Wed, 14 Nov 2018

Package giphyr updated to version 0.1.3 with previous version 0.1.2 dated 2017-10-21

Title: R Interface to the Giphy API
Description: An interface to the 'API' of 'Giphy', a popular index-based search engine for 'GIFs' and animated stickers (see <http://giphy.com/faq> and <https://github.com/Giphy/GiphyAPI> for more information about 'Giphy' and its 'API') . This package also provides a 'RStudio Addin', which can help users easily search and download 'GIFs' and insert them to a 'rmarkdown' presentation.
Author: Hao Zhu [aut, cre] (<https://orcid.org/0000-0002-3386-6076>)
Maintainer: Hao Zhu <haozhu233@gmail.com>

Diff between giphyr versions 0.1.2 dated 2017-10-21 and 0.1.3 dated 2018-11-14

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More information about giphyr at CRAN
Permanent link

Package echarts4r updated to version 0.2.0 with previous version 0.1.1 dated 2018-09-17

Title: Create Interactive Graphs with 'Echarts JavaScript' Version 4
Description: Easily create interactive charts by leveraging the 'Echarts Javascript' library which includes 34 chart types, themes, 'Shiny' proxies and animations.
Author: John Coene [aut, cre]
Maintainer: John Coene <jcoenep@gmail.com>

Diff between echarts4r versions 0.1.1 dated 2018-09-17 and 0.2.0 dated 2018-11-14

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More information about echarts4r at CRAN
Permanent link

Package bReeze updated to version 0.4-3 with previous version 0.4-2 dated 2018-01-05

Title: Functions for Wind Resource Assessment
Description: A collection of functions to analyse, visualize and interpret wind data and to calculate the potential energy production of wind turbines.
Author: Christian Graul and Carsten Poppinga
Maintainer: Christian Graul <christian.graul@gmail.com>

Diff between bReeze versions 0.4-2 dated 2018-01-05 and 0.4-3 dated 2018-11-14

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Package RJafroc updated to version 1.1.0 with previous version 1.0.2 dated 2018-05-31

Title: Modeling, Analysis, Validation and Visualization of Observer Performance Studies in Diagnostic Radiology
Description: Tools for quantitative assessment of medical imaging systems, radiologists or computer aided ('CAD') algorithms. Implements methods described in a book: 'Chakraborty' 'DP' (2017), "Observer Performance Methods for Diagnostic Imaging - Foundations, Modeling, and Applications with R-Based Examples", Taylor-Francis <https://www.crcpress.com/9781482214840> and its Online Appendices <https://github.com/dpc10ster/onlinebookk21778>. Data collection paradigms include receiver operating characteristic ('ROC') and a location specific extension, namely free-response 'ROC' ('FROC'). 'ROC' data consists of a single rating per image, where the rating is the perceived confidence level the image is of a diseased patient. 'FROC' data consists of a variable number (including zero) of mark-rating pairs per image, where a mark is the location of a clinically reportable suspicious region and the rating is the corresponding confidence level that it is a true lesion. The software supersedes the current Windows version of 'JAFROC' software <http://www.devchakraborty.com> which is no longer supported. 'RJafroc' is derived from it being an enhanced R version of original Windows 'JAFROC'. Implemented are a number of figures of merit quantifying performance, functions for visualizing operating characteristics; three ROC ratings data curve-fitting algorithms: the 'binormal' model ('BM'), the contaminated binormal model ('CBM') and the radiological search model ('RSM'). Also implemented is maximum likelihood fitting of paired ROC data utilizing the correlated 'CBM' model ('CORCBM'). Unlike the 'BM', 'CBM', 'CORCBM' and the 'RSM' predict proper ROC curves that do not cross the chance diagonal or display inappropriate hooks, usually near the upper right corner of the plots. 'RSM' fitting yields measures of search and lesion-classification performances, in addition to the usual case-classification performance measured by the area under the 'ROC' curve. Search performance is the ability to find lesions while avoiding finding non-lesions. Lesion-classification performance is the ability to discriminate between found lesions and non-lesions. For fully crossed study designs, termed multiple-reader multiple-case, significance testing of reader-averaged figure-of-merit differences between modalities is implemented via both 'Dorfman', 'Berbaum' and 'Metz' ('DBM') and the 'Obuchowski' and 'Rockette' ('OR') methods, both substantially improved by 'Hillis'. Single treatment analysis allows comparison of performance of a group of radiologists to a specified value, or comparison of 'CAD' performance to a group of radiologists interpreting the same cases. Sample size estimation tools are provided for 'ROC' studies that allow estimation of relevant variances from a pilot study to predict required numbers of readers and cases in a pivotal study. 'FROC' sample size estimation is implemented in Online Appendix Chapter 19 available at <https://github.com/dpc10ster/onlinebookk21778>. Utility and data file manipulation functions allow data to be read in any of the currently used input formats, including Excel, and the results of the analysis can be viewed in text or Excel output files.
Author: Dev Chakraborty [cre, aut, cph], Xuetong Zhai [aut], Lucy D'Agostino McGowan [ctb], Alejandro RodriguezRuiz [ctb]
Maintainer: Dev Chakraborty <dpc10ster@gmail.com>

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Package BDgraph updated to version 2.53 with previous version 2.52 dated 2018-10-03

Title: Bayesian Structure Learning in Graphical Models using Birth-Death MCMC
Description: Provides statistical tools for Bayesian structure learning in undirected graphical models for continuous, discrete, and mixed data. The package is implemented the recent improvements in the Bayesian graphical models literature, including Mohammadi and Wit (2015) <doi:10.1214/14-BA889>, Mohammadi et al. (2017) <doi:10.1111/rssc.12171>, and Dobra and Mohammadi (2018) <doi:10.1214/18-AOAS1164>. To speed up the computations, the BDMCMC sampling algorithms are implemented in parallel using OpenMP in C++.
Author: Reza Mohammadi [aut, cre] <https://orcid.org/0000-0001-9538-0648>, Ernst Wit [aut], Adrian Dobra [ctb]
Maintainer: Reza Mohammadi <a.mohammadi@uva.nl>

