Sat, 17 Jun 2017

Package snowFT updated to version 1.6-0 with previous version 1.5-0 dated 2017-05-26

Title: Fault Tolerant Simple Network of Workstations
Description: Extension of the snow package supporting fault tolerant and reproducible applications, as well as supporting easy-to-use parallel programming - only one function is needed. Dynamic cluster size is also available.
Author: Hana Sevcikova, A. J. Rossini
Maintainer: Hana Sevcikova <hanas@uw.edu>

Diff between snowFT versions 1.5-0 dated 2017-05-26 and 1.6-0 dated 2017-06-17

 ChangeLog               |    4 ++
 DESCRIPTION             |   14 +++----
 MD5                     |   24 ++++++------
 NAMESPACE               |    1 
 R/mpi.R                 |    5 +-
 R/snowFT.R              |   95 +++++++++++++++++++++++++++++++-----------------
 R/sock.R                |    5 +-
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 man/snowFT-package.Rd   |   27 +++++++------
 man/snowFT-rand.Rd      |   33 +++++++++++-----
 man/snowFT-startstop.Rd |   15 +++++--
 tests/run_tests.R       |    3 +
 tests/test_functions.R  |   13 ++++++
 13 files changed, 199 insertions(+), 118 deletions(-)

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Package forecast updated to version 8.1 with previous version 8.0 dated 2017-02-23

Title: Forecasting Functions for Time Series and Linear Models
Description: Methods and tools for displaying and analysing univariate time series forecasts including exponential smoothing via state space models and automatic ARIMA modelling.
Author: Rob Hyndman [aut, cre, cph], Mitchell O'Hara-Wild [aut], Christoph Bergmeir [aut], Slava Razbash [aut], Earo Wang [aut]
Maintainer: Rob Hyndman <Rob.Hyndman@monash.edu>

Diff between forecast versions 8.0 dated 2017-02-23 and 8.1 dated 2017-06-17

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 164 files changed, 8232 insertions(+), 2221 deletions(-)

More information about forecast at CRAN
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New package fingertipsR with initial version 0.1.0
Package: fingertipsR
Type: Package
Version: 0.1.0
Title: Fingertips Data for Public Health
Description: Fingertips (<http://fingertips.phe.org.uk/>) contains data for many indicators of public health in England. The underlying data is now more easily accessible by making use of the API.
Authors@R: c(person("Sebastian", "Fox", , "sebastian.fox@phe.gov.uk", c("aut", "cre")))
URL: https://fingertips.phe.org.uk
BugReports: https://github.com/PublicHealthEngland/fingertipsR/issues
Imports: dplyr, jsonlite, tidyjson
Suggests: knitr, rmarkdown, testthat, ggplot2, pander, DT, curl
VignetteBuilder: knitr
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-06-17 21:42:12 UTC; Seb
Author: Sebastian Fox [aut, cre]
Maintainer: Sebastian Fox <sebastian.fox@phe.gov.uk>
Repository: CRAN
Date/Publication: 2017-06-17 23:57:11 UTC

More information about fingertipsR at CRAN
Permanent link

Package bindrcpp updated to version 0.2 with previous version 0.1 dated 2016-12-11

Title: An 'Rcpp' Interface to Active Bindings
Description: Provides an easy way to fill an environment with active bindings that call a C++ function.
Author: Kirill Müller [aut, cre], RStudio [cph]
Maintainer: Kirill Müller <krlmlr+r@mailbox.org>

Diff between bindrcpp versions 0.1 dated 2016-12-11 and 0.2 dated 2017-06-17

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More information about bindrcpp at CRAN
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Package TraMineR updated to version 2.0-6 with previous version 2.0-5 dated 2017-05-15

Title: Trajectory Miner: a Toolbox for Exploring and Rendering Sequences
Description: Toolbox for the manipulation, description and rendering of sequences, and more generally the mining of sequence data in the field of social sciences. Although the toolbox is primarily intended for analyzing state or event sequences that describe life courses such as family formation histories or professional careers, its features also apply to many other kinds of categorical sequence data. It accepts many different sequence representations as input and provides tools for converting sequences from one format to another. It offers several functions for describing and rendering sequences, for computing distances between sequences with different metrics (among which optimal matching), original dissimilarity-based analysis tools, and simple functions for extracting the most frequent subsequences and identifying the most discriminating ones among them. A user's guide can be found on the TraMineR web page.
Author: Alexis Gabadinho [aut, cph], Matthias Studer [aut, cph], Nicolas Müller [aut], Reto Bürgin [aut], Pierre-Alexandre Fonta [aut], Gilbert Ritschard [aut, cre, cph]
Maintainer: Gilbert Ritschard <gilbert.ritschard@unige.ch>

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More information about TraMineR at CRAN
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Package Rcrawler updated to version 0.1.1 with previous version 0.1 dated 2017-06-15

Title: Web Crawler and Scraper
Description: Performs parallel web crawling and web scraping. It is designed to crawl, parse and store web pages to produce data that can be directly used for analysis application. For details see Khalil and Fakir (2017) <DOI:10.1016/j.softx.2017.04.004>.
Author: Salim Khalil [aut, cre]
Maintainer: Salim Khalil <khalilsalim1@gmail.com>

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Package TAM updated to version 2.2-49 with previous version 2.1-43 dated 2017-05-11

Title: Test Analysis Modules
Description: Includes marginal maximum likelihood estimation of uni- and multidimensional item response models (Rasch, 2PL, 3PL, Generalized Partial Credit, Multi Facets, Nominal Item Response, Structured Latent Class Analysis, Mixture Distribution IRT Models, Located Latent Class Models) and joint maximum likelihood estimation for models from the Rasch family. Latent regression models and plausible value imputation are also supported.
Author: Alexander Robitzsch [aut, cre], Thomas Kiefer [aut], Margaret Wu [aut]
Maintainer: Alexander Robitzsch <robitzsch@ipn.uni-kiel.de>

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Package miceadds updated to version 2.5-9 with previous version 2.4-12 dated 2017-04-19

