Tue, 14 Nov 2017

Package gravity updated to version 0.5 with previous version 0.3 dated 2017-01-31

Title: A Compilation of Different Estimation Methods for Gravity Models
Description: Gravity models are used to explain bilateral flows related to the sizes of bilateral partners, a measure of distance between them and other influences on interaction costs. The underlying idea is rather simple. The greater the masses of two bodies and the smaller the distance between them, the stronger their attraction. This concept is applied to several research topics such as trade, migration or foreign direct investment. Even though their basic idea is rather simple, gravity models can become complex regarding the choice of models or estimation methods. As especially for gravity beginners it is difficult to get an overview of the different methods and implement them in R, the package provides a wrapper of different standard estimation methods for gravity models. By considering the descriptions and codes of the estimation methods, users get a comprehensive and application-oriented overview of the different methods, see which method may be suitable for a certain research question or type of data and extend the code available to their research projects. The package contains two types of estimation methods: those estimating gravity models in their log-log form, such as Ordinary Least Squares (OLS), Fixed Effects, Double Demeaning (DDM), Bonus vetus OLS with simple averages (BVU) and with GDP-weights (BVW), Structural Iterated Least Squares (SILS) and Tetrads. These methods are partly complex to understand and program and thus a comparison of them is not straightforward, wherefore the package aims at easing an overview of the different methods combined with a direct application. A second type of estimation methods utilizes the gravity model in its multiplicative form with a log-link and different families of distributions. They are relatively easy to compute and added for completeness and contain the methods Poisson Pseudo Maximum Likelihood (PPML), Gamma Pseudo Maximum Likelihood (GPML), Negative Binomial Pseudo Maximum Likelihood (NBPML), and Nonlinear Least Squares (NLS). The functions all estimate gravity models, but they differ in whether they estimate them in their multiplicative or additive form, their requirements with respect to data, their handling of Multilateral Resistance terms as well as their possibilities concerning the inclusion of unilateral independent variables. Therefore, they normally lead to different estimation results. We refer the user to the Gravity Cookbook website (<https://sites.google.com/site/hiegravity/>) for more information on gravity models in general. Head, K. and Mayer, T. (2014) <DOI:10.1016/B978-0-444-54314-1.00003-3> provide a comprehensive and accessible overview of the theoretical and empirical development of the gravity literature as well as the use of gravity models and the various estimation methods, especially their merits and potential problems regarding applicability as well as different gravity datasets. In order to have a straightforward application of all methods, the package comes with an example dataset and examples utilizing this dataset are included in the descriptions of the methods. As the range of gravity models and their suitable estimation methods is huge and specific to data and research question at hand, the functions are kept simple such that researchers can utilize them as a starting point of their research and get familiar with them. On the Gravity Cookbook website (<https://sites.google.com/site/hiegravity/>) Keith Head and Thierry Mayer provide Stata code for most methods. Where possible, the functions are tested to lead the same results as the Stata code when choosing the option of robust variance estimation. However, compared to the Stata code available, the functions presented in this package provide users with more flexibility regarding the type of estimation (robust or not robust), the number and type of independent variables as well as the possible data. Furthermore, additional functions are added. The functions of the package include distance as an independent variable. If a panel model is used time-invariant effects, such as geographical distance, may have to be excluded, see the respective descriptions. Therefore, it is up to the user to ensure that the functions can be applied to panel data. Depending on the panel dataset and the variables - specifically the type of fixed effects - included in the model, it may easily occur that the model is not computable. Depending on the specific model, the code of the respective function may has to be changed in order to exclude the distance variable from the estimation. For a comprehensive overview of gravity models for panel data see Egger, P., & Pfaffermayr, M. (2003) <DOI:10.1007/s001810200146>, Gomez-Herrera, E. (2013) <DOI:10.1007/s00181-012-0576-2> and Head, K., Mayer, T., & Ries, J. (2010) <DOI:10.1016/j.jinteco.2010.01.002> as well as the references therein (see also the references included in the descriptions of the different functions). At the very least, the user should take special care with respect to the meaning of the estimated coefficients and variances as well as the decision about which effects to include in the estimation. As, to our knowledge at the moment, there is no explicit literature covering the estimation of a gravity equation by Double Demeaning, Structural Iterated Least Squares or Bonus vetus OLS using panel data, we do not recommend to apply these methods in this case. Contributions, extensions and error corrections are very welcome. Please do not hesitate to contact us.
Author: Anna-Lena Woelwer <woelwer@uni-trier.de>, Jan Pablo Burgard <burgardj@uni-trier.de>, Martin Bresslein <martin.bresslein@googlemail.com>
Maintainer: Anna-Lena Woelwer <woelwer@uni-trier.de>

Diff between gravity versions 0.3 dated 2017-01-31 and 0.5 dated 2017-11-14

 DESCRIPTION              |   19 +++++-----
 MD5                      |   46 ++++++++++++++------------
 NAMESPACE                |    5 +-
 R/BVU.R                  |    9 ++---
 R/BVW.R                  |    9 ++---
 R/DDM.R                  |   11 +++---
 R/Fixed_effects.R        |   44 +++++++++++++------------
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 R/OLS.R                  |   32 ++++++++++--------
 R/PPML.R                 |   82 ++++++++++++++++++++++++-----------------------
 R/SILS.R                 |    9 ++---
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 man/SILS.Rd              |    9 ++---
 man/Tetrads.Rd           |    3 -
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More information about gravity at CRAN
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Package googleAuthR updated to version 0.6.2 with previous version 0.6.1 dated 2017-11-12

Title: Authenticate and Create Google APIs
Description: Create R functions that interact with OAuth2 Google APIs <https://developers.google.com/apis-explorer/> easily, with auto-refresh and Shiny compatibility.
Author: Mark Edmondson [aut, cre] (0000-0002-8434-3881), Jennifer Bryan [ctb], Johann deBoer [ctb], Neal Richardson [ctb]
Maintainer: Mark Edmondson <m@sunholo.com>

Diff between googleAuthR versions 0.6.1 dated 2017-11-12 and 0.6.2 dated 2017-11-14

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 NEWS.md                                                                          |    6 
 R/auth.R                                                                         |    3 
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 R/checks.R                                                                       |    2 
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 build/vignette.rds                                                               |binary
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 inst/doc/building.html                                                           |  112 +++---
 inst/doc/google-authentication-types.Rmd                                         |   59 +++
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 inst/doc/setup.html                                                              |    6 
 inst/doc/troubleshooting.Rmd                                                     |    1 
 inst/doc/troubleshooting.html                                                    |    7 
 man/gar_cache_setup.Rd                                                           |    3 
 man/gar_set_client.Rd                                                            |only
 tests/testthat/gdrive.oauth                                                      |only
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 vignettes/advanced-building.Rmd                                                  |   22 +
 vignettes/google-authentication-types.Rmd                                        |   59 +++
 vignettes/troubleshooting.Rmd                                                    |    1 
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More information about googleAuthR at CRAN
Permanent link

Package EcoGenetics updated to version 1.2.1-1 with previous version 1.2.1 dated 2017-03-03

Title: Management and Exploratory Analysis of Spatial Data in Landscape Genetics
Description: Management and exploratory analysis of spatial data in landscape genetics. Easy integration of information from multiple sources with "ecogen" objects.
Author: Leandro Roser [aut, cre], Juan Vilardi [aut], Beatriz Saidman [aut], Laura Ferreyra [aut]
Maintainer: Leandro Roser <learoser@gmail.com>

Diff between EcoGenetics versions 1.2.1 dated 2017-03-03 and 1.2.1-1 dated 2017-11-14

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More information about EcoGenetics at CRAN
Permanent link

Package crunch updated to version 1.19.0 with previous version 1.18.4 dated 2017-10-12