Diff between BDgraph versions 2.52 dated 2018-10-03 and 2.53 dated 2018-11-14

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New package tableschema.r with initial version 1.1.0
Package: tableschema.r
Type: Package
Title: Frictionless Data Table Schema
Version: 1.1.0
Date: 2018-11-5
Authors@R: c(person("Kleanthis", "Koupidis", email = "koupidis@okfn.gr", role = c("aut", "cre")), person("Lazaros", "Ioannidis", email = "larjohn@gmail.com", role = "aut"), person("Charalampos", "Bratsas", email = "cbratsas@math.auth.gr", role = "aut"), person("Open Knowledge International", email = "info@okfn.org", role = "cph"))
Maintainer: Kleanthis Koupidis <koupidis@okfn.gr>
Description: Allows to work with 'Table Schema' (<http://specs.frictionlessdata.io/table-schema/>). 'Table Schema' is well suited for use cases around handling and validating tabular data in text formats such as 'csv', but its utility extends well beyond this core usage, towards a range of applications where data benefits from a portable schema format. The 'tableschema.r' package can load and validate any table schema descriptor, allow the creation and modification of descriptors, expose methods for reading and streaming data that conforms to a 'Table Schema' via the 'Tabular Data Resource' abstraction.
URL: https://github.com/frictionlessdata/tableschema-r
BugReports: https://github.com/frictionlessdata/tableschema-r/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: config, future, httr, iterators, jsonlite, jsonvalidate, lubridate, purrr, R6, RCurl, rlist, stringr, urltools
Suggests: covr, foreach, testthat
Collate: 'constraints.checkUnique.R' 'constraints.checkRequired.R' 'constraints.checkPattern.R' 'constraints.checkMinLength.R' 'constraints.checkMinimum.R' 'constraints.checkMaxLength.R' 'constraints.checkMaximum.R' 'constraints.checkEnum.R' 'constraints.R' 'types.castArray.R' 'types.castYearmonth.R' 'types.castYear.R' 'types.castTime.R' 'types.castString.R' 'types.castObject.R' 'types.castNumber.R' 'types.castList.R' 'types.castInteger.R' 'types.castGeopoint.R' 'types.castGeojson.R' 'types.castDuration.R' 'types.castDatetime.R' 'types.castDate.R' 'types.castBoolean.R' 'types.castAny.R' 'types.R' 'field.R' 'helpers.R' 'infer.R' 'is.valid.R' 'tableschemaerror.R' 'profile.R' 'readable.R' 'readable.array.R' 'readable.connection.R' 'schema.R' 'table.R' 'tableschema.r.R' 'validate.R' 'writable.R'
RoxygenNote: 6.1.0.9000
NeedsCompilation: no
Packaged: 2018-11-14 15:09:47 UTC; akis_
Author: Kleanthis Koupidis [aut, cre], Lazaros Ioannidis [aut], Charalampos Bratsas [aut], Open Knowledge International [cph]
Repository: CRAN
Date/Publication: 2018-11-14 16:50:03 UTC

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New package mixsqp with initial version 0.1-79
Encoding: UTF-8
Type: Package
Package: mixsqp
Version: 0.1-79
Date: 2018-11-05
Title: Sequential Quadratic Programming for Fast Maximum-Likelihood Estimation of Mixture Proportions
Authors@R: c(person("Youngseok","Kim",role="aut", email="youngseok@uchicago.edu"), person("Peter","Carbonetto",role=c("aut","cre"), email="peter.carbonetto@gmail.com"), person("Mihai","Anitescu",role="aut"), person("Matthew","Stephens",role="aut"))
URL: https://github.com/stephenslab/mixsqp
BugReports: https://github.com/stephenslab/mixsqp/issues
SystemRequirements: C++11
Depends: R (>= 3.3.0)
Description: Provides optimization algorithms based on sequential quadratic programming (SQP) for maximum likelihood estimation of the mixture proportions in a finite mixture model where the component densities are known. The algorithms are expected to obtain solutions that are at least as accurate as the state-of-the-art MOSEK interior-point solver (called by function "KWDual" in the 'REBayes' package), and they are expected to arrive at solutions more quickly in large data sets. The algorithms are described in Y. Kim, P. Carbonetto, M. Stephens & M. Anitescu (2012) <arXiv:1806.01412>.
License: MIT + file LICENSE
Imports: stats, Rcpp (>= 0.12.15)
Suggests: Rmosek, REBayes, testthat, knitr, rmarkdown
LinkingTo: Rcpp, RcppArmadillo
LazyData: true
NeedsCompilation: yes
VignetteBuilder: knitr
RoxygenNote: 6.1.0.9000
Packaged: 2018-11-05 22:41:03 UTC; pcarbo
Author: Youngseok Kim [aut], Peter Carbonetto [aut, cre], Mihai Anitescu [aut], Matthew Stephens [aut]
Maintainer: Peter Carbonetto <peter.carbonetto@gmail.com>
Repository: CRAN
Date/Publication: 2018-11-14 15:10:03 UTC

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New package sparklyr.nested with initial version 0.0.3
Package: sparklyr.nested
Title: A 'sparklyr' Extension for Nested Data
Version: 0.0.3
Authors@R: c( person("Matt", "Pollock", email = "mpollock@mitre.org", role = c("aut", "cre")), person(family = "The MITRE Corporation", role = c("cph")) )
Maintainer: Matt Pollock <mpollock@mitre.org>
Description: A 'sparklyr' extension adding the capability to work easily with nested data.
Depends: R (>= 3.3)
Imports: sparklyr, jsonlite, listviewer, dplyr, rlang, purrr
License: Apache License 2.0 | file LICENSE
SystemRequirements: Spark: 1.6.x or 2.x
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Suggests: testthat
BugReports: https://github.com/mitre/sparklyr.nested/issues
NeedsCompilation: no
Packaged: 2018-11-05 14:33:31 UTC; mpollock
Author: Matt Pollock [aut, cre], The MITRE Corporation [cph]
Repository: CRAN
Date/Publication: 2018-11-14 14:40:03 UTC

