Tue, 11 Jun 2019

Package sjmisc updated to version 2.8.0 with previous version 2.7.9 dated 2019-03-16

Title: Data and Variable Transformation Functions
Description: Collection of miscellaneous utility functions, supporting data transformation tasks like recoding, dichotomizing or grouping variables, setting and replacing missing values. The data transformation functions also support labelled data, and all integrate seamlessly into a 'tidyverse'-workflow.
Author: Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>)
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

Diff between sjmisc versions 2.7.9 dated 2019-03-16 and 2.8.0 dated 2019-06-11

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Package pmmlTransformations updated to version 1.3.3 with previous version 1.3.2 dated 2018-08-14

Title: Transforms Input Data from a PMML Perspective
Description: Allows for data to be transformed before using it to construct models. Builds structures to allow functions in the PMML package to output transformation details in addition to the model in the resulting PMML file. The Predictive Model Markup Language (PMML) is an XML-based language which provides a way for applications to define machine learning, statistical and data mining models and to share models between PMML compliant applications. More information about the PMML industry standard and the Data Mining Group can be found at <http://www.dmg.org>. The generated PMML can be imported into any PMML consuming application, such as Zementis Predictive Analytics products, which integrate with web services, relational database systems and deploy natively on Hadoop in conjunction with Hive, Spark or Storm, as well as allow predictive analytics to be executed for IBM z Systems mainframe applications and real-time, streaming analytics platforms.
Author: Tridivesh Jena, Wen Ching Lin, Dmitriy Bolotov
Maintainer: Dmitriy Bolotov <rpmmlsupport@softwareag.com>

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Package gargle updated to version 0.2.0 with previous version 0.1.3 dated 2019-06-03

Title: Utilities for Working with Google APIs
Description: Provides utilities for working with Google APIs <https://developers.google.com/apis-explorer>. This includes functions and classes for handling common credential types and for preparing, executing, and processing HTTP requests.
Author: Jennifer Bryan [aut, cre] (<https://orcid.org/0000-0002-6983-2759>), Craig Citro [aut], Hadley Wickham [aut] (<https://orcid.org/0000-0003-4757-117X>), Google Inc [cph], RStudio [cph, fnd]
Maintainer: Jennifer Bryan <jenny@rstudio.com>

Diff between gargle versions 0.1.3 dated 2019-06-03 and 0.2.0 dated 2019-06-11

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Package servr updated to version 0.14 with previous version 0.13 dated 2019-03-04

Title: A Simple HTTP Server to Serve Static Files or Dynamic Documents
Description: Start an HTTP server in R to serve static files, or dynamic documents that can be converted to HTML files (e.g., R Markdown) under a given directory.
Author: Yihui Xie [aut, cre] (<https://orcid.org/0000-0003-0645-5666>), Carson Sievert [ctb], Jesse Anderson [ctb], Ramnath Vaidyanathan [ctb]
Maintainer: Yihui Xie <xie@yihui.name>

Diff between servr versions 0.13 dated 2019-03-04 and 0.14 dated 2019-06-11

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Package mime updated to version 0.7 with previous version 0.6 dated 2018-10-05

Title: Map Filenames to MIME Types
Description: Guesses the MIME type from a filename extension using the data derived from /etc/mime.types in UNIX-type systems.
Author: Yihui Xie [aut, cre] (<https://orcid.org/0000-0003-0645-5666>), Jeffrey Horner [ctb], Beilei Bian [ctb]
Maintainer: Yihui Xie <xie@yihui.name>

Diff between mime versions 0.6 dated 2018-10-05 and 0.7 dated 2019-06-11

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Package formatR updated to version 1.7 with previous version 1.6 dated 2019-03-05

Title: Format R Code Automatically
Description: Provides a function tidy_source() to format R source code. Spaces and indent will be added to the code automatically, and comments will be preserved under certain conditions, so that R code will be more human-readable and tidy. There is also a Shiny app as a user interface in this package (see tidy_app()).
Author: Yihui Xie [aut, cre] (<https://orcid.org/0000-0003-0645-5666>), Eugene Ha [ctb], Kohske Takahashi [ctb], Ed Lee [ctb]
Maintainer: Yihui Xie <xie@yihui.name>

Diff between formatR versions 1.6 dated 2019-03-05 and 1.7 dated 2019-06-11

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Package blogdown updated to version 0.13 with previous version 0.12 dated 2019-05-01

Title: Create Blogs and Websites with R Markdown
Description: Write blog posts and web pages in R Markdown. This package supports the static site generator 'Hugo' (<https://gohugo.io>) best, and it also supports 'Jekyll' (<http://jekyllrb.com>) and 'Hexo' (<https://hexo.io>).
Author: Yihui Xie [aut, cre] (<https://orcid.org/0000-0003-0645-5666>), Beilei Bian [ctb], Forest Fang [ctb], Garrick Aden-Buie [ctb], Hiroaki Yutani [ctb], Ian Lyttle [ctb], JJ Allaire [ctb], Kevin Ushey [ctb], Leonardo Collado-Torres [ctb], Xianying Tan [ctb], Raniere Silva [ctb], Jozef Hajnala [ctb], RStudio Inc [cph]
Maintainer: Yihui Xie <xie@yihui.name>