Title: Some Additional Multiple Imputation Functions, Especially for 'mice'
Description: Contains some auxiliary functions for multiple imputation which complements existing functionality in R. In addition to some utility functions, main features include plausible value imputation, multilevel imputation functions, imputation using partial least squares (PLS) for high dimensional predictors, nested multiple imputation.
Author: Alexander Robitzsch [aut, cre], Simon Grund [aut], Thorsten Henke [aut]
Maintainer: Alexander Robitzsch <robitzsch@ipn.uni-kiel.de>

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Package funModeling updated to version 1.6.4 with previous version 1.6.3 dated 2017-06-03

Title: Exploratory Data Analysis and Data Preparation Tool-Box Book
Description: Around 10% of almost any predictive modeling project is spent in predictive modeling, 'funModeling' and the book Data Science Live Book (<http://livebook.datascienceheroes.com/>) are intended to cover remaining 90%: data preparation, profiling, selecting best variables 'dataViz', assessing model performance and other functions.
Author: Pablo Casas
Maintainer: Pablo Casas <pcasas.biz@gmail.com>

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Package CDM updated to version 5.6-16 with previous version 5.5-21 dated 2017-04-11

Title: Cognitive Diagnosis Modeling
Description: Functions for cognitive diagnosis modeling and multidimensional item response modeling for dichotomous and polytomous data. This package enables the estimation of the DINA and DINO model, the multiple group (polytomous) GDINA model, the multiple choice DINA model, the general diagnostic model (GDM), the multidimensional linear compensatory item response model and the structured latent class model (SLCA).
Author: Alexander Robitzsch [aut, cre], Thomas Kiefer [aut], Ann Cathrice George [aut], Ali Uenlue [aut]
Maintainer: Alexander Robitzsch <robitzsch@ipn.uni-kiel.de>

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New package womblR with initial version 1.0.0
Package: womblR
Type: Package
Title: Spatiotemporal Boundary Detection Model for Areal Unit Data
Version: 1.0.0
Description: Implements a spatiotemporal boundary detection model with a dissimilarity metric for areal data with inference in a Bayesian setting using Markov chain Monte Carlo (MCMC). The response variable can be modeled as Gaussian (no nugget), probit or Tobit link and spatial correlation is introduced at each time point through a conditional autoregressive (CAR) prior. Temporal correlation is introduced through a hierarchical structure and can be specified as exponential or first-order autoregressive. Full details of the package can be found in the accompanying vignette.
Date: 2017-06-15
Authors@R: person("Samuel I.", "Berchuck", email = "berchuck@ad.unc.edu", role = c("aut", "cre"))
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 5.0.1
NeedsCompilation: yes
Depends: R (>= 3.0.2)
Imports: graphics, grDevices, mvtnorm (>= 1.0-0), Rcpp (>= 0.12.9), stats, utils
Suggests: coda, classInt, knitr, rmarkdown
LinkingTo: Rcpp, RcppArmadillo (>= 0.7.500.0.0)
VignetteBuilder: knitr
Packaged: 2017-06-16 20:44:23 UTC; Sam
Author: Samuel I. Berchuck [aut, cre]
Maintainer: Samuel I. Berchuck <berchuck@ad.unc.edu>
Repository: CRAN
Date/Publication: 2017-06-17 14:55:19 UTC

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Package TeXCheckR updated to version 0.2.0 with previous version 0.1.1 dated 2017-04-09

Title: Parses LaTeX Documents for Errors
Description: Checks LaTeX documents and .bib files for typing errors, such as spelling errors, incorrect quotation marks. Also provides useful functions for parsing and linting bibliography files.
Author: Hugh Parsonage
Maintainer: Hugh Parsonage <hugh.parsonage@gmail.com>

Diff between TeXCheckR versions 0.1.1 dated 2017-04-09 and 0.2.0 dated 2017-06-17

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New package secret with initial version 1.0.0
Package: secret
Title: Share Sensitive Information in R Packages
Version: 1.0.0
Authors@R: c(person("Gábor", "Csárdi", role=c("aut", "cre"), email="csardi.gabor@gmail.com"), person("Andrie", "de Vries", role=c("aut"), email="apdevries@gmail.com"))
Description: Allow sharing sensitive information, for example passwords, 'API' keys, etc., in R packages, using public key cryptography.
License: MIT + file LICENSE
LazyData: true
URL: https://github.com/gaborcsardi/secret#readme
BugReports: https://github.com/gaborcsardi/secret/issues
RoxygenNote: 6.0.1.9000
Imports: assertthat, openssl, rprojroot, curl, jsonlite
Suggests: covr, mockery, testthat, knitr, rmarkdown, withr
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-06-17 09:01:46 UTC; gaborcsardi
Author: Gábor Csárdi [aut, cre], Andrie de Vries [aut]
Maintainer: Gábor Csárdi <csardi.gabor@gmail.com>
Repository: CRAN
Date/Publication: 2017-06-17 14:33:35 UTC

More information about secret at CRAN
Permanent link

New package RSQLServer with initial version 0.3.0
Package: RSQLServer
Type: Package
Title: SQL Server R Database Interface (DBI) and 'dplyr' SQL Backend
Version: 0.3.0
Authors@R: c(person("Imanuel", "Costigan", role = c("aut", "cre"), email = "i.costigan@me.com"), person("The jTDS Project (for MSSQL Server driver)", role = "aut"), person("Simon", "Urbanek", role = "ctb", email = "Simon.Urbanek@r-project.org"), person("Hadley", "Wickham", email = "hadley@rstudio.com", role = "ctb"), person("Hong", "Ooi", email = "hongooi@microsoft.com", role = "ctb"), person("Romain", "Francois", email = "romain@r-enthusiasts.com", role = "ctb"), person("Bill", "Evans", email = "bill@8pawsexpress.com", role = "ctb"), person("RStudio", role = "cph"), person("The Legion Of The Bouncy Castle", role = c("cph", "ctb")))
Description: Utilises The 'jTDS' project's 'JDBC' 3.0 'SQL Server' driver to extend 'DBI' classes and methods. The package also implements a 'SQL' backend to the 'dplyr' package.
License: GPL-2
Depends: R (>= 3.2.0)
Imports: methods (>= 3.2.0), DBI (>= 0.5.0), rJava (>= 0.9.6), dplyr (>= 0.7.0), dbplyr (>= 1.0.0), assertthat (>= 0.1), yaml (>= 2.1.13), purrr (>= 0.2.1)
Suggests: testthat, DBItest (>= 1.4), covr
SystemRequirements: Java (>= 1.3)
URL: https://github.com/imanuelcostigan/RSQLServer
BugReports: https://github.com/imanuelcostigan/RSQLServer/issues
Collate: 'RSQLServer.R' 'Utils.R' 'dbi-classes.R' 'dbi-methods.R' 'dbi-shims.R' 'dbi-tables.R' 'dplyr-imports.R' 'java-shims.R' 'jdbc-methods.R' 'onLoad.R' 'sql-backends.R'
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-06-16 21:47:46 UTC; imanuel
Author: Imanuel Costigan [aut, cre], The jTDS Project (for MSSQL Server driver) [aut], Simon Urbanek [ctb], Hadley Wickham [ctb], Hong Ooi [ctb], Romain Francois [ctb], Bill Evans [ctb], RStudio [cph], The Legion Of The Bouncy Castle [cph, ctb]
Maintainer: Imanuel Costigan <i.costigan@me.com>
Repository: CRAN
Date/Publication: 2017-06-17 14:33:29 UTC