Title: Crunch.io Data Tools
Description: The Crunch.io service <http://crunch.io/> provides a cloud-based data store and analytic engine, as well as an intuitive web interface. Using this package, analysts can interact with and manipulate Crunch datasets from within R. Importantly, this allows technical researchers to collaborate naturally with team members, managers, and clients who prefer a point-and-click interface.
Author: Neal Richardson [aut, cre], Jonathan Keane [ctb], Gordon Shotwell [ctb]
Maintainer: Neal Richardson <neal@crunch.io>

Diff between crunch versions 1.18.4 dated 2017-10-12 and 1.19.0 dated 2017-11-14

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 crunch-1.19.0/crunch/DESCRIPTION                                                                   |   48 
 crunch-1.19.0/crunch/MD5                                                                           |  252 +-
 crunch-1.19.0/crunch/NAMESPACE                                                                     |   15 
 crunch-1.19.0/crunch/R/AllClasses.R                                                                |    5 
 crunch-1.19.0/crunch/R/AllGenerics.R                                                               |    2 
 crunch-1.19.0/crunch/R/R-to-variable.R                                                             |    8 
 crunch-1.19.0/crunch/R/add-subvariable.R                                                           |   40 
 crunch-1.19.0/crunch/R/add-variable.R                                                              |   39 
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 crunch-1.19.0/crunch/R/case-variables.R                                                            |   37 
 crunch-1.19.0/crunch/R/categories.R                                                                |   49 
 crunch-1.19.0/crunch/R/category.R                                                                  |   12 
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 crunch-1.19.0/crunch/R/copy.R                                                                      |   22 
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 crunch-1.19.0/crunch/R/crunchbox.R                                                                 |   14 
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 crunch-1.19.0/crunch/R/formula.R                                                                   |  125 -
 crunch-1.19.0/crunch/R/geo.R                                                                       |   76 
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 crunch-1.19.0/crunch/R/json.R                                                                      |   13 
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 crunch-1.19.0/crunch/R/multitables.R                                                               |    2 
 crunch-1.19.0/crunch/R/shoji-order-slots.R                                                         |    2 
 crunch-1.19.0/crunch/R/shoji-order.R                                                               |   13 
 crunch-1.19.0/crunch/R/tab-book.R                                                                  |    4 
 crunch-1.19.0/crunch/R/teams.R                                                                     |    1 
 crunch-1.19.0/crunch/R/variable-to-R.R                                                             |   15 
 crunch-1.19.0/crunch/R/variable.R                                                                  |   26 
 crunch-1.19.0/crunch/R/weight.R                                                                    |   13 
 crunch-1.19.0/crunch/inst/WORDLIST                                                                 |   22 
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Package DPWeibull (with last version 1.1) was removed from CRAN

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

2017-09-04 1.1
2017-06-13 1.0

Permanent link
Package RWekajars updated to version 3.9.1-5 with previous version 3.9.1-4 dated 2017-10-14

Title: R/Weka Interface Jars
Description: External jars required for package 'RWeka'.
Author: Kurt Hornik [aut, cre] (<https://orcid.org/0000-0003-4198-9911>), University of Waikato [ctb, cph] (Weka Java library)
Maintainer: Kurt Hornik <Kurt.Hornik@R-project.org>

Diff between RWekajars versions 3.9.1-4 dated 2017-10-14 and 3.9.1-5 dated 2017-11-14

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Package RWeka updated to version 0.4-36 with previous version 0.4-35 dated 2017-10-14

Title: R/Weka Interface
Description: An R interface to Weka (Version 3.9.1). Weka is a collection of machine learning algorithms for data mining tasks written in Java, containing tools for data pre-processing, classification, regression, clustering, association rules, and visualization. Package 'RWeka' contains the interface code, the Weka jar is in a separate package 'RWekajars'. For more information on Weka see <http://www.cs.waikato.ac.nz/ml/weka/>.
Author: Kurt Hornik [aut, cre] (<https://orcid.org/0000-0003-4198-9911>), Christian Buchta [ctb], Torsten Hothorn [ctb], Alexandros Karatzoglou [ctb], David Meyer [ctb], Achim Zeileis [ctb] (<https://orcid.org/0000-0003-0918-3766>)
Maintainer: Kurt Hornik <Kurt.Hornik@R-project.org>

Diff between RWeka versions 0.4-35 dated 2017-10-14 and 0.4-36 dated 2017-11-14

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Package L1pack updated to version 0.38.19 with previous version 0.38.1 dated 2017-08-15

Title: Routines for L1 Estimation
Description: L1 estimation for linear regression, density, distribution function, quantile function and random number generation for univariate and multivariate Laplace distribution.
Author: Felipe Osorio [aut, cre], Tymoteusz Wolodzko [aut]
Maintainer: Felipe Osorio <felipe.osorios@usm.cl>

Diff between L1pack versions 0.38.1 dated 2017-08-15 and 0.38.19 dated 2017-11-14

 ChangeLog     |    4 ++++
 DESCRIPTION   |    8 ++++----
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 NAMESPACE     |    4 +++-
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 6 files changed, 43 insertions(+), 13 deletions(-)

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New package tribe with initial version 0.1.6
Package: tribe
Type: Package
Title: Play with the Tribe of Attributes
Version: 0.1.6
Date: 2017-11-14
Authors@R: c(person("Paul", "Poncet", , "paulponcet@yahoo.fr", role = c("aut", "cre")), person("Stefan Milton", "Bache", , "stefan@stefanbache.dk", role = "aut", comment = "for functions copied or modified from the 'magrittr' package"), person("Hadley", "Wickham", , "h.wickham@gmail.com", role = "aut", comment = "for functions copied or modified from the 'magrittr' package"))
Description: Functions to make manipulation of object attributes easier. It also contains a few functions that extend the 'dplyr' package for data manipulation, and it provides new pipe operators, including the pipe '%@>%' similar to the 'magrittr' '%>%', but with the additional functionality to enable attributes propagation.
License: MIT + file LICENSE
LazyData: TRUE
Depends: R (>= 3.1.3)
Imports: bazar, dplyr, lazyeval, magrittr, rlist, rstudioapi
VignetteBuilder: knitr
Suggests: knitr, ggplot2, lplyr, observer, testthat
URL: https://github.com/paulponcet/tribe
BugReports: https://github.com/paulponcet/tribe/issues
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-11-14 17:12:04 UTC; YL1101
Author: Paul Poncet [aut, cre], Stefan Milton Bache [aut] (for functions copied or modified from the 'magrittr' package), Hadley Wickham [aut] (for functions copied or modified from the 'magrittr' package)
Maintainer: Paul Poncet <paulponcet@yahoo.fr>
Repository: CRAN
Date/Publication: 2017-11-14 18:11:46 UTC

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Package tidyverse updated to version 1.2.1 with previous version 1.2.0 dated 2017-11-07

Title: Easily Install and Load the 'Tidyverse'
Description: The 'tidyverse' is a set of packages that work in harmony because they share common data representations and 'API' design. This package is designed to make it easy to install and load multiple 'tidyverse' packages in a single step. Learn more about the 'tidyverse' at <https://tidyverse.org>.
Author: Hadley Wickham [aut, cre], RStudio [cph, fnd]
Maintainer: Hadley Wickham <hadley@rstudio.com>

Diff between tidyverse versions 1.2.0 dated 2017-11-07 and 1.2.1 dated 2017-11-14