Diff between blogdown versions 0.12 dated 2019-05-01 and 0.13 dated 2019-06-11

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Package DT updated to version 0.7 with previous version 0.6 dated 2019-05-09

Title: A Wrapper of the JavaScript Library 'DataTables'
Description: Data objects in R can be rendered as HTML tables using the JavaScript library 'DataTables' (typically via R Markdown or Shiny). The 'DataTables' library has been included in this R package. The package name 'DT' is an abbreviation of 'DataTables'.
Author: Yihui Xie [aut, cre], Joe Cheng [aut], Xianying Tan [aut], JJ Allaire [ctb], Maximilian Girlich [ctb], Greg Freedman Ellis [ctb], Johannes Rauh [ctb], jQuery contributors [ctb, cph] (jQuery in htmlwidgets/lib), SpryMedia Limited [ctb, cph] (DataTables in htmlwidgets/lib), Brian Reavis [ctb, cph] (selectize.js in htmlwidgets/lib), Leon Gersen [ctb, cph] (noUiSlider in htmlwidgets/lib), Bartek Szopka [ctb, cph] (jquery.highlight.js in htmlwidgets/lib), RStudio Inc [cph]
Maintainer: Yihui Xie <xie@yihui.name>

Diff between DT versions 0.6 dated 2019-05-09 and 0.7 dated 2019-06-11

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Package SpatialVx updated to version 0.6-5 with previous version 0.6-4 dated 2019-01-04

Title: Spatial Forecast Verification
Description: Spatial forecast verification arose from verifying high-resolution forecasts, where coarser-resolution models generally are favored even when a human forecaster finds the higher-resolution model to be considerably better. Most newly proposed methods, which largely come from image analysis, computer vision, and similar, are available, with more on the way.
Author: Eric Gilleland <EricG@ucar.edu>
Maintainer: Eric Gilleland <EricG@ucar.edu>

Diff between SpatialVx versions 0.6-4 dated 2019-01-04 and 0.6-5 dated 2019-06-11

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New package regressoR with initial version 1.1.7
Title: Regression Data Analysis System
Package: regressoR
Type: Package
Version: 1.1.7
Authors@R: c( person("Oldemar", "Rodriguez R.", email = "oldemar.rodriguez@ucr.ac.cr", role = c("aut","cre")), person("Andres", "Navarro D.", role = c("ctb","prg")), person("Diego", "Jimenez A.", role = c("ctb","prg")))
Depends: R (>= 3.5)
Imports: shiny (>= 1.2.0), shinyAce (>= 0.3.3), shinydashboardPlus (>= 0.6.0), shinyWidgets (>= 0.4.4), shinyjs (>= 1.0), flexdashboard (>= 0.5.1.1), neuralnet (>= 1.44.2), rpart (>= 4.1-13), rattle (>= 5.2.0), xgboost (>= 0.81.0.1), colourpicker (>= 1.0), DT (>= 0.5), randomForest (>= 4.6-14), e1071 (>= 1.7-0.1), kknn (>= 1.3.1), corrplot (>= 0.84), ROCR (>= 1.0-7), glmnet (>= 2.0-16), gbm (>= 2.1.5), pls (>= 2.7-1), zip (>= 2.0.0), ggplot2 (>= 3.1.0), dplyr (>= 0.8.0.1), htmltools (>= 0.3.6)
Suggests: forcats, gridExtra, tibble, scales, scatterplot3d, psych, dummies, testthat
Description: Perform a supervised data analysis on a database through a 'shiny' graphical interface. It includes methods such as linear regression, penalized regression, k-nearest neighbors, decision trees, ada boosting, extreme gradient boosting, random forest, neural networks, deep learning and support vector machines.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
URL: http://www.promidat.com
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-05 14:58:05 UTC; promidat04
Author: Oldemar Rodriguez R. [aut, cre], Andres Navarro D. [ctb, prg], Diego Jimenez A. [ctb, prg]
Maintainer: Oldemar Rodriguez R. <oldemar.rodriguez@ucr.ac.cr>
Repository: CRAN
Date/Publication: 2019-06-11 17:20:04 UTC

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New package ForecastFramework with initial version 0.10.1
Package: ForecastFramework
Title: A Basis for Modular Model Creation
Version: 0.10.1
Authors@R: c( person("Joshua", "Kaminsky", email = "jkaminsky@jhu.edu", role = c("aut", "cre")), person("Justin", "Lessler", email = "justin@jhu.edu", role = c("aut")), person("Nicholas", "Reich", email = "nick@schoolph.umass.edu", role = c("aut")))
Maintainer: Joshua Kaminsky <jkaminsky@jhu.edu>
Description: Create modular models. Quickly prototype models whose input includes (multiple) time series data. Create pieces of model use cases separately, and swap out particular models as desired. Create modeling competitions, data processing pipelines, and re-useable models.
Depends: R6
Imports: abind,lubridate,dplyr,reshape2,magrittr,tibble
Suggests: testthat,knitr,rmarkdown,DAAG
Enhances: surveillance
Encoding: UTF-8
License: GPL-3
LazyData: true
RoxygenNote: 6.1.1
Collate: 'AbstractClasses.R' 'DataContainers.R' 'Forecasts.R' 'SimulatedIncidenceMatrix.R' 'IncidenceForecast.R' 'IncidenceMatrix.R' 'Models.R' 'SimpleForecast.R' 'MoveAheadModel.R' 'ObservationList.R'
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-06-11 16:34:13 UTC; jkaminsky
Author: Joshua Kaminsky [aut, cre], Justin Lessler [aut], Nicholas Reich [aut]
Repository: CRAN
Date/Publication: 2019-06-11 17:30:02 UTC