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New package sensmediation with initial version 0.2.0
Package: sensmediation
Title: Parametric Estimation and Sensitivity Analysis of Direct and Indirect Effects
Version: 0.2.0
Date: 2018-11-05
Author: Anita Lindmark <anita.lindmark@umu.se>
Maintainer: Anita Lindmark <anita.lindmark@umu.se>
Description: We implement functions to estimate and perform sensitivity analysis to unobserved confounding of direct and indirect effects introduced in Lindmark, de Luna and Eriksson (2018) <doi:10.1002/sim.7620>. The estimation and sensitivity analysis are parametric, based on probit and/or linear regression models. Sensitivity analysis is implemented for unobserved confounding of the exposure-mediator, mediator-outcome and exposure-outcome relationships.
Depends: R (>= 3.5.0)
Imports: maxLik (>= 1.3-4), mvtnorm (>= 1.0-8), stats (>= 3.5.1)
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Collate: 'calc.effects.R' 'coefs.sensmed.R' 'mediationmethods.R' 'sensmediation.R'
NeedsCompilation: no
Packaged: 2018-11-05 10:16:26 UTC; anli0053
Repository: CRAN
Date/Publication: 2018-11-14 14:40:08 UTC

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New package RGenData with initial version 1.0
Package: RGenData
Type: Package
Title: Generates Multivariate Nonnormal Data and Determines How Many Factors to Retain
Version: 1.0
Author: John Ruscio
Maintainer: John Ruscio <ruscio@tcnj.edu>
Description: The GenDataSample() and GenDataPopulation() functions create, respectively, a sample or population of multivariate nonnormal data using methods described in Ruscio and Kaczetow (2008). Both of these functions call a FactorAnalysis() function to reproduce a correlation matrix. The EFACompData() function allows users to determine how many factors to retain in an exploratory factor analysis of an empirical data set using a method described in Ruscio and Roche (2012). The latter function uses populations of comparison data created by calling the GenDataPopulation() function. <DOI: 10.1080/00273170802285693>. <DOI: 10.1037/a0025697>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2018-11-05 17:02:12 UTC; oliviaortelli
Repository: CRAN
Date/Publication: 2018-11-14 15:00:09 UTC

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New package pluscode with initial version 0.1.0
Package: pluscode
Type: Package
Title: Encoder for Google 'Pluscodes'
Version: 0.1.0
Author: Michael Doyle
Maintainer: Michael Doyle <michaeledoyle7@gmail.com>
Description: Retrieves a 'pluscode' by inputting latitude and longitude. Includes additional functions to retrieve neighbouring 'pluscodes'.
License: GPL-2
LazyData: FALSE
Imports: httr, jsonlite
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2018-11-05 14:01:37 UTC; michael.doyle@paddypowerbetfair.com
Repository: CRAN
Date/Publication: 2018-11-14 15:00:03 UTC

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New package majesticR with initial version 0.1.0
Package: majesticR
Type: Package
Title: R Interface to Access the 'Majestic' API
Version: 0.1.0
Authors@R: person("Remi", "Bacha", email = "hello@remibacha.com", role = c("aut", "cre"))
Description: Implements methods for querying backlink data from 'Majestic' using its API (<https://developer-support.majestic.com/api/>). 'Majestic' API uses a basic authentication with an API key.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Imports: utils, jsonlite
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-11-05 11:37:00 UTC; rbacha
Author: Remi Bacha [aut, cre]
Maintainer: Remi Bacha <hello@remibacha.com>
Repository: CRAN
Date/Publication: 2018-11-14 15:00:06 UTC

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Package LNIRT updated to version 0.3.5 with previous version 0.3.0 dated 2018-03-24

Title: LogNormal Response Time Item Response Theory Models
Description: Allows the simultaneous analysis of responses and response times in an Item Response Theory (IRT) modelling framework. Supports covariates for item and person (random) parameters. Parameter estimation is done with a MCMC algorithm. LNIRT replaces the package CIRT, which was written by Rinke Klein Entink. For reference, see the paper by Fox, Klein Entink and Van der Linden (2007), "Modeling of Responses and Response Times with the Package cirt", Journal of Statistical Software, <doi:10.18637/jss.v020.i07>.
Author: Jean-Paul Fox, Konrad Klotzke, Rinke Klein Entink
Maintainer: Konrad Klotzke <omd.bms.utwente.stats@gmail.com>

Diff between LNIRT versions 0.3.0 dated 2018-03-24 and 0.3.5 dated 2018-11-14

 DESCRIPTION |    8 ++++----
 MD5         |    4 ++--
 R/summary.R |    4 ++--
 3 files changed, 8 insertions(+), 8 deletions(-)

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Package GPM updated to version 2.0.0 with previous version 1.0.2 dated 2018-07-23

Title: Gaussian Process Modeling of Multi-Response Datasets
Description: A general and efficient package for modeling (possibly noisy) datasets via Gaussian processes.
Author: Ramin Bostanabad, Wei Chen (IDEAL)
Maintainer: Ramin Bostanabad <bostanabad@u.northwestern.edu>

Diff between GPM versions 1.0.2 dated 2018-07-23 and 2.0.0 dated 2018-11-14

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 GPM-2.0.0/GPM/NAMESPACE            |    6 
 GPM-2.0.0/GPM/R/Draw.R             |   47 +++----
 GPM-2.0.0/GPM/R/Fit.R              |  244 +++++++++++++++----------------------
 GPM-2.0.0/GPM/R/NLogL.R            |   43 +++---
 GPM-2.0.0/GPM/R/Predict.R          |   73 +++++------
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 GPM-2.0.0/GPM/man/Draw.Rd          |    6 
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New package GB2group with initial version 0.1.0
Package: GB2group
Type: Package
Title: Estimation of the Generalised Beta Distribution of the Second Kind from Grouped Data
Version: 0.1.0
Author: Vanesa Jorda <jordav@unican.es>, Jose Maria Sarabia <jose.sarabia@unican.es>, Markus Jäntti <markus.jantti@sofi.su.se>.
Maintainer: Vanesa Jorda <jordav@unican.es>
Depends: R (>= 3.1.0)
Imports: GB2, minpack.lm, ineq, numDeriv
Description: Estimation of the generalized beta distribution of the second kind (GB2) and related models using grouped data in form of income shares. The GB2 family is a general class of distributions that provides an accurate fit to income data. 'GB2group' includes functions to estimate the GB2, the Singh-Maddala, the Dagum, the Beta 2, the Lognormal and the Fisk distributions. 'GB2group' deploys two different econometric strategies to estimate these parametric distributions, non-linear least squares (NLS) and the generalised method of moments (GMM). Asymptotic standard errors are reported for the GMM estimates. Standard errors of the NLS estimates are obtained by Monte Carlo simulation. See Jorda et al. (2018) <arXiv:1808.09831> for a detailed description of the estimation procedure.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2018-11-05 16:27:59 UTC; Vanesa
Repository: CRAN
Date/Publication: 2018-11-14 15:00:15 UTC

