 0.3.0 dated 2017-10-17

Title: The Knockoff Filter for Controlled Variable Selection
Description: The knockoff filter is a general procedure for controlling the false discovery rate (FDR) when performing variable selection. For more information, see the website below and the accompanying paper: Candes et al., "Panning for Gold: Model-X Knockoffs for High-dimensional Controlled Variable Selection", 2016, <arXiv:1610.02351>.
Author: Rina Foygel Barber [ctb] (Development of the original Fixed-X Knockoffs), Emmanuel Candes [ctb] (Development of Model-X Knockoffs and original Fixed-X Knockoffs), Lucas Janson [ctb] (Development of Model-X Knockoffs), Evan Patterson [aut] (Original R package for the original Fixed-X Knockoffs), Matteo Sesia [aut, cre] (R package for Model-X Knockoffs)
Maintainer: Matteo Sesia <msesia@stanford.edu>

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Package fieldRS updated to version 0.1.1 with previous version 0.1.0 dated 2018-08-02

Title: Remote Sensing Field Work Tools
Description: In remote sensing, designing a field campaign to collect ground-truth data can be a challenging task. We need to collect representative samples while accounting for issues such as budget constraints and limited accessibility created by e.g. poor infrastructure. As suggested by Olofsson et al. (2014) <doi:10.1016/j.rse.2014.02.015>, this demands the establishment of best-practices to collect ground-truth data that avoid the waste of time and funds. 'fieldRS' addresses this issue by helping scientists and practitioners design field campaigns through the identification of priority sampling sites, the extraction of potential sampling plots and the conversion of plots into consistent training and validation samples that can be used in e.g. land cover classification.
Author: Ruben Remelgado [aut, cre]
Maintainer: Ruben Remelgado <ruben.remelgado@uni-wuerzburg.de>

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Package dynr updated to version 0.1.13-3 with previous version 0.1.13-2 dated 2018-09-15

Title: Dynamic Modeling in R
Description: Intensive longitudinal data have become increasingly prevalent in various scientific disciplines. Many such data sets are noisy, multivariate, and multi-subject in nature. The change functions may also be continuous, or continuous but interspersed with periods of discontinuities (i.e., showing regime switches). The package 'dynr' (Dynamic Modeling in R) is an R package that implements a set of computationally efficient algorithms for handling a broad class of linear and nonlinear discrete- and continuous-time models with regime-switching properties under the constraint of linear Gaussian measurement functions. The discrete-time models can generally take on the form of a state- space or difference equation model. The continuous-time models are generally expressed as a set of ordinary or stochastic differential equations. All estimation and computations are performed in C, but users are provided with the option to specify the model of interest via a set of simple and easy-to-learn model specification functions in R. Model fitting can be performed using single- subject time series data or multiple-subject longitudinal data.
Author: Lu Ou [aut], Michael D. Hunter [aut, cre], Sy-Miin Chow [aut]
Maintainer: Michael D. Hunter <mhunter.ou@gmail.com>

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Package divest updated to version 0.6.1 with previous version 0.6.0 dated 2018-04-26

Title: Get Images Out of DICOM Format Quickly
Description: Provides tools to sort DICOM-format medical image files, and convert them to NIfTI-1 format.
Author: Jon Clayden [aut, cre], Chris Rorden [aut], Martin J Fiedler [cph], Cong Xu [cph], Pascal Gloor [cph]
Maintainer: Jon Clayden <code@clayden.org>

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Package DHS.rates updated to version 0.4.0 with previous version 0.3.1 dated 2018-06-10

Title: Calculate Key DHS Indicators
Description: Calculates key indicators such as fertility rates (Total Fertility Rate (TFR), General Fertility Rate (GFR), and Age Specific Fertility Rate (ASFR)) using Demographic and Health Survey (DHS) women/individual data, and childhood mortality rates such as Neonatal Mortality Rate (NNMR), Post-neonatal Mortality Rate (PNNMR), Infant Mortality Rate (IMR), Child Mortality Rate (CMR), and Under-five Mortality Rate (U5MR). In addition to the indicators, the 'DHS.rates' package estimates sampling errors indicators such as Standard Error (SE), Design Effect (DEFT), Relative Standard Error (RSE) and Confidence Interval (CI). The package is developed according to the DHS methodology of calculating the fertility indicators and the childhood mortality rates outlined in the "Guide to DHS Statistics" (Croft, Trevor N., Aileen M. J. Marshall, Courtney K. Allen, et al. 2018, <https://dhsprogram.com/Data/Guide-to-DHS-Statistics/index.cfm>) and the DHS methodology of estimating the sampling errors indicators outlined in the "DHS Sampling and Household Listing Manual" (ICF International 2012, <https://dhsprogram.com/pubs/pdf/DHSM4/DHS6_Sampling_Manual_Sept2012_DHSM4.pdf>).
Author: Mahmoud Elkasabi
Maintainer: Mahmoud Elkasabi <mahmoud.elkasabi@icf.com>

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Package brms updated to version 2.5.0 with previous version 2.4.0 dated 2018-07-20