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Package OUwie updated to version 1.53 with previous version 1.50 dated 2016-06-18

Title: Analysis of Evolutionary Rates in an OU Framework
Description: Calculates and compares rate differences of continuous character evolution under Brownian motion and a new set of Ornstein-Uhlenbeck based Hansen models that allow the strength of selection and stochastic motion to vary across selective regimes. Beaulieu et al (2012) <doi:10.1111/j.1558-5646.2012.01619.x>.
Author: Jeremy M. Beaulieu <jbeaulieu@nimbios.org>, Brian O'Meara <bomeara@utk.edu>
Maintainer: Jeremy Beaulieu <jbeaulieu@nimbios.org>

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Package NNS updated to version 0.4.2 with previous version 0.4.1 dated 2019-06-10

Title: Nonlinear Nonparametric Statistics
Description: Nonlinear nonparametric statistics using partial moments. Partial moments are the elements of variance and asymptotically approximate the area of f(x). These robust statistics provide the basis for nonlinear analysis while retaining linear equivalences. NNS offers: Numerical integration, Numerical differentiation, Clustering, Correlation, Dependence, Causal analysis, ANOVA, Regression, Classification, Seasonality, Autoregressive modeling, Normalization and Stochastic dominance. All routines based on: Viole, F. and Nawrocki, D. (2013), Nonlinear Nonparametric Statistics: Using Partial Moments (ISBN: 1490523995).
Author: Fred Viole
Maintainer: Fred Viole <ovvo.financial.systems@gmail.com>

Diff between NNS versions 0.4.1 dated 2019-06-10 and 0.4.2 dated 2019-06-11

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Package MortCast updated to version 2.1-1 with previous version 2.0-1 dated 2019-03-19

Title: Estimation and Projection of Age-Specific Mortality Rates
Description: Age-specific mortality rates are estimated and projected using the Kannisto, Lee-Carter and related methods as described in Sevcikova et al. (2016) <doi:10.1007/978-3-319-26603-9_15>.
Author: Hana Sevcikova, Nan Li and Patrick Gerland
Maintainer: Hana Sevcikova <hanas@uw.edu>

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Package monomvn updated to version 1.9-10 with previous version 1.9-9 dated 2019-03-07

Title: Estimation for Multivariate Normal and Student-t Data with Monotone Missingness
Description: Estimation of multivariate normal and student-t data of arbitrary dimension where the pattern of missing data is monotone. Through the use of parsimonious/shrinkage regressions (plsr, pcr, lasso, ridge, etc.), where standard regressions fail, the package can handle a nearly arbitrary amount of missing data. The current version supports maximum likelihood inference and a full Bayesian approach employing scale-mixtures for Gibbs sampling. Monotone data augmentation extends this Bayesian approach to arbitrary missingness patterns. A fully functional standalone interface to the Bayesian lasso (from Park & Casella), Normal-Gamma (from Griffin & Brown), Horseshoe (from Carvalho, Polson, & Scott), and ridge regression with model selection via Reversible Jump, and student-t errors (from Geweke) is also provided.
Author: Robert B. Gramacy <rbg@vt.edu>
Maintainer: Robert B. Gramacy <rbg@vt.edu>

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Package FHDI updated to version 1.3.2 with previous version 1.2.5 dated 2018-04-26

Title: Fractional Hot Deck and Fully Efficient Fractional Imputation
Description: Impute general multivariate missing data with the fractional hot deck imputation based on Jaekwang Kim (2011) <doi:10.1093/biomet/asq073>.
Author: Jongho Im [aut], Inho Cho [aut, cre], Jaekwang Kim [aut]
Maintainer: Inho Cho <icho@iastate.edu>

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Package EHRtemporalVariability updated to version 1.0.1 with previous version 1.0 dated 2019-03-14

Title: Delineating Reference Changes in Electronic Health Records over Time
Description: The 'EHRtemporalVariability' package contains functions to delineate reference changes over time in Electronic Health Records through the projection and visualization of dissimilarities among data temporal batches. This is done through the estimation of data statistical distributions over time and their projection in non-parametric statistical manifolds uncovering the patterns of the data latent temporal variability. Results can be explored through visual analytics formats such as Data Temporal Heatmaps and Information Geometric Temporal (IGT) plots. An additional 'EHRtemporalVariability' Shiny app can be used to load and explore the package results and even to allow the use of these functions to those users non-experienced in R coding.
Author: Carlos Sáez [aut, cre], Alba Gutiérrez-Sacristán [aut], Isaac Kohane [aut], Juan M García-Gómez [aut], Paul Avillach [aut], Biomedical Data Science Lab, Universitat Politècnica de València (Spain) [cph], Department of Biomedical Informatics, Harvard Medical School [cph]
Maintainer: Carlos Sáez <carsaesi@upv.es>