More information about RSQLServer at CRAN
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Package opencpu updated to version 2.0.2 with previous version 2.0.1 dated 2017-05-21

Title: Producing and Reproducing Results
Description: A system for embedded scientific computing and reproducible research with R. The OpenCPU server exposes a simple but powerful HTTP api for RPC and data interchange with R. This provides a reliable and scalable foundation for statistical services or building R web applications. The OpenCPU server runs either as a single-user development server within the interactive R session, or as a multi-user Linux stack based on Apache2. The entire system is fully open source and permissively licensed. The OpenCPU website has detailed documentation and example apps.
Author: Jeroen Ooms
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

Diff between opencpu versions 2.0.1 dated 2017-05-21 and 2.0.2 dated 2017-06-17

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Package MFPCA updated to version 1.1 with previous version 1.0-1 dated 2016-08-12

Title: Multivariate Functional Principal Component Analysis for Data Observed on Different Dimensional Domains
Description: Calculate a multivariate functional principal component analysis for data observed on different dimensional domains. The estimation algorithm relies on univariate basis expansions for each element of the multivariate functional data. Multivariate and univariate functional data objects are represented by S4 classes for this type of data implemented in the package 'funData'.
Author: Clara Happ [aut, cre]
Maintainer: Clara Happ <clara.happ@stat.uni-muenchen.de>

Diff between MFPCA versions 1.0-1 dated 2016-08-12 and 1.1 dated 2017-06-17

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More information about MFPCA at CRAN
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Package interp updated to version 1.0-29 with previous version 1.0-27 dated 2017-06-16

Title: Interpolation Methods
Description: Bivariate data interpolation on regular and irregular grids, either linear or using splines are the main part of this package. It is intended to provide FOSS replacement functions for the ACM licensed akima::interp and tripack::tri.mesh functions. Currently the piecewise linear interpolation part of akima::interp (and also akima::interpp) is implemented in interp::interp, this corresponds to the call akima::interp(..., linear=TRUE) which is the default setting and covers most of akima::interp use cases in depending packages. A re-implementation of Akimas spline interpolation (akima::interp(..., linear=FALSE)) is currently under development and will complete this package in a later version. Estimators for partial derivatives are already available, these are a prerequisite for the spline interpolation. The basic part is currently a GPLed triangulation algorithm (sweep hull algorithm by David Sinclair) providing the starting point for the piecewise linear interpolator. As side effect this algorithm is also used to provide replacements for the basic functions of the tripack package which also suffer from the ACM restrictions. All functions are designed to be backward compatible with their akima / tripack counterparts.
Author: Albrecht Gebhardt [aut, cre, cph] (...), Roger Bivand [aut], David Sinclair [aut, cph]
Maintainer: Albrecht Gebhardt <albrecht.gebhardt@aau.at>

Diff between interp versions 1.0-27 dated 2017-06-16 and 1.0-29 dated 2017-06-17

 ChangeLog           |   31 +++++++++++++++++++++++++++++++
 DESCRIPTION         |   30 ++++++++++++++++++++++++------
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More information about interp at CRAN
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Package frailtyEM updated to version 0.7.0-1 with previous version 0.6.2 dated 2017-05-01

Title: Fitting Frailty Models with the EM Algorithm
Description: Contains functions for fitting shared frailty models with a semi-parametric baseline hazard with the Expectation-Maximization algorithm. Supported data formats include clustered failures with left truncation and recurrent events in gap-time or Andersen-Gill format. Several frailty distributions, such as the the gamma, positive stable and the Power Variance Family are supported.
Author: Theodor Adrian Balan, Hein Putter
Maintainer: Theodor Adrian Balan <t.a.balan@lumc.nl>

Diff between frailtyEM versions 0.6.2 dated 2017-05-01 and 0.7.0-1 dated 2017-06-17

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New package ECFsup with initial version 0.1-2
Package: ECFsup
Type: Package
Title: Equal Covariance Functions Testing by L2-Norm and Sup-Norm
Version: 0.1-2
Date: 2017-06-16
Author: Jia Guo, Bu Zhou, Jin-Ting Zhang
Maintainer: Bu Zhou <bu.zhou@u.nus.edu>
Description: Testing the equality of several covariance functions of functional data. Four different methods are implemented: L2-norm with W-S naive, L2-norm with W-S bias-reduced, L2-norm (Zhang 2013) <ISBN:9781439862735>, and sup-norm with resampling (Guo et al. 2017) <arXiv:1609.04232>.
URL: https://arxiv.org/abs/1609.04232
License: GNU Lesser General Public License
Imports: Rcpp (>= 0.12.9), foreach (>= 1.4.3)
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2017-06-17 12:54:19 UTC; hp
Repository: CRAN
Date/Publication: 2017-06-17 14:57:01 UTC