Title: Bayesian Regression Models using 'Stan'
Description: Fit Bayesian generalized (non-)linear multivariate multilevel models using 'Stan' for full Bayesian inference. A wide range of distributions and link functions are supported, allowing users to fit -- among others -- linear, robust linear, count data, survival, response times, ordinal, zero-inflated, hurdle, and even self-defined mixture models all in a multilevel context. Further modeling options include non-linear and smooth terms, auto-correlation structures, censored data, meta-analytic standard errors, and quite a few more. In addition, all parameters of the response distribution can be predicted in order to perform distributional regression. Prior specifications are flexible and explicitly encourage users to apply prior distributions that actually reflect their beliefs. Model fit can easily be assessed and compared with posterior predictive checks and leave-one-out cross-validation. References: Bürkner (2017) <doi:10.18637/jss.v080.i01>; Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>.
Author: Paul-Christian Bürkner [aut, cre]
Maintainer: Paul-Christian Bürkner <paul.buerkner@gmail.com>

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Package recmap updated to version 1.0.0 with previous version 0.5.37 dated 2018-08-28

Title: Compute the Rectangular Statistical Cartogram
Description: Provides an interface and a C++ implementation of the RecMap MP2 construction heuristic (see 'citation("recmap")' for details). This algorithm draws maps according to a given statistical value (e.g., election results, population or epidemiological data). The basic idea of the RecMap algorithm is that each map region (e.g., different countries) is represented by a rectangle. The area of each rectangle represents the statistical value given as input (maintain zero cartographic error). Documentation about RecMap is provided by a vignette included in this package.
Author: Christian Panse [aut, cre] (<https://orcid.org/0000-0003-1975-3064>)
Maintainer: Christian Panse <Christian.Panse@gmail.com>

Diff between recmap versions 0.5.37 dated 2018-08-28 and 1.0.0 dated 2018-09-16

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Package psychReport updated to version 0.2 with previous version 0.1 dated 2018-08-11

Title: Reproducible Reports in Psychology
Description: Helper functions for producing reports in Psychology (Reproducible Research). Provides required formatted strings (APA style) for use in 'Sweave'/'Knitr' 'Latex' integration within *.Rnw files.
Author: Ian G Mackenzie
Maintainer: Ian G Mackenzie <ian.mackenzie@uni-tuebingen.de>

Diff between psychReport versions 0.1 dated 2018-08-11 and 0.2 dated 2018-09-16

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Package rgeopat2 updated to version 0.2.6 with previous version 0.2.5 dated 2018-06-15

Title: Additional Functions for 'GeoPAT' 2
Description: Supports analysis of spatial data processed with the 'GeoPAT' 2 software <http://sil.uc.edu/cms/index.php?id=geopat2>. Available features include creation of a grid based on the 'GeoPAT' 2 grid header file and reading a 'GeoPAT' 2 text outputs.
Author: Jakub Nowosad [aut, cre] (<https://orcid.org/0000-0002-1057-3721>), Space Informatics Lab [cph]
Maintainer: Jakub Nowosad <nowosad.jakub@gmail.com>

Diff between rgeopat2 versions 0.2.5 dated 2018-06-15 and 0.2.6 dated 2018-09-16

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Package usmap updated to version 0.4.0 with previous version 0.3.0 dated 2018-06-03

Title: US Maps Including Alaska and Hawaii
Description: Obtain United States map data frames of varying region types (e.g. county, state). The map data frames include Alaska and Hawaii conveniently placed to the bottom left, as they appear in most maps of the US. Convenience functions for plotting choropleths and working with FIPS codes are also provided.
Author: Paolo Di Lorenzo [aut, cre]
Maintainer: Paolo Di Lorenzo <paolo@dilorenzo.pl>

Diff between usmap versions 0.3.0 dated 2018-06-03 and 0.4.0 dated 2018-09-16

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Package reprex updated to version 0.2.1 with previous version 0.2.0 dated 2018-06-22

Title: Prepare Reproducible Example Code via the Clipboard
Description: Convenience wrapper that uses the 'rmarkdown' package to render small snippets of code to target formats that include both code and output. The goal is to encourage the sharing of small, reproducible, and runnable examples on code-oriented websites, such as <https://stackoverflow.com> and <https://github.com>, or in email. The user's clipboard is the default source of input code and the default target for rendered output. 'reprex' also extracts clean, runnable R code from various common formats, such as copy/paste from an R session.
Author: Jennifer Bryan [aut, cre] (<https://orcid.org/0000-0002-6983-2759>), Jim Hester [aut] (<https://orcid.org/0000-0002-2739-7082>), David Robinson [aut], Hadley Wickham [aut] (<https://orcid.org/0000-0003-4757-117X>), RStudio [cph, fnd]
Maintainer: Jennifer Bryan <jenny@rstudio.com>

Diff between reprex versions 0.2.0 dated 2018-06-22 and 0.2.1 dated 2018-09-16

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 reprex-0.2.1/reprex/NAMESPACE                                                 |    1 
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Package arrangements updated to version 1.1.3 with previous version 1.1.2 dated 2018-08-24

Title: Fast Generators and Iterators for Permutations, Combinations and Partitions
Description: Fast generators and iterators for permutations, combinations and partitions. The iterators allow users to generate arrangements in a memory efficient manner and the generated arrangements are in lexicographical (dictionary) order. Permutations and combinations can be drawn with/without replacement and support multisets. It has been demonstrated that 'arrangements' outperforms most of the existing packages of similar kind. Some benchmarks could be found at <https://randy3k.github.io/arrangements/articles/benchmark.html>.
Author: Randy Lai [aut, cre]
Maintainer: Randy Lai <randy.cs.lai@gmail.com>

Diff between arrangements versions 1.1.2 dated 2018-08-24 and 1.1.3 dated 2018-09-16

 arrangements-1.1.2/arrangements/src/partitions/partitions.h                 |only
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More information about arrangements at CRAN
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