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Package bayesTFR updated to version 6.3-1 with previous version 6.3-0 dated 2019-05-27

Title: Bayesian Fertility Projection
Description: Making probabilistic projections of total fertility rate for all countries of the world, using a Bayesian hierarchical model.
Author: Hana Sevcikova (hanas@uw.edu), Leontine Alkema (alkema@nus.edu.sg), Adrian Raftery (raftery@uw.edu), Bailey Fosdick (bfosdick@uw.edu), Patrick Gerland (gerland@un.org)
Maintainer: Hana Sevcikova <hanas@uw.edu>

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Package padr updated to version 0.5.0 with previous version 0.4.2 dated 2019-04-13

Title: Quickly Get Datetime Data Ready for Analysis
Description: Transforms datetime data into a format ready for analysis. It offers two core functionalities; aggregating data to a higher level interval (thicken) and imputing records where observations were absent (pad).
Author: Edwin Thoen
Maintainer: Edwin Thoen <edwinthoen@gmail.com>

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Package BayesianFROC updated to version 0.1.3 with previous version 0.1.2 dated 2019-05-28

Title: FROC Analysis by Bayesian Approaches
Description: Provides new methods for the so-called Free-response Receiver Operating Characteristic (FROC) analysis. The ultimate aim of FROC analysis is to compare observer performances, which means comparing characteristics, such as area under the curve (AUC) or figure of merit (FOM). In this package, we only use the notion of AUC for modality comparison, where by "modality", we mean imaging methods such as Magnetic Resonance Imaging (MRI), Computed Tomography (CT), Positron Emission Tomography (PET), ..., etc. So there is a problem that which imaging method is better to detect lesions from shadows in radiographs. To solve modality comparison issues, this package provides new methods using hierarchical Bayesian models proposed by the author of this package. Using this package, one can obtain at least one conclusion that which imaging methods are better for finding lesions in radiographs with the case of your data. Fitting FROC statistical models is sometimes not so good, it can easily confirm by drawing FROC curves and comparing these curves and the points constructed by False Positive fractions (FPFs) and True Positive Fractions (TPFs), we can validate the goodness of fit intuitively. Such validation is also implemented by the Chi square goodness of fit statistics in the Bayesian context which means that the parameter is not deterministic, thus by integrating it with the posterior predictive measure, we get a desired value. To compare modalities (imaging methods: MRI, CT, PET, ... , etc), we evaluate AUCs for each modality. FROC is developed by Dev Chakraborty, his FROC model in his 1989 paper relies on the maximal likelihood methodology. The author modified and provided the alternative Bayesian FROC model. Strictly speaking, his model does not coincide with models in this package. In FROC context, we means by multiple reader and multiple case (MRMC) the case of the number of reader or modality is two or more. The MRMC data is available for functions of this package. I hope that medical researchers use not only the frequentist method but also alternative Bayesian methods. In medical research, many problems are considered under only frequentist methods, such as the notion of p-values. But p-value is sometimes misunderstood. Bayesian methods provide very simple, direct, intuitive answer for research questions. Combining frequentist methods with Bayesian methods, we can obtain more reliable answer for research questions. Please execute the following R scripts from the R (R studio) console, demo(demo_MRMC, package = "BayesianFROC"); demo(demo_srsc, package = "BayesianFROC"); demo(demo_stan, package = "BayesianFROC"); demo(demo_drawcurves_srsc, package = "BayesianFROC"); demo_Bayesian_FROC(); demo_Bayesian_FROC_without_pause(). References: Dev Chakraborty (1989) <doi:10.1118/1.596358> Maximum likelihood analysis of free - response receiver operating characteristic (FROC) data. Pre-print: Issei Tsunoda; Bayesian Models for free-response receiver operating characteristic analysis. See the vignettes for more details.
Author: Issei Tsunoda [aut, cre]
Maintainer: Issei Tsunoda <tsunoda.issei1111@gmail.com>

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 BayesianFROC-0.1.3/BayesianFROC/NAMESPACE                                                                     |    6 
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Package lineqGPR updated to version 0.0.4 with previous version 0.0.3 dated 2018-09-30

Title: Gaussian Process Regression Models with Linear Inequality Constraints
Description: Gaussian processes regression models with linear inequality constraints (Lopez-Lopera et al., 2018) <doi:10.1137/17M1153157>.
Author: Andres Felipe LOPEZ-LOPERA
Maintainer: Andres Felipe LOPEZ-LOPERA <andres-felipe.lopez@emse.fr>

Diff between lineqGPR versions 0.0.3 dated 2018-09-30 and 0.0.4 dated 2019-06-11

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Package aweek updated to version 1.0.0 with previous version 0.2.2 dated 2019-04-26

Title: Convert Dates to Arbitrary Week Definitions
Description: Which day a week starts depends heavily on the either the local or professional context. This package is designed to be a lightweight solution to easily switching between week-based date definitions.
Author: Zhian N. Kamvar [aut, cre]
Maintainer: Zhian N. Kamvar <zkamvar@gmail.com>

Diff between aweek versions 0.2.2 dated 2019-04-26 and 1.0.0 dated 2019-06-11

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Package RPANDA updated to version 1.6 with previous version 1.5 dated 2019-01-30