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New package BondValuation with initial version 0.1.0
Package: BondValuation
Title: Fixed Coupon Bond Valuation Allowing for Odd Coupon Periods and Various Day Count Conventions
Date: 2018-11-05
Version: 0.1.0
Authors@R: person("Djatschenko","Wadim",email="wadim.djatschenko@gmx.de",role = c("aut", "cre"))
Description: Analysis of large datasets of fixed coupon bonds, allowing for irregular first and last coupon periods and various day count conventions. With this package you can compute the yield to maturity, the modified and MacAulay durations and the convexity of fixed-rate bonds. It provides the function AnnivDates, which can be used to evaluate the quality of the data and return time-invariant properties and temporal structure of a bond.
Depends: R (>= 2.15.1)
Imports: Rcpp, timeDate
LazyData: TRUE
License: GPL-3
RoxygenNote: 6.1.0
LinkingTo: Rcpp
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2018-11-05 19:51:21 UTC; Wadim
Author: Djatschenko Wadim [aut, cre]
Maintainer: Djatschenko Wadim <wadim.djatschenko@gmx.de>
Repository: CRAN
Date/Publication: 2018-11-14 15:00:18 UTC

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New package adamethods with initial version 1.0
Package: adamethods
Type: Package
Title: Archetypoid Algorithms and Anomaly Detection
Version: 1.0
Date: 2018-11-05
Author: Guillermo Vinue
Maintainer: Guillermo Vinue <Guillermo.Vinue@uv.es>
Description: Collection of several algorithms to obtain archetypoids with small and large databases and with both classical multivariate data and functional data (univariate and multivariate). Some of these algorithms also allow to detect anomalies (outliers).
License: GPL (>= 2)
URL: https://www.R-project.org, https://www.uv.es/vivigui
Depends: R (>= 3.4.0)
Imports: Anthropometry, archetypes, FNN, foreach, nnls, parallel, reticulate, stats, tolerance, univOutl
Suggests: doParallel, fda
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-11-05 13:23:10 UTC; guillevinue
Repository: CRAN
Date/Publication: 2018-11-14 14:40:12 UTC

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Package RJSONIO updated to version 1.3-1.1 with previous version 1.3-1 dated 2018-11-12

Title: Serialize R Objects to JSON, JavaScript Object Notation
Description: This is a package that allows conversion to and from data in Javascript object notation (JSON) format. This allows R objects to be inserted into Javascript/ECMAScript/ActionScript code and allows R programmers to read and convert JSON content to R objects. This is an alternative to rjson package. Originally, that was too slow for converting large R objects to JSON and was not extensible. rjson's performance is now similar to this package, and perhaps slightly faster in some cases. This package uses methods and is readily extensible by defining methods for different classes, vectorized operations, and C code and callbacks to R functions for deserializing JSON objects to R. The two packages intentionally share the same basic interface. This package (RJSONIO) has many additional options to allow customizing the generation and processing of JSON content. This package uses libjson rather than implementing yet another JSON parser. The aim is to support other general projects by building on their work, providing feedback and benefit from their ongoing development.
Author: Duncan Temple Lang [aut, cre] (<https://orcid.org/0000-0003-0159-1546>), Jonathan Wallace [aut] (aka ninja9578, author of included libjson sources)
Maintainer: ORPHANED

Diff between RJSONIO versions 1.3-1 dated 2018-11-12 and 1.3-1.1 dated 2018-11-14

 RJSONIO-1.3-1.1/RJSONIO/DESCRIPTION                          |   13 +-
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 RJSONIO-1.3-1.1/RJSONIO/src/libjson/Source/JSONMemoryPool.h  |    2 
 RJSONIO-1.3-1.1/RJSONIO/src/libjson/Source/JSONValidator.cpp |    4 
 RJSONIO-1.3-1.1/RJSONIO/src/libjson/Source/JSONWorker.cpp    |    8 -
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 29 files changed, 83 insertions(+), 68 deletions(-)

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Package personalized updated to version 0.2.2 with previous version 0.2.1 dated 2018-09-19

Title: Estimation and Validation Methods for Subgroup Identification and Personalized Medicine
Description: Provides functions for fitting and validation of models for subgroup identification and personalized medicine / precision medicine under the general subgroup identification framework of Chen et al. (2017) <doi:10.1111/biom.12676>. This package is intended for use for both randomized controlled trials and observational studies.
Author: Jared Huling [aut, cre] (<https://orcid.org/0000-0003-0670-4845>), Aaron Potvien [ctb], Alexandros Karatzoglou [cph], Alex Smola [cph]
Maintainer: Jared Huling <jaredhuling@gmail.com>

Diff between personalized versions 0.2.1 dated 2018-09-19 and 0.2.2 dated 2018-11-14

 DESCRIPTION                                     |   14 ++---
 MD5                                             |   11 ++--
 R/est_subgroup_effects.R                        |    3 -
 R/summarize_subgroups.R                         |   12 ++--
 inst/CITATION                                   |only
 inst/doc/usage_of_the_personalized_package.html |   66 +++++++++---------------
 man/print.Rd                                    |    7 +-
 7 files changed, 54 insertions(+), 59 deletions(-)

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Package sdcTable updated to version 0.25 with previous version 0.24 dated 2018-07-24