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New package tidyposterior with initial version 0.0.1
Package: tidyposterior
Version: 0.0.1
Title: Bayesian Analysis to Compare Models using Resampling Statistics
Description: Bayesian analysis used here to answer the question: "when looking at resampling results, are the differences between models 'real'?" To answer this, a model can be created were the performance statistic is the resampling statistics (e.g. accuracy or RMSE). These values are explained by the model types. In doing this, we can get parameter estimates for each model's affect on performance and make statistical (and practical) comparisons between models. The methods included here are similar to Benavoli et al (2017) <http://jmlr.org/papers/v18/16-305.html>.
Authors@R: c( person("Max", "Kuhn", , "max@rstudio.com", c("aut", "cre")), person("RStudio", role = "cph"))
License: GPL-2
URL: https://topepo.github.io/tidyposterior
BugReports: https://github.com/topepo/tidyposterior/issues
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
ByteCompile: true
RoxygenNote: 6.0.1
Depends: ggplot2, broom, R (>= 2.10)
Imports: rsample (>= 0.0.2), tidyr, dplyr, rstanarm, rlang, utils, purrr, tibble
Suggests: knitr, testthat, covr
NeedsCompilation: no
Packaged: 2017-11-14 18:23:20 UTC; max
Author: Max Kuhn [aut, cre], RStudio [cph]
Maintainer: Max Kuhn <max@rstudio.com>
Repository: CRAN
Date/Publication: 2017-11-14 18:55:00 UTC

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New package subsamp with initial version 0.1.0
Package: subsamp
Type: Package
Title: Subsample Winner Algorithm for Variable Selection in Linear Regression with a Large Number of Variables
Version: 0.1.0
Authors@R: c(person("Yiying", "Fan", email = "y.fan67@csuohio.edu", role = c("aut", "cre")),person("Jiayang", "Sun", email = "jsun@case.edu", role = c("aut")),person("Xingye", "Qiao", email = "qiao@math.binghamton.edu", role = c("aut")))
Maintainer: Yiying Fan <y.fan67@csuohio.edu>
Description: This subsample winner algorithm (SWA) for regression with a large-p data (X, Y) selects the important variables (or features) among the p features X in explaining the response Y. The SWA first uses a base procedure, here a linear regression, on each of subsamples randomly drawn from the p variables, and then computes the scores of all features, i.e., the p variables, according to the performance of these features collected in each of the subsample analyses. It then obtains the 'semifinalist' of the features based on the resulting scores and determines the 'finalists', i.e., the important features, from the 'semifinalist'. Fan, Sun and Qiao (2017) <http://sr2c.case.edu/swa-reg/>.
Depends: R (>= 3.0.1)
License: GPL-2 | GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-11-14 17:29:43 UTC; 2566444
Author: Yiying Fan [aut, cre], Jiayang Sun [aut], Xingye Qiao [aut]
Repository: CRAN
Date/Publication: 2017-11-14 18:52:55 UTC

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Package quantregForest updated to version 1.3-6 with previous version 1.3-5 dated 2016-05-19

Title: Quantile Regression Forests
Description: Quantile Regression Forests is a tree-based ensemble method for estimation of conditional quantiles. It is particularly well suited for high-dimensional data. Predictor variables of mixed classes can be handled. The package is dependent on the package 'randomForest', written by Andy Liaw.
Author: Nicolai Meinshausen
Maintainer: Loris Michel <michel@stat.math.ethz.ch>

Diff between quantregForest versions 1.3-5 dated 2016-05-19 and 1.3-6 dated 2017-11-14

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New package nipals with initial version 0.3
Package: nipals
Title: Principal Components Analysis using NIPALS with Gram-Schmidt Orthogonalization
Version: 0.3
Authors@R: person("Kevin", "Wright", email = "kw.stat@gmail.com", role = c("aut", "cre"))
Description: Principal Components Analysis of a matrix using Non-linear Iterative Partial Least Squares with Gram-Schmidt orthogonalization of the scores and loadings. Optimized for speed. See Andrecut (2009) <doi:10.1089/cmb.2008.0221>.
Depends: R (>= 3.4.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
Suggests: knitr, rmarkdown, testthat
URL: https://github.com/kwstat/nipals
BugReports: https://github.com/kwstat/nipals/issues
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-11-14 17:09:24 UTC; wrightkevi
Author: Kevin Wright [aut, cre]
Maintainer: Kevin Wright <kw.stat@gmail.com>
Repository: CRAN
Date/Publication: 2017-11-14 18:50:02 UTC

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Package memery updated to version 0.3.1 with previous version 0.3.0 dated 2017-11-09

Title: Internet Memes for Data Analysts
Description: Generates internet memes that optionally include a superimposed inset plot and other atypical features, combining the visual impact of an attention-grabbing meme with graphic results of data analysis. The package differs from related packages that focus on imitating and reproducing standard memes. Some packages do this by interfacing with online meme generators whereas others achieve this natively. This package takes the latter approach. It does not interface with online meme generators or require any authentication with external websites. It reads images directly from local files or via URL and meme generation is done by the package. While this is similar to the 'meme' package available on CRAN, it differs in that the focus is on allowing for non-standard meme layouts and hybrids of memes mixed with graphs. While this package can be used to make basic memes like an online meme generator would produce, it caters primarily to hybrid graph-meme plots where the meme presentation can be seen as a backdrop highlighting foreground graphs of data analysis results. The package also provides support for an arbitrary number of meme text labels with arbitrary size, position and other attributes rather than restricting to the standard top and/or bottom text placement. This is useful for proper aesthetic interleaving of plots of data between meme image backgrounds and overlain text labels. The package offers a selection of templates for graph placement and appearance with respect to the underlying meme. Graph templates also permit additional template-specific customization.
Author: Matthew Leonawicz [aut, cre]
Maintainer: Matthew Leonawicz <mfleonawicz@alaska.edu>

Diff between memery versions 0.3.0 dated 2017-11-09 and 0.3.1 dated 2017-11-14

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New package ggfan with initial version 0.1.0
Package: ggfan
Type: Package
Title: Summarise a Distribution Through Coloured Intervals
Description: Implements the functionality of the 'fanplot' package as 'geoms' for 'ggplot2'. Designed for summarising MCMC samples from a posterior distribution, where a visualisation is desired for several values of a continuous covariate. Increasing posterior intervals of the sampled quantity are mapped to a continuous colour scale.
Version: 0.1.0
Authors@R: person("Jason", "Hilton", email = "jason_hilton@yahoo.com", role = c("aut", "cre"))
License: GPL-2 | file LICENSE
LazyData: TRUE
Depends: R (>= 3.1)
Imports: ggplot2, colorspace, dplyr, stats, grid
Suggests: testthat, knitr, rmarkdown, tidyr, magrittr, tibble, rstan
URL: https://github.com/jasonhilton/ggfan
BugReports: https://github.com/jasonhilton/ggfan/issues
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-11-14 16:55:48 UTC; jdh1d15
Author: Jason Hilton [aut, cre]
Maintainer: Jason Hilton <jason_hilton@yahoo.com>
Repository: CRAN
Date/Publication: 2017-11-14 18:15:52 UTC

More information about ggfan at CRAN
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Package cdcfluview updated to version 0.7.0 with previous version 0.5.1 dated 2016-12-07

Title: Retrieve 'U.S'. Flu Season Data from the 'CDC' 'FluView' Portal
Description: The 'U.S.' Centers for Disease Control ('CDC') maintains a portal <http://gis.cdc.gov/grasp/fluview/fluportaldashboard.html> for accessing state, regional and national influenza statistics as well as Mortality Surveillance Data. The web interface makes it difficult and time-consuming to select and retrieve influenza data. Tools are provided to access the data provided by the portal's underlying 'API'.
Author: Bob Rudis [aut, cre] (0000-0001-5670-2640), Craig McGowan [ctb] (0000-0002-6298-0185)
Maintainer: Bob Rudis <bob@rud.is>

Diff between cdcfluview versions 0.5.1 dated 2016-12-07 and 0.7.0 dated 2017-11-14

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Package dynsurv updated to version 0.3-6 with previous version 0.3-5 dated 2017-01-09