Title: Phylogenetic ANalyses of DiversificAtion
Description: Implements macroevolutionary analyses on phylogenetic trees. See Morlon et al. (2010) <DOI:10.1371/journal.pbio.1000493>, Morlon et al. (2011) <DOI:10.1073/pnas.1102543108>, Condamine et al. (2013) <DOI:10.1111/ele.12062>, Morlon et al. (2014) <DOI:10.1111/ele.12251>, Manceau et al. (2015) <DOI:10.1111/ele.12415>, Lewitus & Morlon (2016) <DOI:10.1093/sysbio/syv116>, Drury et al. (2016) <DOI:10.1093/sysbio/syw020>, Manceau et al. (2016) <DOI:10.1093/sysbio/syw115>, Morlon et al. (2016) <DOI:10.1111/2041-210X.12526>, Clavel & Morlon (2017) <DOI:10.1073/pnas.1606868114>, Drury et al. (2017) <DOI:10.1093/sysbio/syx079>, Lewitus & Morlon (2017) <DOI:10.1093/sysbio/syx095>, Drury et al. (2018) <DOI:10.1371/journal.pbio.2003563>, Clavel et al. (2019) <DOI:10.1093/sysbio/syy045> and Maliet et al. (2019) <DOI:10.1038/s41559-019-0908-0>.
Author: Hélène Morlon [aut, cre, cph], Eric Lewitus [aut, cph], Fabien Condamine [aut, cph], Marc Manceau [aut, cph], Julien Clavel [aut, cph], Jonathan Drury [aut, cph], Olivier Billaud [aut, cph], Odile Maliet [aut, cph]
Maintainer: Hélène Morlon <morlon@biologie.ens.fr>

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New package leafR with initial version 0.1.4
Package: leafR
Type: Package
Title: Calculates the Leaf Area Index (LAD) and Other Related Functions
Version: 0.1.4
Authors@R: c( person(given="Danilo Roberti Alves de", family="Almeida", email="daniloflorestas@gmail.com", role=c("aut", "cre"), comment=c(ORCID="https://orcid.org/0000-0002-8747-0085")), person(given="Scott Christopher", family="Stark", email="scottcstark@gmail.com", role=c("aut"), comment=c(ORCID="https://orcid.org/0000-0002-1305-1793")), person(given="Carlos Alberto", family="Silva", email="carlos_engflorestal@outlook.com", role=c("aut"), comment=c(ORCID="https://orcid.org/0000-0002-7844-3560")), person(given="Caio", family="Hamamura", email="caiohamamura@gmail.com", role=c("aut"), comment=c(ORCID="https://orcid.org/0000-0001-6149-5885")) )
Description: A set of functions for analyzing the structure of forests based on the leaf area density (LAD) and leaf area index (LAI) measures calculated from Airborne Laser Scanning (ALS), i.e., scanning lidar (Light Detection and Ranging) data. The methodology is discussed and described in Almeida et al. (2019) <doi:10.3390/rs11010092> and Stark et al. (2012) <doi:10.1111/j.1461-0248.2012.01864.x>.
Imports: lidR, sp, data.table, raster, lazyeval
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-09 02:46:16 UTC; caioh
Author: Danilo Roberti Alves de Almeida [aut, cre] (<https://orcid.org/0000-0002-8747-0085>), Scott Christopher Stark [aut] (<https://orcid.org/0000-0002-1305-1793>), Carlos Alberto Silva [aut] (<https://orcid.org/0000-0002-7844-3560>), Caio Hamamura [aut] (<https://orcid.org/0000-0001-6149-5885>)
Maintainer: Danilo Roberti Alves de Almeida <daniloflorestas@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-11 10:40:03 UTC

More information about leafR at CRAN
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Package HybridFS updated to version 0.1.3 with previous version 0.1.2 dated 2017-10-11

Title: A Hybrid Filter-Wrapper Feature Selection Method
Description: A hybrid method of feature selection which combines both filter and wrapper methods. The first level involves feature reduction based on some of the important filter methods while the second level involves feature subset selection as in a wrapper method. Comparative analysis with the existing feature selection packages shows this package results in higher classification accuracy, reduced processing time and improved data handling capacity.
Author: Yamini Pandari [aut, cre], Prashanth Thangavel [aut], Hemanth Senthamaraikannan [aut], Sivaranjani Jagadeeswaran [aut]
Maintainer: Yamini Pandari <yamini.pandari@gmail.com>

Diff between HybridFS versions 0.1.2 dated 2017-10-11 and 0.1.3 dated 2019-06-11

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New package bvartools with initial version 0.0.1
Package: bvartools
Title: Bayesian Inference of Vector Autoregressive Models
Version: 0.0.1
Date: 2019-06-09
Authors@R: person("Franz X.", "Mohr", email = "bvartools@outlook.com", role = c("aut","cre"))
Description: Assists in the set-up of algorithms for Bayesian inference of vector autoregressive (VAR) models. Functions for posterior simulation, forecasting, impulse response analysis and forecast error variance decomposition are largely based on the introductory texts of Koop and Korobilis (2010) <doi:10.1561/0800000013> and Luetkepohl (2007, ISBN: 9783540262398).
License: GPL (>= 2)
Depends: R (>= 3.3.0)
Imports: coda, graphics, Rcpp (>= 0.12.14), stats
LinkingTo: Rcpp, RcppArmadillo
Encoding: UTF-8
RoxygenNote: 6.1.1
URL: https://github.com/franzmohr/bvartools
BugReports: https://github.com/franzmohr/bvartools/issues
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-06-09 08:44:14 UTC; franz
Author: Franz X. Mohr [aut, cre]
Maintainer: Franz X. Mohr <bvartools@outlook.com>
Repository: CRAN
Date/Publication: 2019-06-11 10:10:19 UTC