More information about ECFsup at CRAN
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New package datafsm with initial version 0.2.0
Package: datafsm
Title: Estimating Finite State Machine Models from Data
Version: 0.2.0
Date: 2017-06-16
Authors@R: c( person("Nay", "John J.", email = "john.j.nay@gmail.com", role = c("aut")), person("Gilligan", "Jonathan M.", email = "jonathan.gilligan@vanderbilt.edu", role = c("cre", "aut")))
Description: Our method automatically generates models of dynamic decision- making that both have strong predictive power and are interpretable in human terms. We use an efficient model representation and a genetic algorithm-based estimation process to generate simple deterministic approximations that explain most of the structure of complex stochastic processes. We have applied the software to empirical data, and demonstrated it's ability to recover known data- generating processes by simulating data with agent-based models and correctly deriving the underlying decision models for multiple agent models and degrees of stochasticity.
URL: https://github.com/jonathan-g/datafsm
BugReports: https://github.com/jonathan-g/datafsm/issues
Depends: R (>= 3.1.1), methods, stats
License: MIT + file LICENSE
LazyData: true
LinkingTo: Rcpp
Suggests: doParallel, foreach, testthat, diagram, knitr
Imports: caret, GA, Rcpp
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2017-06-17 02:14:05 UTC; Jonathan
Author: Nay John J. [aut], Gilligan Jonathan M. [cre, aut]
Maintainer: Gilligan Jonathan M. <jonathan.gilligan@vanderbilt.edu>
Repository: CRAN
Date/Publication: 2017-06-17 14:40:08 UTC

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Package blob updated to version 1.1.0 with previous version 1.0.0 dated 2016-12-28

Title: A Simple S3 Class for Representing Vectors of Binary Data ('BLOBS')
Description: R's raw vector is useful for storing a single binary object. What if you want to put a vector of them in a data frame? The blob package provides the blob object, a list of raw vectors, suitable for use as a column in data frame.
Author: Hadley Wickham [aut], Kirill Müller [cre], RStudio [cph]
Maintainer: Kirill Müller <krlmlr+r@mailbox.org>

Diff between blob versions 1.0.0 dated 2016-12-28 and 1.1.0 dated 2017-06-17

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Package tableone updated to version 0.8.1 with previous version 0.7.3 dated 2015-11-11

Title: Create 'Table 1' to Describe Baseline Characteristics
Description: Creates 'Table 1', i.e., description of baseline patient characteristics, which is essential in every medical research. Supports both continuous and categorical variables, as well as p-values and standardized mean differences. Weighted data are supported via the 'survey' package. See 'github' for a screen cast. 'tableone' was inspired by descriptive statistics functions in 'Deducer' , a Java-based GUI package by Ian Fellows. This package does not require GUI or Java, and intended for command-line users.
Author: Kazuki Yoshida, Justin Bohn.
Maintainer: Kazuki Yoshida <kazukiyoshida@mail.harvard.edu>

Diff between tableone versions 0.7.3 dated 2015-11-11 and 0.8.1 dated 2017-06-17

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Package xpose4 updated to version 4.6.0 with previous version 4.5.3 dated 2014-11-24

Title: Tools for Nonlinear Mixed-Effect Model Building and Diagnostics
Description: A collection of functions to be used as a model building aid for nonlinear mixed-effects (population) analysis using NONMEM. It facilitates data set checkout, exploration and visualization, model diagnostics, candidate covariate identification and model comparison.
Author: Andrew C. Hooker [aut, cre, cph], Mats O. Karlsson [aut, cph], Justin J. Wilkins [aut], E. Niclas Jonsson [aut, trl, cph], Ron Keizer [ctb] (functionality for bootstrap of GAM and SCM)
Maintainer: Andrew C. Hooker <andrew.hooker@farmbio.uu.se>