Title: Dynamic Models for Survival Data
Description: Functions fitting time-varying coefficient models for interval censored and right censored survival data. Three major approaches are implemented: 1) Bayesian Cox model with time-independent, time-varying or dynamic coefficients for right censored and interval censored data; 2) Spline based time-varying coefficient Cox model for right censored data; 3) Transformation model with time-varying coefficients for right censored data using estimating equations.
Author: Wenjie Wang [cre, aut], Ming-Hui Chen [aut], Xiaojing Wang [aut], Jun Yan [aut]
Maintainer: Wenjie Wang <wenjie.2.wang@uconn.edu>

Diff between dynsurv versions 0.3-5 dated 2017-01-09 and 0.3-6 dated 2017-11-14

 ChangeLog             |    9 +++++++
 DESCRIPTION           |   17 +++++++-------
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 NAMESPACE             |    1 
 R/bayesCox.R          |   57 ++++++++++++++++++++++++--------------------------
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Package SpatialFloor updated to version 1.0.2 with previous version 1.0.1 dated 2017-08-30

Title: Spatial Floor Simulation (Isotropic)
Description: Spatial floor simulation with exponential/Gaussian variance-covariance function (isotropic), with specification of distance function, nugget, sill, range. The methodology follows Nole A.C. Cressie (2015) <doi:10.1002/9781119115151>. The original release is 2017-08-29.
Author: Le Zheng <le.zheng@advantaseeds.com>, Martin Grondona <martin.grondona@advantaseeds.com>, Maria Arrieta <maria.arrieta@advantaseeds.com>
Maintainer: Le Zheng <le.zheng@advantaseeds.com>

Diff between SpatialFloor versions 1.0.1 dated 2017-08-30 and 1.0.2 dated 2017-11-14

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 MD5                                  |   21 +++++++++++++--------
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 14 files changed, 28 insertions(+), 22 deletions(-)

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New package QRFCCA with initial version 1.0
Package: QRFCCA
Type: Package
Title: Quadratically Regularized Functional Canonical Correlation Analysis
Version: 1.0
Date: 2017-11-06
Author: Nan Lin and Momiao Xiong
Maintainer: Nan Lin <edmondlinnan@gmail.com>
Description: Conduct quadratically regularized functional canonical correlation analysis. The details of the method are explained in Nan Lin, Yun Zhu, Ruzhong Fan and Momiaoxiong (2017) <DOI:10.1371/journal.pcbi.1005788>.
License: GPL-2 | GPL-3
Depends: graphics,grDevices,stats,utils,fda,MASS,flare,corpcor,igraph
NeedsCompilation: no
Packaged: 2017-11-14 16:32:54 UTC; nlin
Repository: CRAN
Date/Publication: 2017-11-14 16:48:41 UTC

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New package ML.MSBD with initial version 1.0.0
Package: ML.MSBD
Type: Package
Title: Maximum Likelihood Inference on Multi-State Trees
Version: 1.0.0
Date: 2017-10-25
Authors@R: person("Joelle", "Barido-Sottani", email = "joelle.barido-sottani@m4x.org", role = c("aut", "cre"))
Description: Inference of a multi-states birth-death model from a phylogeny, comprising a number of states N, birth and death rates for each state and on which edges each state appears. Inference is done using a hybrid approach: states are progressively added in a greedy approach. For a fixed number of states N the best model is selected via maximum likelihood. Reference: J. Barido-Sottani and T. Stadler (2017) <doi:10.1101/215491>.
License: GPL-3
Imports: ape (>= 4.1)
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-11-14 16:35:57 UTC; bjoelle
Author: Joelle Barido-Sottani [aut, cre]
Maintainer: Joelle Barido-Sottani <joelle.barido-sottani@m4x.org>
Repository: CRAN
Date/Publication: 2017-11-14 16:54:53 UTC

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Package inlabru updated to version 2.1.2 with previous version 2.1.1 dated 2017-11-10

Title: Spatial Inference using Integrated Nested Laplace Approximation
Description: Facilitates spatial modeling using integrated nested Laplace approximation via the INLA package (<http://www.r-inla.org>). Additionally, implements a log Gaussian Cox process likelihood for modeling univariate and spatial point processes based on ecological survey data. See Yuan Yuan, Fabian E. Bachl, Finn Lindgren, David L. Borchers, Janine B. Illian, Stephen T. Buckland, Havard Rue, Tim Gerrodette (2017), <arXiv:1604.06013>.
Author: Fabian E. Bachl <bachlfab@gmail.com> (main code), Finn Lindgren <Finn.Lindgren@ed.ac.uk> (SPDE posterior plotting), David L. Borchers <dlb@st-andrews.ac.uk> (Gorilla data import and sampling, multiplot tool), Daniel Simpson <dp.simpson@gmail.com> (basic LGCP sampling method), Lindesay Scott-Hayward <lass@@st-andrews.ac.uk> (MRSea data import)
Maintainer: Fabian E. Bachl <bachlfab@gmail.com>

Diff between inlabru versions 2.1.1 dated 2017-11-10 and 2.1.2 dated 2017-11-14

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Package coop updated to version 0.6-1 with previous version 0.6-0 dated 2016-12-12

Title: Co-Operation: Fast Covariance, Correlation, and Cosine Similarity Operations
Description: Fast implementations of the co-operations: covariance, correlation, and cosine similarity. The implementations are fast and memory-efficient and their use is resolved automatically based on the input data, handled by R's S3 methods. Full descriptions of the algorithms and benchmarks are available in the package vignettes.
Author: Drew Schmidt [aut, cre], Christian Heckendorf [ctb] (Caught some memory errors.)
Maintainer: Drew Schmidt <wrathematics@gmail.com>

Diff between coop versions 0.6-0 dated 2016-12-12 and 0.6-1 dated 2017-11-14

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New package bestNormalize with initial version 0.2.2
Package: bestNormalize
Type: Package
Title: Normalizing Transformation Functions
Version: 0.2.2
Date: 2017-11-13
Authors@R: person("Ryan Andrew", "Peterson", email = "ryan-peterson@uiowa.edu", role = c("aut", "cre"))
Description: Estimate a suite of normalizing transformations, including a new technique based on ranks which can guarantee normally distributed transformed data if there are no ties: Ordered Quantile Normalization. The package is built to estimate the best normalizing transformation for a vector consistently and accurately. It implements the Box-Cox transformation, the Yeo-Johnson transformation, three types of Lambert WxF transformations, and the Ordered Quantile normalization transformation.
URL: https://github.com/petersonR/bestNormalize
License: GPL-3
Depends: R (>= 3.1.0)
Imports: LambertW, nortest
Suggests: knitr, MASS, testthat, mgcv
VignetteBuilder: knitr
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-11-14 16:19:48 UTC; rpterson
Author: Ryan Andrew Peterson [aut, cre]
Maintainer: Ryan Andrew Peterson <ryan-peterson@uiowa.edu>
Repository: CRAN
Date/Publication: 2017-11-14 16:26:23 UTC

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New package PreciseSums with initial version 0.1
Package: PreciseSums
Title: Accurate Floating Point Sums and Products
Version: 0.1
Authors@R: c(person("Matthew","Fidler", role = c("aut","cre","cph"), email = "matthew.fidler@gmail.com"), person("Raymond","Hettinger",role=c("cph","aut")), person("Jonathan", "Shewchuk",role=c("cph","aut")), person("Julian", "Taylor",role=c("cph","aut")), person("Nathaniel", "Smith",role=c("cph","aut")), person("NumPy Team", role="cph"), person("Python Team", role="cph") )
Description: Most of the time floating point arithmetic does approximately the right thing. When adding sums or having products of numbers that greatly differ in magnitude, the floating point arithmetic may be incorrect. This package implements the Kahan (1965) sum <doi:10.1145/363707.363723>, Neumaier (1974) sum <doi:10.1002/zamm.19740540106>, pairwise-sum (adapted from 'NumPy', See Castaldo (2008) <doi:10.1137/070679946> for a discussion of accuracy), and arbitrary precision sum (adapted from the fsum in 'Python' ; Shewchuk (1997) <http://www.cs.berkeley.edu/~jrs/papers/robustr.pdf>). In addition, products are changed to long double precision for accuracy, or changed into a log-sum for accuracy.
Depends: R (>= 3.2)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Suggests: testthat
NeedsCompilation: yes
Packaged: 2017-11-14 14:30:44 UTC; FIDLEMA3
Author: Matthew Fidler [aut, cre, cph], Raymond Hettinger [cph, aut], Jonathan Shewchuk [cph, aut], Julian Taylor [cph, aut], Nathaniel Smith [cph, aut], NumPy Team [cph], Python Team [cph]
Maintainer: Matthew Fidler <matthew.fidler@gmail.com>
Repository: CRAN
Date/Publication: 2017-11-14 15:48:25 UTC