More information about bvartools at CRAN
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Package AdhereR updated to version 0.5 with previous version 0.4.1 dated 2019-02-11

Title: Adherence to Medications
Description: Computation of adherence to medications from Electronic Health care Data and visualization of individual medication histories and adherence patterns. The package implements a set of S3 classes and functions consistent with current adherence guidelines and definitions. It allows the computation of different measures of adherence (as defined in the literature, but also several original ones), their publication-quality plotting, the estimation of event duration and time to initiation, the interactive exploration of patient medication history and the real-time estimation of adherence given various parameter settings. It scales from very small datasets stored in flat CSV files to very large databases and from single-thread processing on mid-range consumer laptops to parallel processing on large heterogeneous computing clusters. It exposes a standardized interface allowing it to be used from other programming languages and platforms, such as Python.
Author: Dan Dediu [aut, cre], Alexandra Dima [aut], Samuel Allemann [aut]
Maintainer: Dan Dediu <ddediu@gmail.com>

Diff between AdhereR versions 0.4.1 dated 2019-02-11 and 0.5 dated 2019-06-11

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New package sass with initial version 0.1.1
Type: Package
Package: sass
Version: 0.1.1
Title: Syntactically Awesome Style Sheets (Sass) for R
Description: An 'SCSS' compiler, powered by the 'libSass' library. With this, R developers can use variables, inheritance, and functions to generate dynamic style sheets. The package uses the Sass CSS extension language, which is stable, powerful, and CSS compatible.
Authors@R: c( person("Richard", "Iannone", , "rich@rstudio.com", c("aut", "cre"), comment = c(ORCID = "0000-0003-3925-190X")), person("Timothy", "Mastny", , "tim.mastny@gmail.com", "aut"), person("Barret", "Schloerke", , "barret@rstudio.com", "aut", comment = c(ORCID = "0000-0001-9986-114X")), person("Joe", "Cheng", , "joe@rstudio.com", c("aut", "rev")), person(family = "RStudio", role = c("cph", "fnd")), person(family = "Sass Open Source Foundation", role = c("ctb", "cph"), comment = "LibSass library"), person("Hampton", "Catlin", role = c("ctb", "cph"), comment = "LibSass library"), person("Nathan", "Weizenbaum", role = c("ctb", "cph"), comment = "LibSass library"), person("Chris", "Eppstein", role = c("ctb", "cph"), comment = "LibSass library") )
License: MIT + file LICENSE
URL: https://github.com/rstudio/sass
BugReports: https://github.com/rstudio/sass/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
SystemRequirements: GNU make
Imports: digest
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-06-09 03:38:17 UTC; rich
Author: Richard Iannone [aut, cre] (<https://orcid.org/0000-0003-3925-190X>), Timothy Mastny [aut], Barret Schloerke [aut] (<https://orcid.org/0000-0001-9986-114X>), Joe Cheng [aut, rev], RStudio [cph, fnd], Sass Open Source Foundation [ctb, cph] (LibSass library), Hampton Catlin [ctb, cph] (LibSass library), Nathan Weizenbaum [ctb, cph] (LibSass library), Chris Eppstein [ctb, cph] (LibSass library)
Maintainer: Richard Iannone <rich@rstudio.com>
Repository: CRAN
Date/Publication: 2019-06-11 10:00:03 UTC

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New package pcFactorStan with initial version 0.11
Package: pcFactorStan
Title: Stan Models for the Pairwise Comparison Factor Model
Version: 0.11
Authors@R: c(person(given = c("Joshua", "N."), family = "Pritikin", role = c("aut", "cre"), email = "jpritikin@pobox.com", comment = c(ORCID = "0000-0002-9862-5484")), person(given = c("Daniel C."), family = "Furr", role="ctb", email = "danielcfurr@berkeley.edu"), person("Trustees of Columbia University", role="cph"))
Description: Provides convenience functions and pre-programmed Stan models related to the pairwise comparison factor model. Its purpose is to make fitting pairwise comparison data using Stan easy.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.3.0), StanHeaders (>= 2.18.0), BH (>= 1.66.0), rstan (>= 2.18.1)
Imports: rstan (>= 2.18), reshape2, mvtnorm, igraph
Depends: R (>= 3.4), methods, Rcpp (>= 0.12.0)
Suggests: knitr, rmarkdown, testthat, shiny, ggplot2, covr, qgraph
SystemRequirements: GNU make
VignetteBuilder: knitr
NeedsCompilation: yes
URL: https://github.com/jpritikin/pcFactorStan
BugReports: https://github.com/jpritikin/pcFactorStan/issues
RoxygenNote: 6.1.1
Packaged: 2019-06-08 12:00:51 UTC; joshua
Author: Joshua N. Pritikin [aut, cre] (<https://orcid.org/0000-0002-9862-5484>), Daniel C. Furr [ctb], Trustees of Columbia University [cph]
Maintainer: Joshua N. Pritikin <jpritikin@pobox.com>
Repository: CRAN
Date/Publication: 2019-06-11 09:40:03 UTC