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 xpose4-4.6.0/xpose4/R/absval.iwres.vs.idv.R                 |   38 
 xpose4-4.6.0/xpose4/R/absval.iwres.vs.ipred.R               |   57 
 xpose4-4.6.0/xpose4/R/absval.iwres.vs.ipred.by.cov.R        |   60 
 xpose4-4.6.0/xpose4/R/absval.iwres.vs.pred.R                |   58 
 xpose4-4.6.0/xpose4/R/absval.iwres.wres.vs.ipred.pred.R     |   30 
 xpose4-4.6.0/xpose4/R/absval.wres.vs.cov.bw.R               |   58 
 xpose4-4.6.0/xpose4/R/absval.wres.vs.idv.R                  |   66 
 xpose4-4.6.0/xpose4/R/absval.wres.vs.pred.R                 |   56 
 xpose4-4.6.0/xpose4/R/absval.wres.vs.pred.by.cov.R          |   62 
 xpose4-4.6.0/xpose4/R/add.absval.R                          |   80 
 xpose4-4.6.0/xpose4/R/add.dichot.R                          |   25 
 xpose4-4.6.0/xpose4/R/add.exp.R                             |   24 
 xpose4-4.6.0/xpose4/R/add.grid.table.R                      |   41 
 xpose4-4.6.0/xpose4/R/add.log.R                             |    3 
 xpose4-4.6.0/xpose4/R/add.model.comp.R                      |   57 
 xpose4-4.6.0/xpose4/R/add.tad.R                             |    4 
 xpose4-4.6.0/xpose4/R/addid.R                               |   38 
 xpose4-4.6.0/xpose4/R/addit.gof.R                           |   71 
 xpose4-4.6.0/xpose4/R/all_classes.R                         |only
 xpose4-4.6.0/xpose4/R/autocorr.cwres.R                      |   63 
 xpose4-4.6.0/xpose4/R/autocorr.iwres.R                      |   35 
 xpose4-4.6.0/xpose4/R/autocorr.wres.R                       |   62 
 xpose4-4.6.0/xpose4/R/basic.gof.R                           |   74 
 xpose4-4.6.0/xpose4/R/basic.model.comp.R                    |   55 
 xpose4-4.6.0/xpose4/R/boot.hist.R                           |  444 ++--
 xpose4-4.6.0/xpose4/R/bootgam.R                             |  107 -
 xpose4-4.6.0/xpose4/R/bootgam.menu.R                        |   37 
 xpose4-4.6.0/xpose4/R/bootgam.plots.R                       |  877 +++++++-
 xpose4-4.6.0/xpose4/R/bootscm.R                             |  719 +++----
 xpose4-4.6.0/xpose4/R/calc.npar.R                           |   42 
 xpose4-4.6.0/xpose4/R/cat.dv.vs.idv.sb.R                    |   65 
 xpose4-4.6.0/xpose4/R/cat.pc.R                              |   61 
 xpose4-4.6.0/xpose4/R/categorical.table.R                   |   35 
 xpose4-4.6.0/xpose4/R/change.ab.graph.par.R                 |   72 
 xpose4-4.6.0/xpose4/R/change.bw.graph.par.R                 |   28 
 xpose4-4.6.0/xpose4/R/change.cat.cont.R                     |  107 -
 xpose4-4.6.0/xpose4/R/change.cat.levels.R                   |   33 
 xpose4-4.6.0/xpose4/R/change.cond.graph.par.R               |   27 
 xpose4-4.6.0/xpose4/R/change.dil.graph.par.R                |   27 
 xpose4-4.6.0/xpose4/R/change.dispersion.R                   |   77 
 xpose4-4.6.0/xpose4/R/change.dv.cat.levels.R                |   30 
 xpose4-4.6.0/xpose4/R/change.label.par.R                    |   26 
 xpose4-4.6.0/xpose4/R/change.lm.graph.par.R                 |   27 
 xpose4-4.6.0/xpose4/R/change.medianNorm.R                   |   54 
 xpose4-4.6.0/xpose4/R/change.misc.graph.par.R               |   27 
 xpose4-4.6.0/xpose4/R/change.miss.R                         |   27 
 xpose4-4.6.0/xpose4/R/change.parm.R                         |   15 
 xpose4-4.6.0/xpose4/R/change.pi.graph.par.R                 |   26 
 xpose4-4.6.0/xpose4/R/change.smooth.graph.par.R             |   26 
 xpose4-4.6.0/xpose4/R/change.subset.R                       |   54 
 xpose4-4.6.0/xpose4/R/change.var.name.R                     |   30 
 xpose4-4.6.0/xpose4/R/change.xlabel.R                       |   32 
 xpose4-4.6.0/xpose4/R/change.xvardef.R                      |   62 
 xpose4-4.6.0/xpose4/R/check.gamobj.R                        |   78 
 xpose4-4.6.0/xpose4/R/check.vars.R                          |   38 
 xpose4-4.6.0/xpose4/R/compute.cwres.R                       |  444 ++++
 xpose4-4.6.0/xpose4/R/computePI.R                           |   19 
 xpose4-4.6.0/xpose4/R/continuous.table.R                    |   26 
 xpose4-4.6.0/xpose4/R/cov.hist.R                            |   76 
 xpose4-4.6.0/xpose4/R/cov.qq.R                              |   81 
 xpose4-4.6.0/xpose4/R/cov.splom.R                           |   26 
 xpose4-4.6.0/xpose4/R/cov.summary.R                         |   74 
 xpose4-4.6.0/xpose4/R/create.mirror.R                       |   49 
 xpose4-4.6.0/xpose4/R/create.parameter.list.R               |  255 +-
 xpose4-4.6.0/xpose4/R/create.rand.R                         |   24 
 xpose4-4.6.0/xpose4/R/create.strat.rand.R                   |    2 
 xpose4-4.6.0/xpose4/R/create.xpose.plot.classes.R           |   29 
 xpose4-4.6.0/xpose4/R/createXposeClasses.R                  |  511 ++---
 xpose4-4.6.0/xpose4/R/cwres.dist.hist.R                     |   28 
 xpose4-4.6.0/xpose4/R/cwres.dist.qq.R                       |   40 
 xpose4-4.6.0/xpose4/R/cwres.vs.cov.R                        |  170 +
 xpose4-4.6.0/xpose4/R/cwres.vs.idv.R                        |   49 
 xpose4-4.6.0/xpose4/R/cwres.vs.idv.bw.R                     |   43 
 xpose4-4.6.0/xpose4/R/cwres.vs.pred.R                       |   44 
 xpose4-4.6.0/xpose4/R/cwres.vs.pred.bw.R                    |   67 
 xpose4-4.6.0/xpose4/R/cwres.wres.vs.idv.R                   |   65 
 xpose4-4.6.0/xpose4/R/cwres.wres.vs.pred.R                  |   29 
 xpose4-4.6.0/xpose4/R/dOFV.vs.cov.R                         |   35 
 xpose4-4.6.0/xpose4/R/dOFV.vs.id.R                          |   48 
 xpose4-4.6.0/xpose4/R/dOFV1.vs.dOFV2.R                      |   37 
 xpose4-4.6.0/xpose4/R/data.checkout.R                       |   72 
 xpose4-4.6.0/xpose4/R/db.names.R                            |   64 
 xpose4-4.6.0/xpose4/R/dv.preds.vs.idv.R                     |   63 
 xpose4-4.6.0/xpose4/R/dv.vs.idv.R                           |   52 
 xpose4-4.6.0/xpose4/R/dv.vs.ipred.R                         |   37 
 xpose4-4.6.0/xpose4/R/dv.vs.ipred.by.cov.R                  |   42 
 xpose4-4.6.0/xpose4/R/dv.vs.ipred.by.idv.R                  |   36 
 xpose4-4.6.0/xpose4/R/dv.vs.pred.R                          |   40 