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New package OptimalTiming with initial version 0.1.0
Package: OptimalTiming
Type: Package
Title: Optimal Timing Identification
Version: 0.1.0
Author: Xiao Lin <xlin3@mdanderson.org>, Xuelin Huang<xlhuang@mdanderson.org>
Maintainer: Xiao Lin <xlin3@mdanderson.org>
Description: Identify the optimal timing for new treatment initiation during multiple state disease transition, including multistate model fitting, simulation of mean residual lifetime for a given transition state, and estimation of confidence interval. The method is referred to de Wreede, L., Fiocco, M., & Putter, H. (2011) <doi:10.18637/jss.v038.i07>.
Depends: R (>= 3.0.0)
Imports: mstate, survival
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
LazyLoad: true
RoxygenNote: 6.0.1
Packaged: 2017-11-14 15:15:34 UTC; xlin3
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2017-11-14 15:52:34 UTC

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New package oaqc with initial version 1.0
Package: oaqc
Title: Computation of the Orbit-Aware Quad Census
Version: 1.0
Authors@R: c(person("Mark", "Ortmann", email = "mark.ortmann@uni.kn", role = c("aut", "cre")), person("Felix", "Schoenenberger", role = c("aut")))
Description: Implements the efficient algorithm by Ortmann and Brandes (2017) <doi:10.1007/s41109-017-0027-2> to compute the orbit-aware frequency distribution of induced and non-induced quads, i.e. subgraphs of size four. Given an edge matrix, data frame, or a graph object (e.g., 'igraph'), the orbit-aware counts are computed respective each of the edges and nodes.
Depends: R (>= 3.4)
Suggests: igraph, knitr, rmarkdown
License: GPL-3
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
SystemRequirements: C++11
RoxygenNote: 6.0.1
VignetteBuilder: knitr
Packaged: 2017-11-14 13:04:59 UTC; ortmann
Author: Mark Ortmann [aut, cre], Felix Schoenenberger [aut]
Maintainer: Mark Ortmann <mark.ortmann@uni.kn>
Repository: CRAN
Date/Publication: 2017-11-14 15:17:21 UTC

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New package likelihoodExplore with initial version 0.1.0
Package: likelihoodExplore
Type: Package
Title: Likelihood Exploration
Version: 0.1.0
Authors@R: c(person("Ben", "Barnard", email = "ben_barnard@outlook.com", role = c("aut", "cre")))
Maintainer: Ben Barnard <ben_barnard@outlook.com>
Description: Provides likelihood functions as defined by Fisher (1922) <doi:10.1098/rsta.1922.0009> and a function that creates likelihood functions from density functions. The functions are meant to aid in education of likelihood based methods.
License: GPL-2
LazyData: TRUE
RoxygenNote: 6.0.1
Suggests: covr
Imports: lazyeval, plyr
URL: https://likelihoodExplore.bearstatistics.com
NeedsCompilation: no
Packaged: 2017-11-14 14:52:30 UTC; ben_barnard
Author: Ben Barnard [aut, cre]
Repository: CRAN
Date/Publication: 2017-11-14 15:51:01 UTC

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Package ggpubr updated to version 0.1.6 with previous version 0.1.5 dated 2017-08-22

Title: 'ggplot2' Based Publication Ready Plots
Description: 'ggplot2' is an excellent and flexible package for elegant data visualization in R. However the default generated plots requires some formatting before we can send them for publication. Furthermore, to customize a 'ggplot', the syntax is opaque and this raises the level of difficulty for researchers with no advanced R programming skills. 'ggpubr' provides some easy-to-use functions for creating and customizing 'ggplot2'- based publication ready plots.
Author: Alboukadel Kassambara [aut, cre]
Maintainer: Alboukadel Kassambara <alboukadel.kassambara@gmail.com>

Diff between ggpubr versions 0.1.5 dated 2017-08-22 and 0.1.6 dated 2017-11-14

 DESCRIPTION                                               |   28 +--
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 NAMESPACE                                                 |    5 
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Package BoSSA updated to version 2.2 with previous version 2.1 dated 2017-05-09

Title: A Bunch of Structure and Sequence Analysis
Description: Reads and plots phylogenetic placements obtained using the 'pplacer' and 'guppy' softwares <https://matsen.github.io/pplacer/>.
Author: Pierre Lefeuvre
Maintainer: Pierre Lefeuvre <pierre.lefeuvre@cirad.fr>

Diff between BoSSA versions 2.1 dated 2017-05-09 and 2.2 dated 2017-11-14

 DESCRIPTION                  |   12 +-
 MD5                          |   46 ++++---
 NAMESPACE                    |    4 
 R/plot.pplace.R              |   15 ++
 R/pplace_to_matrix.R         |   31 ++++-
 R/pplace_to_taxonomy.R       |   21 ++-
 R/print.jplace.R             |only
 R/print.pplace.R             |    2 
 R/read_jplace.R              |   30 ++++-
 R/read_sqlite.R              |    2 
 R/refpkg.R                   |  254 +++++++++++++++++++++++--------------------
 build/partial.rdb            |binary
 inst/doc/bossa-analysis.Rmd  |    8 -
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 inst/doc/bossa-refpkg.R      |   10 +
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 man/pplace_to_taxonomy.Rd    |   12 --
 man/print.pplace.Rd          |    8 -
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 vignettes/bossa-analysis.Rmd |    8 -
 vignettes/bossa-refpkg.Rmd   |   34 +++++
 25 files changed, 439 insertions(+), 243 deletions(-)

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New package BootValidation with initial version 0.1.3
Package: BootValidation
Type: Package
Title: Adjusting for Optimism in 'glmnet' Regression using Bootstrapping
Version: 0.1.3
Author: Antonio Jose Canada Martinez
Maintainer: Antonio Jose Canada Martinez <ancamar2@gmail.com>
Description: Main objective of a predictive model is to provide accurated predictions of a new observations. Unfortunately we don't know how well the model performs. In addition, at the current era of omic data where p >> n, is not reasonable applying internal validation using data-splitting. Under this background a good method to assessing model performance is applying internal bootstrap validation (Harrell Jr, Frank E (2015) <doi:10.1007/978-1-4757-3462-1>.) This package provides bootstrap validation for the linear and logistic 'glmnet' models.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: glmnet, pbapply, pROC, parallel
RdMacros: Rdpack
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-11-14 13:28:30 UTC; 53257632M
Repository: CRAN
Date/Publication: 2017-11-14 15:30:31 UTC

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Package bazar updated to version 1.0.6 with previous version 0.1.6 dated 2017-06-25

Title: Miscellaneous Basic Functions
Description: A collection of miscellaneous functions for copying objects to the clipboard ('Copy'); manipulating strings ('concat', 'mgsub', 'trim', 'verlan'); loading or showing packages ('library_with_dep', 'require_with_dep', 'sessionPackages'); creating or testing for named lists ('nlist', 'as.nlist', 'is.nlist'), formulas ('is.formula'), empty objects ('as.empty', 'is.empty'), whole numbers ('as.wholenumber', 'is.wholenumber'); testing for equality ('almost.equal', 'almost.zero') and computing uniqueness ('almost.unique'); getting modified versions of usual functions ('rle2', 'sumNA'); making a pause or a stop ('pause', 'stopif'); converting into a function ('as.fun'); providing a C like ternary operator ('condition %?% true %:% false'); finding packages and functions ('get_all_pkgs', 'get_all_funs'); and others ('erase', '%nin%', 'unwhich', 'top', 'bot', 'normlize').
Author: Paul Poncet [aut, cre]
Maintainer: Paul Poncet <paulponcet@yahoo.fr>