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New package PakPMICS2018mn with initial version 0.1.0
Package: PakPMICS2018mn
Type: Package
Title: Multiple Indicator Cluster Survey (MICS) 2017-18 Men Questionnaire Data for Punjab, Pakistan
Version: 0.1.0
Authors@R: c( person(c("Muhammad", "Yaseen"), email = "myaseen208@gmail.com", role = c("aut", "cre")) , person(c("Muhammad", "Usman"), email = "usmann75@hotmail.com", role = c("ctb")) )
Author: Muhammad Yaseen [aut, cre], Muhammad Usman [ctb]
Maintainer: Muhammad Yaseen <myaseen208@gmail.com>
Description: Provides data set and function for exploration of Multiple Indicator Cluster Survey (MICS) 2017-18 Men questionnaire data for Punjab, Pakistan. The results of the present survey are critically important for the purposes of Sustainable Development Goals (SDGs) monitoring, as the survey produces information on 32 global Sustainable Development Goals (SDGs) indicators. The data was collected from 53,840 households selected at the second stage with systematic random sampling out of a sample of 2,692 clusters selected using probability proportional to size sampling. Six questionnaires were used in the survey: (1) a household questionnaire to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; (2) a water quality testing questionnaire administered in three households in each cluster of the sample; (3) a questionnaire for individual women administered in each household to all women age 15-49 years; (4) a questionnaire for individual men administered in every second household to all men age 15-49 years; (5) an under-5 questionnaire, administered to mothers (or caretakers) of all children under 5 living in the household; and (6) a questionnaire for children age 5-17 years, administered to the mother (or caretaker) of one randomly selected child age 5-17 years living in the household (<http://www.mics.unicef.org/surveys>).
Depends: R (>= 3.5.0)
Imports: tibble
License: GPL-2
URL: https://github.com/myaseen208/PakPMICS2018mn, https://myaseen208.github.io/PakPMICS2018mn/
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Note: Department of Mathematics and Statistics, University of Agriculture Faisalabad, Faisalabad-Pakistan.
Suggests: testthat, R.rsp
VignetteBuilder: R.rsp
NeedsCompilation: no
Packaged: 2019-06-08 13:10:59 UTC; myaseen
Repository: CRAN
Date/Publication: 2019-06-11 09:40:09 UTC

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Package POD updated to version 1.1.4 with previous version 1.1.0 dated 2019-04-15

Title: Probability of Detection for Qualitative PCR Methods
Description: This tool computes the probability of detection (POD) curve and the limit of detection (LOD), i.e. the number of copies of the target DNA sequence required to ensure a 95 % probability of detection (LOD95). Other quantiles of the LOD can be specified. This is a reimplementation of the mathematical-statistical modelling of the validation of qualitative polymerase chain reaction (PCR) methods within a single laboratory as provided by the commercial tool 'PROLab' <http://quodata.de/>. The modelling itself has been described by Uhlig et al. (2015) <doi:10.1007/s00769-015-1112-9>.
Author: Markus Boenn (State Office for Consumer Protection Saxony-Anhalt, Germany)
Maintainer: Markus Boenn <markus.boenn.sf@gmail.com>

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Package MetaSubtract updated to version 1.50 with previous version 1.43 dated 2018-07-10

Title: Subtracting Summary Statistics of One or more Cohorts from Meta-GWAS Results
Description: If results from a meta-GWAS are used for validation in one of the cohorts that was included in the meta-analysis, this will yield biased (i.e. too optimistic) results. The validation cohort needs to be independent from the meta-Genome-Wide-Association-Study (meta-GWAS) results. 'MetaSubtract' will subtract the results of the respective cohort from the meta-GWAS results analytically without having to redo the meta-GWAS analysis using the leave-one-out methodology. It can handle different meta-analyses methods and takes into account if single or double genomic control correction was applied to the original meta-analysis. It can also handle different meta-analysis methods. It can be used for whole GWAS, but also for a limited set of genetic markers.
Author: Ilja M. Nolte
Maintainer: Ilja M. Nolte <i.m.nolte@umcg.nl>

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Package robsurvey updated to version 0.1.1 with previous version 0.1.0 dated 2019-05-29

Title: Robust Survey Statistics Estimation
Description: Multiple functions to compute robust survey statistics. The package supports the computations of robust means, totals, and ratios. Available methods are Huber M-estimators, trimming, and winsorization. The package 'robsurvey' complements the 'survey' package. The package additionally includes a weighted version of the resistant line function of base R (line()), as well as two median based simple regression estimators. The methods are described in Hulliger (1995) <https://www150.statcan.gc.ca/n1/en/catalogue/12-001-X199500114407/>.
Author: Beat Hulliger [aut], Tobias Schoch [aut], Martin Sterchi [cre]
Maintainer: Martin Sterchi <martin.sterchi@fhnw.ch>

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Package EstimationTools updated to version 1.2.0 with previous version 1.1.0 dated 2019-06-06