 xpose4-4.6.0/xpose4/R/dv.vs.pred.by.cov.R                   |   41 
 xpose4-4.6.0/xpose4/R/dv.vs.pred.by.idv.R                   |   35 
 xpose4-4.6.0/xpose4/R/dv.vs.pred.ipred.R                    |   45 
 xpose4-4.6.0/xpose4/R/eq.xpose.R                            |    2 
 xpose4-4.6.0/xpose4/R/export.graph.par.R                    |   64 
 xpose4-4.6.0/xpose4/R/export.variable.definitions.R         |   48 
 xpose4-4.6.0/xpose4/R/fix.wrapped.lines.R                   |   23 
 xpose4-4.6.0/xpose4/R/get.doc.R                             |   26 
 xpose4-4.6.0/xpose4/R/get.refrunno.R                        |    2 
 xpose4-4.6.0/xpose4/R/gof.R                                 |  136 +
 xpose4-4.6.0/xpose4/R/gofSetup.R                            |    2 
 xpose4-4.6.0/xpose4/R/import.graph.par.R                    |   64 
 xpose4-4.6.0/xpose4/R/import.variable.definitions.R         |   57 
 xpose4-4.6.0/xpose4/R/ind.plots.R                           |  104 +
 xpose4-4.6.0/xpose4/R/ind.plots.cwres.hist.R                |    5 
 xpose4-4.6.0/xpose4/R/ind.plots.cwres.qq.R                  |    5 
 xpose4-4.6.0/xpose4/R/ind.plots.wres.hist.R                 |   95 
 xpose4-4.6.0/xpose4/R/ind.plots.wres.qq.R                   |   98 
 xpose4-4.6.0/xpose4/R/ipred.vs.idv.R                        |   44 
 xpose4-4.6.0/xpose4/R/is.readable.file.R                    |    2 
 xpose4-4.6.0/xpose4/R/iwres.dist.hist.R                     |   25 
 xpose4-4.6.0/xpose4/R/iwres.dist.qq.R                       |   23 
 xpose4-4.6.0/xpose4/R/iwres.vs.idv.R                        |   39 
 xpose4-4.6.0/xpose4/R/kaplan.plot.R                         |  147 +
 xpose4-4.6.0/xpose4/R/make.sb.data.R                        |   18 
 xpose4-4.6.0/xpose4/R/npc.coverage.R                        |   95 
 xpose4-4.6.0/xpose4/R/nsim.R                                |   26 
 xpose4-4.6.0/xpose4/R/parm.hist.R                           |   26 
 xpose4-4.6.0/xpose4/R/parm.qq.R                             |   36 
 xpose4-4.6.0/xpose4/R/parm.splom.R                          |  164 -
 xpose4-4.6.0/xpose4/R/parm.summary.R                        |   29 
 xpose4-4.6.0/xpose4/R/parm.vs.cov.R                         |   53 
 xpose4-4.6.0/xpose4/R/parm.vs.parm.R                        |   47 
 xpose4-4.6.0/xpose4/R/prazosin_xpdb.R                       |only
 xpose4-4.6.0/xpose4/R/pred.vs.idv.R                         |   45 
 xpose4-4.6.0/xpose4/R/print.xpose.multiple.plot.R           |   99 
 xpose4-4.6.0/xpose4/R/randtest.hist.R                       |   71 
 xpose4-4.6.0/xpose4/R/ranpar.hist.R                         |   26 
 xpose4-4.6.0/xpose4/R/ranpar.qq.R                           |   28 
 xpose4-4.6.0/xpose4/R/ranpar.splom.R                        |   26 
 xpose4-4.6.0/xpose4/R/ranpar.vs.cov.R                       |   53 
 xpose4-4.6.0/xpose4/R/read.TTE.sim.data.R                   |   31 
 xpose4-4.6.0/xpose4/R/read.lst.R                            |    2 
 xpose4-4.6.0/xpose4/R/read.lst6.R                           |   24 
 xpose4-4.6.0/xpose4/R/read.lst7.R                           |   23 
 xpose4-4.6.0/xpose4/R/read.nm.tables.R                      |  226 +-
 xpose4-4.6.0/xpose4/R/read.npc.vpc.results.R                |   36 
 xpose4-4.6.0/xpose4/R/read.phi.R                            |   24 
 xpose4-4.6.0/xpose4/R/read.vpctab.R                         |   35 
 xpose4-4.6.0/xpose4/R/read_nm_table.R                       |only
 xpose4-4.6.0/xpose4/R/reset.graph.par.R                     |   59 
 xpose4-4.6.0/xpose4/R/runsum.R                              |   70 
 xpose4-4.6.0/xpose4/R/set.doc.R                             |   66 
 xpose4-4.6.0/xpose4/R/simprazExample.R                      |   29 
 xpose4-4.6.0/xpose4/R/tabulate.parameters.R                 |   36 
 xpose4-4.6.0/xpose4/R/test.xpose.data.R                     |    2 
 xpose4-4.6.0/xpose4/R/wres.dist.hist.R                      |   27 
 xpose4-4.6.0/xpose4/R/wres.dist.qq.R                        |   26 
 xpose4-4.6.0/xpose4/R/wres.vs.cov.R                         |   62 
 xpose4-4.6.0/xpose4/R/wres.vs.idv.R                         |   42 
 xpose4-4.6.0/xpose4/R/wres.vs.idv.bw.R                      |   36 
 xpose4-4.6.0/xpose4/R/wres.vs.pred.R                        |   38 
 xpose4-4.6.0/xpose4/R/wres.vs.pred.bw.R                     |   37 
 xpose4-4.6.0/xpose4/R/xlabel.R                              |   59 
 xpose4-4.6.0/xpose4/R/xp.akaike.plot.R                      |   65 
 xpose4-4.6.0/xpose4/R/xp.cook.R                             |   71 
 xpose4-4.6.0/xpose4/R/xp.gam.R                              |   42 
 xpose4-4.6.0/xpose4/R/xp.get.disp.R                         |   89 
 xpose4-4.6.0/xpose4/R/xp.ind.inf.fit.R                      |  140 -
 xpose4-4.6.0/xpose4/R/xp.ind.inf.terms.R                    |  101 -
 xpose4-4.6.0/xpose4/R/xp.ind.stud.res.R                     |   33 
 xpose4-4.6.0/xpose4/R/xp.plot.R                             |   30 
 xpose4-4.6.0/xpose4/R/xp.scope3.R                           |  175 -
 xpose4-4.6.0/xpose4/R/xp.summary.R                          |   25 
 xpose4-4.6.0/xpose4/R/xpose.VPC.R                           |  274 ++
 xpose4-4.6.0/xpose4/R/xpose.VPC.both.R                      |   57 
 xpose4-4.6.0/xpose4/R/xpose.VPC.categorical.R               |   81 
 xpose4-4.6.0/xpose4/R/xpose.ask.for.filename.R              |   18 
 xpose4-4.6.0/xpose4/R/xpose.bin.R                           |    2 
 xpose4-4.6.0/xpose4/R/xpose.calculate.cwres.R               |   31 
 xpose4-4.6.0/xpose4/R/xpose.create.title.R                  |   44 
 xpose4-4.6.0/xpose4/R/xpose.data.R                          |  198 +
 xpose4-4.6.0/xpose4/R/xpose.dev.new.R                       |   34 
 xpose4-4.6.0/xpose4/R/xpose.gam.R                           |   94 
 xpose4-4.6.0/xpose4/R/xpose.license.citation.R              |   15 
 xpose4-4.6.0/xpose4/R/xpose.log.axes.R                      |   38 
 xpose4-4.6.0/xpose4/R/xpose.multiple.plot.R                 |   33 
 xpose4-4.6.0/xpose4/R/xpose.multiple.plot.default.R         |   59 
 xpose4-4.6.0/xpose4/R/xpose.panel.bw.R                      |  102 +
 xpose4-4.6.0/xpose4/R/xpose.panel.default.R                 |  433 ++++