Title: Methods for Statistical Disclosure Control in Tabular Data
Description: Methods for statistical disclosure control in tabular data such as primary and secondary cell suppression as described for example in Hundepol et al. (2012) <doi:10.1002/9781118348239> are covered in this package.
Author: Bernhard Meindl
Maintainer: Bernhard Meindl <bernhard.meindl@gmail.com>

Diff between sdcTable versions 0.24 dated 2018-07-24 and 0.25 dated 2018-11-14

 sdcTable-0.24/sdcTable/README.md                          |only
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 sdcTable-0.25/sdcTable/MD5                                |   24 
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 sdcTable-0.25/sdcTable/inst/doc/sdcTable.html             | 2679 --------------
 sdcTable-0.25/sdcTable/man/calc.problemInstance-method.Rd |    4 
 sdcTable-0.25/sdcTable/man/calc.simpleTriplet-method.Rd   |    3 
 sdcTable-0.25/sdcTable/man/changeCellStatus.Rd            |    3 
 sdcTable-0.25/sdcTable/man/createArgusInput.Rd            |    8 
 sdcTable-0.25/sdcTable/man/get.simpleTriplet-method.Rd    |    3 
 sdcTable-0.25/sdcTable/man/runArgusBatchFile.Rd           |    5 
 sdcTable-0.25/sdcTable/man/sdcProb2df.Rd                  |    3 
 sdcTable-0.25/sdcTable/man/set.problemInstance-method.Rd  |    4 
 14 files changed, 156 insertions(+), 2609 deletions(-)

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New package RCSF with initial version 1.0.1
Package: RCSF
Type: Package
Title: Airborne LiDAR Filtering Method Based on Cloth Simulation
Version: 1.0.1
Date: 2018-11-04
Authors@R: c( person("Jean-Romain", "Roussel", email = "jean-romain.roussel.1@ulaval.ca", role = c("aut", "cre", "cph")), person("Jianbo", "Qi", email = "jianboqi@gmail.com", role = c("aut", "cph")), person("Wuming", "Zhang", email = "", role = c("cph")), person("Peng", "Wan", email = "", role = c( "cph")), person("Hongtao", "Wang", email = "", role = c("cph")), person("State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Science and Engineering, Beijing Normal University", role = c("cph")))
Description: Cloth Simulation Filter (CSF) is an airborne LiDAR (Light Detection and Ranging) ground points filtering algorithm which is based on cloth simulation. It tries to simulate the interactions between the cloth nodes and the corresponding LiDAR points, the locations of the cloth nodes can be determined to generate an approximation of the ground surface.
Depends: R (>= 3.1.0)
Suggests: testthat
License: Apache License 2.0
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp
Imports: Rcpp
RoxygenNote: 6.1.0
NeedsCompilation: yes
Packaged: 2018-11-04 15:14:03 UTC; jr
Author: Jean-Romain Roussel [aut, cre, cph], Jianbo Qi [aut, cph], Wuming Zhang [cph], Peng Wan [cph], Hongtao Wang [cph], State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Science and Engineering, Beijing Normal University [cph]
Maintainer: Jean-Romain Roussel <jean-romain.roussel.1@ulaval.ca>
Repository: CRAN
Date/Publication: 2018-11-14 11:10:06 UTC

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New package mixggm with initial version 1.0
Package: mixggm
Version: 1.0
Date: 2018-11-02
Title: Mixtures of Gaussian Graphical Models
Description: Mixtures of Gaussian graphical models for model-based clustering with sparse covariance and concentration matrices. See Fop, Murphy, and Scrucca (2018) <doi:10.1007/s11222-018-9838-y>.
Authors@R: c(person("Michael", "Fop", role = c("aut", "cre"), email = "michael.fop@ucd.ie", comment = c(ORCID = "0000-0003-3936-2757")), person("Luca", "Scrucca", role = "ctb", comment = c(ORCID = "0000-0003-3826-0484")), person("Thomas Brendan", "Murphy", role = "ctb", comment = c(ORCID = "0000-0002-5668-7046")))
Maintainer: Michael Fop <michael.fop@ucd.ie>
Depends: R (>= 3.3)
Imports: foreach, GA (>= 3.1), mclust (>= 5.4), memoise, network, Rcpp
LinkingTo: Rcpp, RcppArmadillo
License: GPL (>= 2)
Repository: CRAN
URL: https://github.com/michaelfop/mixggm
BugReports: https://github.com/michaelfop/mixggm/issues
ByteCompile: true
LazyLoad: yes
NeedsCompilation: yes
Packaged: 2018-11-14 10:48:05 UTC; michael
Author: Michael Fop [aut, cre] (<https://orcid.org/0000-0003-3936-2757>), Luca Scrucca [ctb] (<https://orcid.org/0000-0003-3826-0484>), Thomas Brendan Murphy [ctb] (<https://orcid.org/0000-0002-5668-7046>)
Date/Publication: 2018-11-14 11:20:02 UTC

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New package MarketMatching with initial version 1.1.1
Package: MarketMatching
Type: Package
Title: Market Matching and Causal Impact Inference
Version: 1.1.1
Date: 2018-11-04
Authors@R: person("Larsen", "Kim", email = "kblarsen4@gmail.com", role = c("aut", "cre"))
Description: For a given test market find the best control markets using time series matching and analyze the impact of an intervention. The intervention could be be a marketing event or some other local business tactic that is being tested. The workflow implemented in MarketMatching utilizes dynamic time warping (the dtw package) to do the matching and the CausalImpact package to analyze the causal impact. In fact, this package can be considered a "workflow wrapper" for those two packages.
Depends: R (>= 3.5.0)
License: GPL (>= 3)
Imports: data.table, ggplot2, dplyr, utils, iterators, doParallel, parallel, foreach, reshape2, CausalImpact, zoo, bsts, scales, dtw
LazyData: true
VignetteBuilder: knitr
Suggests: knitr, rmarkdown
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-11-05 07:47:15 UTC; thirdlovechangethisname
Author: Larsen Kim [aut, cre]
Maintainer: Larsen Kim <kblarsen4@gmail.com>
Repository: CRAN
Date/Publication: 2018-11-14 11:10:09 UTC