Diff between bazar versions 0.1.6 dated 2017-06-25 and 1.0.6 dated 2017-11-14

 DESCRIPTION              |   16 ++++++++-----
 MD5                      |   34 +++++++++++++++++++++--------
 NAMESPACE                |   22 +++++++++++++++++++
 NEWS.md                  |   54 +++++++++++++++++++++++++++++++++++++++++++++++
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 R/as.fun.R               |only
 R/erase.R                |    3 +-
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 man/normalize.Rd         |only
 man/rollfun.Rd           |only
 man/ternary_operation.Rd |only
 man/top.Rd               |only
 26 files changed, 133 insertions(+), 25 deletions(-)

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Package antaresRead updated to version 2.0.1 with previous version 2.0.0 dated 2017-11-06

Title: Import, Manipulate and Explore the Results of an Antares Simulation
Description: Import, manipulate and explore results generated by Antares, a powerful software developed by RTE to simulate and study electric power systems (more information about Antares here: <https://antares.rte-france.com>).
Author: Jalal-Edine ZAWAM [aut, cre], Francois Guillem [aut], Benoit Thieurmel [aut], Titouan Robert [aut], RTE [cph]
Maintainer: Jalal-Edine ZAWAM <jalal-edine.zawam@rte-france.com>

Diff between antaresRead versions 2.0.0 dated 2017-11-06 and 2.0.1 dated 2017-11-14

 DESCRIPTION                       |    8 -
 MD5                               |   26 ++---
 NEWS                              |    4 
 R/h5_antaresReadH5.R              |    9 +
 R/importOutput.R                  |    4 
 R/readAntares.R                   |    8 +
 R/readLayout.R                    |    2 
 inst/doc/antares.html             |    4 
 inst/doc/antaresH5.html           |    4 
 tests/testthat/helper_init.R      |  186 +++++++++++++++++++-------------------
 tests/testthat/test-h5_write.R    |   27 ++++-
 tests/testthat/test-readLayout.R  |    6 +
 tests/testthat/test-setup.R       |   60 ++++++------
 tests/testthat/test-viewAntares.R |   56 +++++------
 14 files changed, 225 insertions(+), 179 deletions(-)

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New package rpgm with initial version 1.1.1
Package: rpgm
Type: Package
Title: Fast Simulation of Normal/Exponential Random Variables and Stochastic Differential Equations / Poisson Processes
Version: 1.1.1
Date: 2017-08-10
Author: Nicolas Baradel
Maintainer: Nicolas Baradel - PGM Solutions <nicolas.baradel@pgm-solutions.com>
Description: Fast simulation of some random variables than the usual native functions, including rnorm() and rexp(), using Ziggurat method, reference: MARSAGLIA, George, TSANG, Wai Wan, and al. (2000) <doi:10.18637/jss.v005.i08>, and fast simulation of stochastic differential equations / Poisson processes.
License: GPL-3
URL: https://pgm-solutions.com/packages
NeedsCompilation: yes
SystemRequirements: C++11
Packaged: 2017-11-14 09:50:08 UTC; Nicolas
Repository: CRAN
Date/Publication: 2017-11-14 14:44:20 UTC

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New package Rgretl with initial version 0.1.5
Package: Rgretl
Type: Package
Title: Interface to 'gretlcli'
Version: 0.1.5
Date: 2017-11-08
Author: Oleh Komashko
Maintainer: Oleh Komashko <oleg_komashko@ukr.net>
Depends: R (>= 3.3.1)
Imports: compiler
SystemRequirements: gretl (>= 2016c), gretlcli
Description: An interface to 'GNU gretl': running 'gretl' scripts from, estimating econometric models with backward passing of model results, opening 'gretl' data files (.gdt). 'gretl' can be downloaded from <http://gretl.sourceforge.net>. This package could make life on introductory/intermediate econometrics courses much easier: full battery of the required regression diagnostics, including White's heteroskedasticity test, restricted ols estimation, advanced weak instrument test after iv estimation, very convenient dealing with lagged variables in models, standard case treatment in unit root tests, vector auto- regressions, and vector error correction models. Datasets for 8 popular econometrics textbooks can be installed into 'gretl' from its server. All datasets can be easily imported using this package.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2017-11-07 22:40:28 UTC; oleh
Repository: CRAN
Date/Publication: 2017-11-14 13:46:30 UTC

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Package popEpi updated to version 0.4.4 with previous version 0.4.3 dated 2017-09-05

Title: Functions for Epidemiological Analysis using Population Data
Description: Enables computation of epidemiological statistics where e.g. counts or mortality rates of the reference population are used. Currently supported: excess hazard models, rates, mean survival times, relative survival, as well as standardized incidence and mortality ratios (SIRs/SMRs), all of which can be easily adjusted for e.g. age. Fast splitting and aggregation of 'Lexis' objects (from package 'Epi') and other computations achieved using 'data.table'.
Author: Joonas Miettinen [aut, cre], Matti Rantanen [aut], Karri Seppa [ctb]
Maintainer: Joonas Miettinen <joonas.miettinen@cancer.fi>