 xpose4-4.6.0/xpose4/R/xpose.panel.histogram.R               |   77 
 xpose4-4.6.0/xpose4/R/xpose.panel.qq.R                      |   26 
 xpose4-4.6.0/xpose4/R/xpose.panel.splom.R                   |   65 
 xpose4-4.6.0/xpose4/R/xpose.plot.bw.R                       |   99 
 xpose4-4.6.0/xpose4/R/xpose.plot.default.R                  |  225 +-
 xpose4-4.6.0/xpose4/R/xpose.plot.histogram.R                |   95 
 xpose4-4.6.0/xpose4/R/xpose.plot.qq.R                       |   82 
 xpose4-4.6.0/xpose4/R/xpose.plot.splom.R                    |  115 +
 xpose4-4.6.0/xpose4/R/xpose.print.R                         |   36 
 xpose4-4.6.0/xpose4/R/xpose.read.R                          |   76 
 xpose4-4.6.0/xpose4/R/xpose.stack.R                         |    3 
 xpose4-4.6.0/xpose4/R/xpose.string.print.R                  |   13 
 xpose4-4.6.0/xpose4/R/xpose.write.R                         |   28 
 xpose4-4.6.0/xpose4/R/xpose4-package.R                      |only
 xpose4-4.6.0/xpose4/R/xpose4.R                              |   40 
 xpose4-4.6.0/xpose4/R/xsubset.R                             |   48 
 xpose4-4.6.0/xpose4/R/xvardef.R                             |   39 
 xpose4-4.6.0/xpose4/R/zzz.R                                 |    7 
 xpose4-4.6.0/xpose4/README.md                               |   39 
 xpose4-4.6.0/xpose4/data/simpraz.xpdb.RData                 |binary
 xpose4-4.6.0/xpose4/inst/CITATION                           |    2 
 xpose4-4.6.0/xpose4/inst/xpose.ini                          |   14 
 xpose4-4.6.0/xpose4/man/GAM_summary_and_plot.Rd             |only
 xpose4-4.6.0/xpose4/man/absval.cwres.vs.cov.bw.Rd           |  176 -
 xpose4-4.6.0/xpose4/man/absval.cwres.vs.pred.Rd             |  156 -
 xpose4-4.6.0/xpose4/man/absval.cwres.vs.pred.by.cov.Rd      |  196 +
 xpose4-4.6.0/xpose4/man/absval.iwres.cwres.vs.ipred.pred.Rd |only
 xpose4-4.6.0/xpose4/man/absval.iwres.vs.cov.bw.Rd           |only
 xpose4-4.6.0/xpose4/man/absval.iwres.vs.idv.Rd              |only
 xpose4-4.6.0/xpose4/man/absval.iwres.vs.ipred.Rd            |  158 -
 xpose4-4.6.0/xpose4/man/absval.iwres.vs.ipred.by.cov.Rd     |  174 +
 xpose4-4.6.0/xpose4/man/absval.iwres.vs.pred.Rd             |  163 -
 xpose4-4.6.0/xpose4/man/absval.wres.vs.cov.bw.Rd            |  154 -
 xpose4-4.6.0/xpose4/man/absval.wres.vs.idv.Rd               |  178 -
 xpose4-4.6.0/xpose4/man/absval.wres.vs.pred.Rd              |  151 -
 xpose4-4.6.0/xpose4/man/absval.wres.vs.pred.by.cov.Rd       |  181 +
 xpose4-4.6.0/xpose4/man/absval_delta_vs_cov_model_comp.Rd   |only
 xpose4-4.6.0/xpose4/man/add.grid.table.Rd                   |  170 -
 xpose4-4.6.0/xpose4/man/add.model.comp.Rd                   |  129 -
 xpose4-4.6.0/xpose4/man/add_transformed_columns.Rd          |only
 xpose4-4.6.0/xpose4/man/addid.Rd                            |only
 xpose4-4.6.0/xpose4/man/addit.gof.Rd                        |  196 +
 xpose4-4.6.0/xpose4/man/autocorr.cwres.Rd                   |  166 -
 xpose4-4.6.0/xpose4/man/autocorr.iwres.Rd                   |only
 xpose4-4.6.0/xpose4/man/autocorr.wres.Rd                    |  168 -
 xpose4-4.6.0/xpose4/man/basic.gof.Rd                        |  193 +
 xpose4-4.6.0/xpose4/man/basic.model.comp.Rd                 |  174 +
 xpose4-4.6.0/xpose4/man/boot.hist.Rd                        |  186 -
 xpose4-4.6.0/xpose4/man/bootgam.print.Rd                    |   56 
 xpose4-4.6.0/xpose4/man/bootscm.import.Rd                   |  128 -
 xpose4-4.6.0/xpose4/man/cat.dv.vs.idv.sb.Rd                 |  296 +-
 xpose4-4.6.0/xpose4/man/cat.pc.Rd                           |  193 -
 xpose4-4.6.0/xpose4/man/categorical.table.Rd                |only
 xpose4-4.6.0/xpose4/man/change.parm.Rd                      |   56 
 xpose4-4.6.0/xpose4/man/change.var.name.Rd                  |   66 
 xpose4-4.6.0/xpose4/man/change.xlabel.Rd                    |   72 
 xpose4-4.6.0/xpose4/man/change.xvardef.Rd                   |  153 -
 xpose4-4.6.0/xpose4/man/change_graphical_parameters.Rd      |only
 xpose4-4.6.0/xpose4/man/change_misc_parameters.Rd           |only
 xpose4-4.6.0/xpose4/man/check.vars.Rd                       |only
 xpose4-4.6.0/xpose4/man/compute.cwres.Rd                    |  952 ++++-----
 xpose4-4.6.0/xpose4/man/create.mirror.Rd                    |  101 -
 xpose4-4.6.0/xpose4/man/create.xpose.plot.classes.Rd        |   39 
 xpose4-4.6.0/xpose4/man/createXposeClasses.Rd               |   52 
 xpose4-4.6.0/xpose4/man/cwres.dist.hist.Rd                  |  128 -
 xpose4-4.6.0/xpose4/man/cwres.dist.qq.Rd                    |  124 -
 xpose4-4.6.0/xpose4/man/cwres.vs.cov.Rd                     |  196 +
 xpose4-4.6.0/xpose4/man/cwres.vs.idv.Rd                     |  169 -
 xpose4-4.6.0/xpose4/man/cwres.vs.idv.bw.Rd                  |  156 -
 xpose4-4.6.0/xpose4/man/cwres.vs.pred.Rd                    |  158 -
 xpose4-4.6.0/xpose4/man/cwres.vs.pred.bw.Rd                 |  153 -
 xpose4-4.6.0/xpose4/man/cwres_wres_vs_x.Rd                  |only
 xpose4-4.6.0/xpose4/man/dOFV.vs.cov.Rd                      |  168 -
 xpose4-4.6.0/xpose4/man/dOFV.vs.id.Rd                       |  230 +-
 xpose4-4.6.0/xpose4/man/dOFV1.vs.dOFV2.Rd                   |  179 -
 xpose4-4.6.0/xpose4/man/data.checkout.Rd                    |  195 +
 xpose4-4.6.0/xpose4/man/data_extract_or_assign.Rd           |only
 xpose4-4.6.0/xpose4/man/db.names.Rd                         |   90 
 xpose4-4.6.0/xpose4/man/dv.preds.vs.idv.Rd                  |only
 xpose4-4.6.0/xpose4/man/dv.vs.idv.Rd                        |  145 -
 xpose4-4.6.0/xpose4/man/dv.vs.ipred.Rd                      |  154 -
 xpose4-4.6.0/xpose4/man/dv.vs.ipred.by.cov.Rd               |  176 -
 xpose4-4.6.0/xpose4/man/dv.vs.ipred.by.idv.Rd               |  163 -
 xpose4-4.6.0/xpose4/man/dv.vs.pred.Rd                       |  154 -
 xpose4-4.6.0/xpose4/man/dv.vs.pred.by.cov.Rd                |  176 -
 xpose4-4.6.0/xpose4/man/dv.vs.pred.by.idv.Rd                |  164 -
 xpose4-4.6.0/xpose4/man/dv.vs.pred.ipred.Rd                 |  187 +
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Package sads updated to version 0.4.0 with previous version 0.3.2 dated 2017-06-12