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New package forestHES with initial version 1.0-1
Package: forestHES
Version: 1.0-1
Date: 2018-11-4
Type: Package
Title: Forest Health Evaluation System at the Forest Stand Level in China
Authors@R: c(person(given="Zongzheng",family="Chai", email="chaizz@126.com",role=c("aut", "cre")))
Author: Zongzheng Chai [aut, cre]
Maintainer: Zongzheng Chai <chaizz@126.com>
Depends: R (>= 3.4.0)
Description: Assessing forest ecosystem health is an effective way for forest resource management.The national forest health evaluation system at the forest stand level using analytic hierarchy process, has a high application value and practical significance. The package can effectively and easily realize the total assessment process, and help foresters to further assess and management forest resources.
License: GPL (>= 2)
LazyData: TRUE
NeedsCompilation: no
Packaged: 2018-11-05 06:22:26 UTC; jlzhang
Repository: CRAN
Date/Publication: 2018-11-14 11:10:03 UTC

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New package EpiSignalDetection with initial version 0.1.0
Package: EpiSignalDetection
Type: Package
Title: Signal Detection Analysis
Version: 0.1.0
Date: 2018-10-29
Authors@R: c( person( given = "Lore", family = "Merdrignac", role = c("aut", "ctr"), email = "l.merdrignac@epiconcept.fr", comment = "Author of the package and original code"), person( given = "Joana", family = "Gomes Dias", role = c("aut", "fnd", "cre"), email = "joana.gomes.dias@ecdc.europa.eu", comment = "Project manager and package maintainer"), person( given = "Esther", family = "Kissling", role = c("aut", "ctr"), email = "e.kissling@epiconcept.fr"), person( given = "Tommi", family = "Karki", role = c("aut", "fnd"), email = "tommi.karki@ecdc.europa.eu"), person( given = "Margot", family = "Einoder-Moreno", role = c("ctb", "fnd"), email = "margot.einoder-moreno@ecdc.europa.eu"))
Description: Exploring time series for signal detection. It is specifically designed to detect possible outbreaks using infectious disease surveillance data at the European Union / European Economic Area or country level. Automatic detection tools used are presented in the paper "Monitoring count time series in R: aberration detection in public health surveillance", by Salmon et al. (2016) <doi:10.18637/jss.v070.i10>. The package includes: - Signal Detection tool, an interactive 'shiny' application in which the user can import external data and perform basic signal detection analyses; - An automated report in HTML format, presenting the results of the time series analysis in tables and graphs. This report can also be stratified by population characteristics (see 'Population' variable). This project was funded by the European Centre for Disease Prevention and Control.
Depends: R (>= 3.4.0)
License: EUPL
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Imports: shiny, dplyr, pander, DT, surveillance, ISOweek, ggplot2, graphics, utils, knitr (>= 1.20), rmarkdown
VignetteBuilder: knitr
URL: http://atlas.ecdc.europa.eu/public/index.aspx
NeedsCompilation: no
Packaged: 2018-11-05 11:02:59 UTC; LMC
Author: Lore Merdrignac [aut, ctr] (Author of the package and original code), Joana Gomes Dias [aut, fnd, cre] (Project manager and package maintainer), Esther Kissling [aut, ctr], Tommi Karki [aut, fnd], Margot Einoder-Moreno [ctb, fnd]
Maintainer: Joana Gomes Dias <joana.gomes.dias@ecdc.europa.eu>
Repository: CRAN
Date/Publication: 2018-11-14 11:10:12 UTC

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New package EpiReport with initial version 0.1.0
Package: EpiReport
Type: Package
Title: Epidemiological Report
Version: 0.1.0
Date: 2018-10-31
Authors@R: c( person( given = "Lore", family = "Merdrignac", role = c("aut", "ctr", "cre"), email = "l.merdrignac@epiconcept.fr", comment = "Author of the package and original code"), person( given = "Tommi", family = "Karki", role = c("aut", "fnd"), email = "tommi.karki@ecdc.europa.eu"), person( given = "Esther", family = "Kissling", role = c("aut", "ctr"), email = "e.kissling@epiconcept.fr"), person( given = "Joana", family = "Gomes Dias", role = c("aut", "fnd"), email = "joana.gomes.dias@ecdc.europa.eu", comment = "Project manager"))
Description: Drafting an epidemiological report in 'Microsoft Word' format for a given disease, similar to the Annual Epidemiological Reports published by the European Centre for Disease Prevention and Control. Through standalone functions, it is specifically designed to generate each disease specific output presented in these reports and includes: - Table with the distribution of cases by Member State over the last five years; - Seasonality plot with the distribution of cases at the European Union / European Economic Area level, by month, over the past five years; - Trend plot with the trend and number of cases at the European Union / European Economic Area level, by month, over the past five years; - Age and gender bar graph with the distribution of cases at the European Union / European Economic Area level. Two types of datasets can be used: - The default dataset of salmonella 2012-2016 data; - Any dataset specified as described in the vignette.
Depends: R (>= 3.4.0)
License: EUPL
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Imports: officer, flextable, zoo, png, dplyr, tidyr, ggplot2, extrafont, graphics, utils, knitr (>= 1.20), rmarkdown
VignetteBuilder: knitr
URL: https://ecdc.europa.eu/en/annual-epidemiological-reports
NeedsCompilation: no
Packaged: 2018-11-05 10:27:12 UTC; LMC
Author: Lore Merdrignac [aut, ctr, cre] (Author of the package and original code), Tommi Karki [aut, fnd], Esther Kissling [aut, ctr], Joana Gomes Dias [aut, fnd] (Project manager)
Maintainer: Lore Merdrignac <l.merdrignac@epiconcept.fr>
Repository: CRAN
Date/Publication: 2018-11-14 11:10:16 UTC