Title: Maximum Likelihood Estimation for Probability Functions from Data Sets
Description: A routine for parameter estimation for any probability density or mass function implemented in R via maximum likelihood (ML) given a data set. This routine is a wrapper function specifically developed for ML estimation. There are included optimization procedures such as 'nlminb' and 'optim' from base package, and 'DEoptim' Mullen (2011) <doi: 10.18637/jss.v040.i06>. Standard errors are estimated with 'numDeriv' Gilbert (2011) <http://CRAN.R-project.org/package=numDeriv> or the option 'Hessian = TRUE' of 'optim' function.
Author: Jaime Mosquera [aut, cre] (<https://orcid.org/0000-0002-1684-4756>), Freddy Hernandez [aut] (<https://orcid.org/0000-0001-7459-3329>)
Maintainer: Jaime Mosquera <jmosquerag@unal.edu.co>

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Package cglasso updated to version 1.1.1 with previous version 1.1.0 dated 2018-09-19

Title: L1-Penalized Censored Gaussian Graphical Models
Description: The l1-penalized censored Gaussian graphical model is an extension of the graphical lasso estimator developed to handle datasets with censored observations. An EM-like algorithm is implemented to estimate the parameters of the censored Gaussian graphical models.
Author: Luigi Augugliaro
Maintainer: Luigi Augugliaro <luigi.augugliaro@unipa.it>

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Package tinyProject updated to version 0.6 with previous version 0.5 dated 2017-09-27

Title: A Lightweight Template for Data Analysis Projects
Description: Creates useful files and folders for data analysis projects and provides functions to manage data, scripts and output files. Also provides a project template for 'Rstudio'.
Author: Francois Guillem
Maintainer: Francois Guillem <guillem.francois@gmail.com>

Diff between tinyProject versions 0.5 dated 2017-09-27 and 0.6 dated 2019-06-11

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Package showtext updated to version 0.7 with previous version 0.6 dated 2019-01-10

Title: Using Fonts More Easily in R Graphs
Description: Making it easy to use various types of fonts ('TrueType', 'OpenType', Type 1, web fonts, etc.) in R graphs, and supporting most output formats of R graphics including PNG, PDF and SVG. Text glyphs will be converted into polygons or raster images, hence after the plot has been created, it no longer relies on the font files. No external software such as 'Ghostscript' is needed to use this package.
Author: Yixuan Qiu and authors/contributors of the included software. See file AUTHORS for details.
Maintainer: Yixuan Qiu <yixuan.qiu@cos.name>

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Package RSpectra updated to version 0.15-0 with previous version 0.14-0 dated 2019-04-04

Title: Solvers for Large-Scale Eigenvalue and SVD Problems
Description: R interface to the 'Spectra' library <https://spectralib.org/> for large-scale eigenvalue and SVD problems. It is typically used to compute a few eigenvalues/vectors of an n by n matrix, e.g., the k largest eigenvalues, which is usually more efficient than eigen() if k << n. This package provides the 'eigs()' function that does the similar job as in 'Matlab', 'Octave', 'Python SciPy' and 'Julia'. It also provides the 'svds()' function to calculate the largest k singular values and corresponding singular vectors of a real matrix. The matrix to be computed on can be dense, sparse, or in the form of an operator defined by the user.
Author: Yixuan Qiu [aut, cre], Jiali Mei [aut] (Function interface of matrix operation), Gael Guennebaud [ctb] (Eigenvalue solvers from the 'Eigen' library), Jitse Niesen [ctb] (Eigenvalue solvers from the 'Eigen' library)
Maintainer: Yixuan Qiu <yixuan.qiu@cos.name>

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Package RcppNumerical updated to version 0.3-3 with previous version 0.3-2 dated 2018-02-18

Title: 'Rcpp' Integration for Numerical Computing Libraries
Description: A collection of open source libraries for numerical computing (numerical integration, optimization, etc.) and their integration with 'Rcpp'.
Author: Yixuan Qiu [aut, cre], Sreekumar Balan [aut] (Numerical integration library), Matt Beall [aut] (Numerical integration library), Mark Sauder [aut] (Numerical integration library), Naoaki Okazaki [aut] (The libLBFGS library), Thomas Hahn [aut] (The Cuba library)
Maintainer: Yixuan Qiu <yixuan.qiu@cos.name>

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Package DAIME updated to version 1.1 with previous version 1.0 dated 2019-05-16

Title: Effects of Changing Deposition Rates
Description: Reverse and model the effects of changing deposition rates on geological data and rates. Based on Hohmann (2018) <doi:10.13140/RG.2.2.23372.51841> .
Author: Niklas Hohmann
Maintainer: Niklas Hohmann <Niklas.Hohmann@fau.de>

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Package cholera updated to version 0.6.5 with previous version 0.6.0 dated 2019-03-08

Title: Amend, Augment and Aid Analysis of John Snow's Cholera Map
Description: Amends errors, augments data and aids analysis of John Snow's map of the 1854 London cholera outbreak.
Author: Peter Li [aut, cre]
Maintainer: Peter Li <lindbrook@gmail.com>

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 cholera-0.6.5/cholera/README.md                                       |  377 +++++-----
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 110 files changed, 1186 insertions(+), 1090 deletions(-)

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