Title: Maximum Likelihood Models for Species Abundance Distributions
Description: Maximum likelihood tools to fit and compare models of species abundance distributions and of species rank-abundance distributions.
Author: Paulo I. Prado, Murilo Dantas Miranda and Andre Chalom
Maintainer: Paulo I. Prado <prado@ib.usp.br>

Diff between sads versions 0.3.2 dated 2017-06-12 and 0.4.0 dated 2017-06-17

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Package rcbalance updated to version 1.8.4 with previous version 1.8.3 dated 2016-08-16

Title: Large, Sparse Optimal Matching with Refined Covariate Balance
Description: Tools for large, sparse optimal matching of treated units and control units in observational studies. Provisions are made for refined covariate balance constraints, which include fine and near-fine balance as special cases. Matches are optimal in the sense that they are computed as solutions to network optimization problems rather than greedy algorithms.
Author: Samuel D. Pimentel
Maintainer: Samuel D. Pimentel <spi@wharton.upenn.edu>

Diff between rcbalance versions 1.8.3 dated 2016-08-16 and 1.8.4 dated 2017-06-17

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Package Rborist updated to version 0.1-7 with previous version 0.1-6 dated 2017-05-09

Title: Extensible, Parallelizable Implementation of the Random Forest Algorithm
Description: Scalable decision tree training and prediction.
Author: Mark Seligman
Maintainer: Mark Seligman <mseligman@suiji.org>

Diff between Rborist versions 0.1-6 dated 2017-05-09 and 0.1-7 dated 2017-06-17

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Package R6 updated to version 2.2.2 with previous version 2.2.1 dated 2017-05-10

Title: Classes with Reference Semantics
Description: The R6 package allows the creation of classes with reference semantics, similar to R's built-in reference classes. Compared to reference classes, R6 classes are simpler and lighter-weight, and they are not built on S4 classes so they do not require the methods package. These classes allow public and private members, and they support inheritance, even when the classes are defined in different packages.
Author: Winston Chang [aut, cre]
Maintainer: Winston Chang <winston@stdout.org>

Diff between R6 versions 2.2.1 dated 2017-05-10 and 2.2.2 dated 2017-06-17

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Package manipulateWidget updated to version 0.7.0 with previous version 0.6.0 dated 2017-05-24

Title: Add Even More Interactivity to Interactive Charts
Description: Like package 'manipulate' does for static graphics, this package helps to easily add controls like sliders, pickers, checkboxes, etc. that can be used to modify the input data or the parameters of an interactive chart created with package 'htmlwidgets'.
Author: Francois Guillem [aut, cre], RTE [cph], JJ Allaire [ctb], Marion Praz [ctb] (New user interface)
Maintainer: Francois Guillem <francois.guillem@rte-france.com>

Diff between manipulateWidget versions 0.6.0 dated 2017-05-24 and 0.7.0 dated 2017-06-17

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Package HiddenMarkov updated to version 1.8-8 with previous version 1.8-7 dated 2016-08-30

Title: Hidden Markov Models
Description: Contains functions for the analysis of Discrete Time Hidden Markov Models, Markov Modulated GLMs and the Markov Modulated Poisson Process. It includes functions for simulation, parameter estimation, and the Viterbi algorithm. See the topic "HiddenMarkov" for an introduction to the package, and "Change Log" for a list of recent changes. The algorithms are based of those of Walter Zucchini.
Author: David Harte
Maintainer: David Harte <d.s.harte@gmail.com>

Diff between HiddenMarkov versions 1.8-7 dated 2016-08-30 and 1.8-8 dated 2017-06-17

 DESCRIPTION             |    8 ++++----
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