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New package AutoStepwiseGLM with initial version 0.2.0
Package: AutoStepwiseGLM
Type: Package
Title: Builds Stepwise GLMs via Train and Test Approach
Version: 0.2.0
Author: Aaron England <aaron.england24@gmail.com>
Maintainer: Aaron England <aaron.england24@gmail.com>
Description: Randomly splits data into testing and training sets. Then, uses stepwise selection to fit numerous multiple regression models on the training data, and tests them on the test data. Returned for each model are plots comparing model Akaike Information Criterion (AIC), Pearson correlation coefficient (r) between the predicted and actual values, Mean Absolute Error (MAE), and R-Squared among the models. Each model is ranked relative to the other models by the model evaluation metrics (i.e., AIC, r, MAE, and R-Squared) and the model with the best mean ranking among the model evaluation metrics is returned. Model evaluation metric weights for AIC, r, MAE, and R-Squared are taken in as arguments as aic_wt, r_wt, mae_wt, and r_squ_wt, respectively. They are equally weighted as default but may be adjusted relative to each other if the user prefers one or more metrics to the others, Field, A. (2013, ISBN:978-1-4462-4918-5).
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Depends: caret, formula.tools
NeedsCompilation: no
Packaged: 2018-11-04 17:00:25 UTC; aengland
Repository: CRAN
Date/Publication: 2018-11-14 11:20:06 UTC

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New package zipR with initial version 0.1.0
Package: zipR
Title: Pythonic Zip() for R
Version: 0.1.0
Authors@R: person("Leslie", "Huang", email = "lesliehuang@nyu.edu", role = c("aut", "cre"))
Description: Implements Python-style zip for R. Is a more flexible version of cbind.
Depends: R (>= 2.1.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1.9000
Suggests: knitr, rmarkdown, devtools
URL: https://github.com/leslie-huang/zipR
BugReports: https://github.com/leslie-huang/zipR/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-11-02 20:21:12 UTC; lesliehuang
Author: Leslie Huang [aut, cre]
Maintainer: Leslie Huang <lesliehuang@nyu.edu>
Repository: CRAN
Date/Publication: 2018-11-14 10:20:03 UTC

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New package vegperiod with initial version 0.2.5
Package: vegperiod
Version: 0.2.5
Title: Determine Thermal Vegetation Periods
Authors@R: person("Robert", "Nuske", role=c("aut", "cre"), email="robert.nuske@mailbox.org", comment=c(ORCID="0000-0001-9773-2061"))
Maintainer: Robert Nuske <robert.nuske@mailbox.org>
Depends: R (>= 2.15.0)
Imports: utils
Suggests: curl, testthat (>= 1.0.2)
Description: Collection of common methods to determine growing season length in a simple manner. Start and end dates of the vegetation periods are calculated solely based on daily mean temperatures and the day of the year.
URL: https://github.com/rnuske/vegperiod
BugReports: https://github.com/rnuske/vegperiod/issues
Encoding: UTF-8
License: GPL (>= 3)
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-11-02 19:20:40 UTC; rnuske
Author: Robert Nuske [aut, cre] (<https://orcid.org/0000-0001-9773-2061>)
Repository: CRAN
Date/Publication: 2018-11-14 10:20:06 UTC

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New package SolveRationalMatrixEquation with initial version 0.1.0
Package: SolveRationalMatrixEquation
Type: Package
Title: Solve Rational Matrix Equation
Version: 0.1.0
Author: Aditi Tiwari
Maintainer: Aditi Tiwari <aditi.jec31@gmail.com>
Description: Given a symmetric positive definite matrix Q and a non-singular matrix L, find symmetric positive definite solution X such that X = Q + L (X inv) L^T. Reference: Benner, P., Faßbender, H. On the Solution of the Rational Matrix Equation. Benner, Faßbender (2007) <doi:10.1155/2007/21850>.
License: GPL-2
Encoding: UTF-8
RoxygenNote: 6.1.0
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-11-04 04:00:45 UTC; apple
Repository: CRAN
Date/Publication: 2018-11-14 10:40:09 UTC

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New package smoothROCtime with initial version 0.1.0
Package: smoothROCtime
Type: Package
Title: Smooth Time-Dependent ROC Curve Estimation
Version: 0.1.0
Author: Susana Diaz-Coto <UO266718@uniovi.es>
Maintainer: Susana Diaz-Coto <UO266718@uniovi.es>
Imports: ks
Suggests: KMsurv,lattice, survival
Description: Computes smooth estimations for the Cumulative/Dynamic and Incident/Dynamic ROC curves, in presence of right censorship, based on the bivariate kernel density estimation of the joint distribution function of the Marker and Time-to-event variables.
License: GPL
LazyData: TRUE
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-11-03 02:20:09 UTC; SUSANA
Repository: CRAN
Date/Publication: 2018-11-14 10:40:03 UTC

More information about smoothROCtime at CRAN
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New package semdrw with initial version 0.1.0
Package: semdrw
Type: Package
Title: 'SEM Shiny'
Version: 0.1.0
Author: Kartikeya Bolar
Maintainer: Kartikeya Bolar <kartikeya.bolar@tapmi.edu.in>
Description: Interactive 'shiny' application for working with Structural Equation Modelling technique. Runtime examples are provided in the package function as well as at <https://kartikeyab.shinyapps.io/semwebappk/> .
License: GPL-2
Encoding: UTF-8
LazyData: TRUE
Depends: R (>= 3.0.3)
Imports: shiny,shinyAce,lavaan,semPlot,dplyr,semTools,psych
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-11-04 19:11:55 UTC; KARTIKEYA
Repository: CRAN
Date/Publication: 2018-11-14 11:00:02 UTC

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Package RPyGeo updated to version 1.0.0 with previous version 0.9-3 dated 2012-08-23

Title: ArcGIS Geoprocessing via Python
Description: Provides access to ArcGIS geoprocessing tools by building an interface between R and the ArcPy Python side-package via the reticulate package.
Author: Alexander Brenning [aut, cre], Fabian Polakowski [aut], Marc Becker [aut], Jannes Muenchow [ctb] (<https://orcid.org/0000-0001-7834-4717>)
Maintainer: Alexander Brenning <alexander.brenning@uni-jena.de>

Diff between RPyGeo versions 0.9-3 dated 2012-08-23 and 1.0.0 dated 2018-11-14

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 RPyGeo-1.0.0/RPyGeo/DESCRIPTION                             |   46 
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 37 files changed, 148 insertions(+), 593 deletions(-)