Diff between popEpi versions 0.4.3 dated 2017-09-05 and 0.4.4 dated 2017-11-14

 DESCRIPTION                                             |    8 
 MD5                                                     |  261 -
 NAMESPACE                                               |  176 
 NEWS.md                                                 |  267 -
 R/S3_definitions.R                                      | 2946 ++++++++--------
 R/aggregating.R                                         | 1232 +++---
 R/data_document.R                                       |  348 -
 R/direct_adjusting.R                                    |  314 -
 R/evaluation.R                                          | 1878 +++++-----
 R/flexyargs.R                                           |  332 -
 R/fractional_years.R                                    |  300 -
 R/incidence_rates.R                                     |  686 +--
 R/incidence_rates_utils.R                               |  266 -
 R/lexpand.R                                             | 1873 +++++-----
 R/lexpand2.R                                            |  278 -
 R/lifetime_function.R                                   |  564 +--
 R/ltable.R                                              |  502 +-
 R/mean_survival.R                                       | 1326 +++----
 R/popEpi_package.r                                      |   60 
 R/pophaz.R                                              |  136 
 R/prevalence.R                                          |  282 -
 R/relative_poisson.R                                    | 1217 +++---
 R/relative_poisson_net_survival.R                       |  352 -
 R/sir.R                                                 | 2893 +++++++--------
 R/sir_utils.R                                           |  226 -
 R/splitLexisDT.R                                        |  543 +-
 R/splitMulti.R                                          |  504 +-
 R/splitting_utility_functions.R                         | 2514 +++++++------
 R/startup_message.R                                     |   60 
 R/survival_aggregated.R                                 | 1780 ++++-----
 R/survival_lexis.R                                      | 1184 +++---
 R/survival_utility_functions.R                          | 1273 +++---
 R/utility_functions.R                                   | 2830 +++++++--------
 R/weighted_table.R                                      | 1328 +++----
 README.md                                               |  378 +-
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 inst/doc/survtab_examples.Rmd                           |  592 +--
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 man/ICSS.Rd                                             |   72 
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 man/RPL.Rd                                              |   42 
 man/adjust.Rd                                           |   48 
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 man/lines.sirspline.Rd                                  |   84 
 man/lines.survmean.Rd                                   |   70 
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 man/poisson.ci.Rd                                       |   52 
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 man/rate.Rd                                             |  208 -
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 man/setclass.Rd                                         |   54 
 man/setcolsnull.Rd                                      |   64 
 man/sibr.Rd                                             |   76 
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 man/sir_exp.Rd                                          |  204 -
 man/sir_ratio.Rd                                        |  162 
 man/sire.Rd                                             |   74 
 man/sirspline.Rd                                        |  282 -
 man/splitLexisDT.Rd                                     |  176 
 man/splitMulti.Rd                                       |  264 -
 man/stdpop101.Rd                                        |   54 
 man/stdpop18.Rd                                         |   58 
 man/summary.aggre.Rd                                    |   64 
 man/summary.survtab.Rd                                  |  188 -
 man/survmean.Rd                                         |  560 +--
 man/survtab.Rd                                          |  616 +--
 man/survtab_ag.Rd                                       |  782 ++--
 man/try2int.Rd                                          |   54 
 tests/testthat.R                                        |    8 
 tests/testthat/test_aggre.R                             |  458 +-
 tests/testthat/test_epi.R                               |   68 
 tests/testthat/test_expo.R                              |   94 
 tests/testthat/test_lexpand.R                           |  750 ++--
 tests/testthat/test_prevtab.R                           |   40 
 tests/testthat/test_rate.R                              |  624 +--
 tests/testthat/test_relpois_mean_curve.R                |  136 
 tests/testthat/test_sir.R                               |  882 ++--
 tests/testthat/test_splitLexisDT.R                      |  249 -
 tests/testthat/test_splitMulti.R                        |  241 -
 tests/testthat/test_splitting_attributes.R              |only
 tests/testthat/test_splitting_breaks.R                  |  160 
 tests/testthat/test_splitting_randomly.R                |only
 tests/testthat/test_splitting_randomly_on_random_data.R |only
 tests/testthat/test_survmean.R                          |  606 +--
 tests/testthat/test_survtab_adjusted.R                  |  152 
 tests/testthat/test_survtab_bad_surv_ints.R             |  190 -
 tests/testthat/test_survtab_observed.R                  |  266 -
 tests/testthat/test_survtab_relative.R                  |  396 +-
 tests/testthat/test_survtab_usage.R                     |  960 ++---
 tests/testthat/test_utils.R                             |  834 ++--
 tests/testthat/test_weighter.R                          |  278 -
 vignettes/sir.Rmd                                       |  319 -
 vignettes/survtab_examples.Rmd                          |  592 +--
 133 files changed, 26630 insertions(+), 26089 deletions(-)

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Package systemicrisk updated to version 0.4.1 with previous version 0.4 dated 2017-01-08

Title: A Toolbox for Systemic Risk
Description: A toolbox for systemic risk based on liabilities matrices. Contains a Gibbs sampler for liabilities matrices where only row and column sums of the liabilities matrix as well as some other fixed entries are observed. Includes models for power law distribution on the degree distribution.
Author: Axel Gandy and Luitgard A.M. Veraart
Maintainer: Axel Gandy <a.gandy@imperial.ac.uk>

Diff between systemicrisk versions 0.4 dated 2017-01-08 and 0.4.1 dated 2017-11-14

 DESCRIPTION                       |    8 +++---
 MD5                               |   21 ++++++++++------
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 build/vignette.rds                |binary
 inst/CITATION                     |   13 ++++++++--
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 14 files changed, 74 insertions(+), 40 deletions(-)

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New package mazealls with initial version 0.1.0
Package: mazealls
Maintainer: Steven E. Pav <shabbychef@gmail.com>
Authors@R: c(person(c("Steven", "E."), "Pav", role=c("aut","cre"), email="shabbychef@gmail.com", comment = c(ORCID = "0000-0002-4197-6195")))
Version: 0.1.0
Date: 2017-11-13
License: LGPL-3
Title: Generate Recursive Mazes
BugReports: https://github.com/shabbychef/mazealls/issues
Description: Supports the generation of parallelogram, equilateral triangle, regular hexagon, isosceles trapezoid and Koch snowflake mazes via 'TurtleGraphics'. Mazes are generated by the recursive method: the domain is divided into sub-domains in which mazes are generated, then dividing lines with holes are drawn between them, see J. Buck, Recursive Division, <http://weblog.jamisbuck.org/2011/1/12/maze-generation-recursive-division-algorithm>.
Depends: R (>= 3.0.2)
Imports: TurtleGraphics
Suggests: testthat, knitr
URL: https://github.com/shabbychef/mazealls
Collate: 'eq_triangle_maze.r' 'hexagon_maze.r' 'holey_line.r' 'holey_path.r' 'iso_trapezoid_maze.r' 'koch_maze.r' 'mazealls.r' 'parallelogram_maze.r' 'utils.r'
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-11-14 06:23:32 UTC; root
Author: Steven E. Pav [aut, cre] (0000-0002-4197-6195)
Repository: CRAN
Date/Publication: 2017-11-14 11:21:21 UTC

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Package shinyKGode updated to version 1.0.1 with previous version 1.0.0 dated 2017-11-13

Title: An Interactive Application for ODE Parameter Inference Using Gradient Matching
Description: An interactive Shiny application to perform fast parameter inference on dynamical systems (described by ordinary differential equations) using gradient matching. Please see the project page for more details.
Author: Joe Wandy
Maintainer: Joe Wandy <joe.wandy@glasgow.ac.uk>

Diff between shinyKGode versions 1.0.0 dated 2017-11-13 and 1.0.1 dated 2017-11-14

 DESCRIPTION       |   19 +++++++++----------
 MD5               |    5 +++--
 README.md         |    2 +-
 man/shinyKGode.Rd |only
 4 files changed, 13 insertions(+), 13 deletions(-)

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New package variosig with initial version 0.1
Package: variosig
Type: Package
Imports: gstat, geoR, sp
Depends: R (>= 3.1.0)
Title: Spatial Dependence Based on Empirical Variograms
Version: 0.1
Author: Craig Wang
Maintainer: Craig Wang <craig.wang@uzh.ch>
Description: Apply Monte Carlo permutation to compute pointwise variogram envelopes, and check spatial dependence using permutation test adjusted for multiple testing.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2017-11-13 20:44:07 UTC; craigwang
Repository: CRAN
Date/Publication: 2017-11-14 09:21:16 UTC

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New package rpicosat with initial version 1.0.0
Package: rpicosat
Type: Package
Title: R Bindings for the 'PicoSAT' SAT Solver
Authors@R: c( person("Dirk", "Schumacher", email = "mail@dirk-schumacher.net", role = c("aut", "cre")), person("Armin", "Biere", role = c("ctb", "cph"), comment = "Author and copyright holder of included PicoSAT code"))
Version: 1.0.0
Description: Bindings for the 'PicoSAT' solver to solve Boolean satisfiability problems (SAT). The boolean satisfiability problem asks the question if a given boolean formula can be TRUE; i.e. does there exist an assignment of TRUE/FALSE for each variable such that the whole formula is TRUE? The package bundles 'PicoSAT' solver release 965 <http://www.fmv.jku.at/picosat/>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
ByteCompile: true
RoxygenNote: 6.0.1
URL: https://github.com/dirkschumacher/rpicosat
BugReports: https://github.com/dirkschumacher/rpicosat/issues
NeedsCompilation: yes
Depends: R (>= 3.4.0)
Suggests: testthat, covr
Packaged: 2017-11-13 18:11:42 UTC; dirkschumacher
Author: Dirk Schumacher [aut, cre], Armin Biere [ctb, cph] (Author and copyright holder of included PicoSAT code)
Maintainer: Dirk Schumacher <mail@dirk-schumacher.net>
Repository: CRAN
Date/Publication: 2017-11-14 09:26:48 UTC

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Package dataCompareR updated to version 0.1.1 with previous version 0.1.0 dated 2017-07-17

Title: Compare Two Data Frames and Summarise the Difference
Description: Easy comparison of two tabular data objects in R. Specifically designed to show differences between two sets of data in a useful way that should make it easier to understand the differences, and if necessary, help you work out how to remedy them. Aims to offer a more useful output than all.equal() when your two data sets do not match, but isn't intended to replace all.equal() as a way to test for equality.
Author: Rob Noble-Eddy [aut, cre], Sarah Johnston [aut], Sarah Pollicott [aut], Merlijn van Horssen [aut], Lukas Drapal [ctb], Nikolaos Perrakis [ctb], Nikhil Thomas Joy [ctb], Shahriar Asta [ctb], Karandeep Lidher [ctb], Dan Kellett [ctb], Kevin Chisholm [ctb], Laura Joy [ctb], Fergus Wadsley [ctb], Heather Hackett [ctb], David Robinson [ctb], Cheryl Renton [ctb], Matt Triggs [ctb], Krishan Bhasin [ctb], Carola Deppe [ctb]
Maintainer: Rob Noble-Eddy <opensource@capitalone.com>

Diff between dataCompareR versions 0.1.0 dated 2017-07-17 and 0.1.1 dated 2017-11-14

 DESCRIPTION                                     |   10 
 LICENSE                                         |   14 
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 NAMESPACE                                       |    2 
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 R/out_createReportText.R                        |   50 -
 R/out_generateMismatchData.R                    |  230 +++----
 R/out_helperFunctions.R                         |   70 +-
 R/out_outputStructureFunctions.R                |  148 ++--
 R/out_printrcompareobject.R                     |  290 ++++-----
 R/out_printsummaryrcompareobject.R              |   50 -
 R/out_rCompObjectQueryFunctions.R               |  126 ++--
 R/out_saveReport.R                              |  226 +++----
 R/out_summaryrcompareobject.R                   |  588 +++++++++----------
 R/out_unifiedOutputGenerator.R                  |  452 +++++++-------
 R/pd_coerceFactorsToChar.R                      |   52 -
 R/pd_executeCoercions.R                         |  116 +--
 R/pd_matchColumns.R                             |  204 +++---
 R/pd_matchRows.R                                |  370 ++++++------
 R/pd_prepareData.R                              |   96 +--
 R/pd_trimCharVars.R                             |   52 -
 R/pf_createCompareObject.R                      |   48 -
 R/pf_processFlow.R                              |  132 ++--
 R/rc_coerceData.R                               |  148 ++--
 R/rc_isRCompareObject.R                         |   42 -
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 R/rc_rounddf.R                                  |   48 -
 R/rc_validateArguments.R                        |  246 ++++----
 R/rco_createCleaningInfo.R                      |   82 +-
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 R/rco_updateCompareObject_ColMatching.R         |   60 -
 R/rco_updateCompareObject_Matches.R             |   42 -
 R/rco_updateCompareObject_Meta.R                |  112 +--
 R/rco_updateCompareObject_Mismatches.R          |   42 -
 R/rco_updateCompareObject_RowMatching.R         |   62 +-
 R/vd_checkColumnNames.R                         |   52 -
 R/vd_checkEmpty.R                               |   70 +-
 R/vd_checkKeysExists.R                          |   68 +-
 R/vd_validateData.R                             |   74 +-
 R/zzz.R                                         |   48 -
 build/vignette.rds                              |binary
 inst/css/table.css                              |  106 +--
 inst/doc/dataCompareR.R                         |    4 
 inst/doc/dataCompareR.Rmd                       |  322 +++++-----
 inst/doc/dataCompareR.html                      |   64 --
 man/compareData.Rd                              |    2 
 man/executeCoercions.Rd                         |    4 
 man/locateMismatches.Rd                         |    2 
 man/prepareData.Rd                              |    4 
 man/print.dataCompareRobject.Rd                 |    4 
 man/processFlow.Rd                              |    2 
 man/rCompare.Rd                                 |    6 
 man/saveReport.Rd                               |    4 
 man/validateArguments.Rd                        |    4 
 tests/performanceTesting/colSizeTests.R         |  204 +++---
 tests/performanceTesting/keyNoKeyTests.R        |   94 +--
 tests/performanceTesting/largeDataSetCreator.R  |  268 ++++----
 tests/performanceTesting/profiling.R            |   84 +-
 tests/performanceTesting/rowSizeTests.R         |  262 ++++----
 tests/testthat.R                                |   38 -
 tests/testthat/createTitanicDatasets.R          |  214 +++----
 tests/testthat/createTwoKeyData.R               |  284 ++++-----
 tests/testthat/testCheckEmpty.R                 |   86 +-
 tests/testthat/testCheckKeysExist.R             |  136 ++--
 tests/testthat/testCheckPrintObject.R           |  394 ++++++------
 tests/testthat/testCheckSummaryObject.R         |  336 +++++------
 tests/testthat/testCheckUniqueness.R            |   74 +-
 tests/testthat/testCheckisRCompareObject.R      |   86 +-
 tests/testthat/testCoerceData.R                 |  156 ++---
 tests/testthat/testCoerceFactorsToChar.R        |  124 ++--
 tests/testthat/testCoercion.R                   |  192 +++---
 tests/testthat/testCompareDifferentDFs.R        |   74 +-
 tests/testthat/testCreateCompareObject.R        |  114 +--
 tests/testthat/testCreateMismatchData.R         |  380 ++++++------
 tests/testthat/testCreateMismatchObject.R       |  206 +++---
 tests/testthat/testEndToEndBit64.R              |  104 +--
 tests/testthat/testEndToEndDates.R              |  202 +++---
 tests/testthat/testEndToEndFourKeys.R           |  382 ++++++------
 tests/testthat/testEndToEndMismatchParam.R      |   92 +--
 tests/testthat/testEndToEndOrderedFactors.R     |   86 +-
 tests/testthat/testEndToEndTimes.R              |   90 +-
 tests/testthat/testEndToEndTitanic.R            |  728 ++++++++++++------------
 tests/testthat/testEndToEndTwoKeys.R            |  346 +++++------
 tests/testthat/testLocateMismatches.R           |  220 +++----
 tests/testthat/testMakeValidNames.R             |  358 +++++------
 tests/testthat/testMatchColumns.R               |  184 +++---
 tests/testthat/testMatchMultiIndex.R            |  190 +++---
 tests/testthat/testMatchNoIndex.R               |  150 ++--
 tests/testthat/testMatchRows.R                  |  336 +++++------
 tests/testthat/testMatchSingleIndex.R           |  104 +--
 tests/testthat/testPrintSummaryRcompareObject.R |  368 ++++++------
 tests/testthat/testRCompareStructure.R          |  122 ++--
 tests/testthat/testRounddf.R                    |  102 +--
 tests/testthat/testSaveReport.R                 |  136 ++--
 tests/testthat/testTrimCharVars.R               |   70 +-
 tests/testthat/testValidateArguments.R          |  276 ++++-----
 tests/testthat/testValidation.R                 |  162 ++---
 tests/testthat/test_outHelperFunctions.R        |   80 +-
 tests/testthat/testcreateReportText.R           |  344 +++++------
 tests/testthat/testing.Rmd                      |    6 
 tests/testthat/testing.html                     |    6 
 tests/testthat/testing.md                       |    6 
 tests/testthat/testrCompObjectQueryFunctions.R  |   58 -
 vignettes/dataCompareR.Rmd                      |  322 +++++-----
 112 files changed, 8048 insertions(+), 8090 deletions(-)

More information about dataCompareR at CRAN
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Package rpgm (with last version 1.1.0) was removed from CRAN

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

2017-10-08 1.1.0
2017-09-14 1.0.2
2017-07-08 1.0.1
2017-03-16 1.0.0
2017-02-28 0.1.3

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Package BHPMF (with last version 1.0) was removed from CRAN

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

2017-06-13 1.0

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