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New package portalr with initial version 0.1.4
Package: portalr
Title: Create Useful Summaries of the Portal Data
Version: 0.1.4
Authors@R: c(person(c("Glenda", "M."), "Yenni", role = c("aut", "cre"), email = "glenda@weecology.org", comment = c(ORCID = "0000-0001-6969-1848")), person("Hao", "Ye", role = c("aut"), comment = c(ORCID = "0000-0002-8630-1458")), person(c("Erica", "M."), "Christensen", role = c("aut"), comment = c(ORCID = "0000-0002-5635-2502")), person(c("Juniper", "L."), "Simonis", role = c("aut"), comment = c(ORCID = "0000-0001-9798-0460")), person(c("Ellen", "K."), "Bledsoe", role = c("aut"), comment = c(ORCID = "0000-0002-3629-7235")), person(c("Renata", "M."), "Diaz", role = c("aut"), comment = c(ORCID = "0000-0003-0803-4734")), person(c("Shawn", "D."), "Taylor", role = c("aut"), comment = c(ORCID = "0000-0002-6178-6903")), person(c("Ethan", "P,"), "White", role = c("ctb"), comment = c(ORCID = "0000-0001-6728-7745")), person(c("S.K.", "Morgan"), "Ernest", role = c("aut"), comment = c(ORCID = "0000-0002-6026-8530")))
Description: Download and generate summaries for the rodent, plant, ant, and weather data from the Portal Project. Portal is a long-term (and ongoing) experimental monitoring site in the Chihuahua desert. The raw data files can be found at <https://github.com/weecology/portalData>.
License: MIT + file LICENSE
URL: https://github.com/weecology/portalr
BugReports: https://github.com/weecology/portalr/issues
LazyData: true
Depends: R (>= 3.2.3)
Imports: dplyr, ggplot2, tidyr, zoo, lubridate, magrittr, httr, rlang, forecast, lunar, jsonlite
Suggests: httptest, digest, tidyverse, cowplot, knitr, rmarkdown
RoxygenNote: 6.1.0
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-11-02 23:31:12 UTC; GlendaYenni
Author: Glenda M. Yenni [aut, cre] (<https://orcid.org/0000-0001-6969-1848>), Hao Ye [aut] (<https://orcid.org/0000-0002-8630-1458>), Erica M. Christensen [aut] (<https://orcid.org/0000-0002-5635-2502>), Juniper L. Simonis [aut] (<https://orcid.org/0000-0001-9798-0460>), Ellen K. Bledsoe [aut] (<https://orcid.org/0000-0002-3629-7235>), Renata M. Diaz [aut] (<https://orcid.org/0000-0003-0803-4734>), Shawn D. Taylor [aut] (<https://orcid.org/0000-0002-6178-6903>), Ethan P, White [ctb] (<https://orcid.org/0000-0001-6728-7745>), S.K. Morgan Ernest [aut] (<https://orcid.org/0000-0002-6026-8530>)
Maintainer: Glenda M. Yenni <glenda@weecology.org>
Repository: CRAN
Date/Publication: 2018-11-14 11:00:07 UTC

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Package mnreadR updated to version 2.1.1 with previous version 2.1.0 dated 2018-07-06

Title: MNREAD Parameters Estimation and Curve Plotting
Description: Allows to analyze the reading data obtained with the MNREAD Acuity Chart, a continuous-text reading acuity chart for normal and low vision. Provides the necessary functions to plot the MNREAD curve and estimate automatically the four MNREAD parameters: Maximum Reading Speed, Critical Print Size, Reading Acuity and Reading Accessibility Index. Parameters can be estimated either with the standard method or with a nonlinear mixed-effects (NLME) modeling. See Calabrese et al. 2018 for more details <doi.org/10.1167/18.1.8>.
Author: Aurélie Calabrèse [aut, cre], J. Steve Mansfield [aut], Gordon E. Legge [aut]
Maintainer: Aurélie Calabrèse <acalabre@umn.edu>

Diff between mnreadR versions 2.1.0 dated 2018-07-06 and 2.1.1 dated 2018-11-14

 DESCRIPTION          |    8 +++++---
 MD5                  |   12 ++++++------
 R/acc_index.R        |    7 ++++++-
 R/all_mnread_param.R |   11 ++++++++---
 R/nlme_curve.R       |   28 +++++++++++++++++++++++++++-
 inst/CITATION        |    4 ++--
 man/nlmeCurve.Rd     |   28 +++++++++++++++++++++++++++-
 7 files changed, 81 insertions(+), 17 deletions(-)

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Package gllvm updated to version 1.1.0 with previous version 1.0 dated 2018-07-30

Title: Generalized Linear Latent Variable Models
Description: Analysis of multivariate data using generalized linear latent variable models (gllvm). Estimation is performed using either Laplace approximation method or variational approximation method implemented via TMB (Kristensen et al., (2016), <doi:10.18637/jss.v070.i05>). Details for gllvm, see Hui et al. (2015) <doi:10.1111/2041-210X.12236> and (2017) <doi:10.1080/10618600.2016.1164708> and Niku et al. (2017) <doi:10.1007/s13253-017-0304-7>.
Author: Jenni Niku, Wesley Brooks, Riki Herliansyah, Francis K.C. Hui, Sara Taskinen, David I. Warton
Maintainer: Jenni Niku <jenni.m.e.niku@jyu.fi>

Diff between gllvm versions 1.0 dated 2018-07-30 and 1.1.0 dated 2018-11-14

 DESCRIPTION                 |   10 
 MD5                         |   56 ++--
 NAMESPACE                   |    9 
 R/TMBtrait.R                |   53 +++-
 R/anova.gllvm.R             |   83 ++++---
 R/coef.gllvm.R              |    8 
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 R/confint.gllvm.R           |   54 ++--
 R/getResidualCor.gllvm.R    |   24 +-
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 man/logLik.gllvm.Rd         |    2 
 man/ordiplot.gllvm.Rd       |    8 
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 man/residuals.gllvm.Rd      |    8 
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 29 files changed, 1299 insertions(+), 700 deletions(-)

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New package gamlss.countKinf with initial version 3.5.1
Package: gamlss.countKinf
Type: Package
Title: Generating and Fitting K-Inflated 'discrete gamlss.family' Distributions
Version: 3.5.1
Author: Saeed Mohammadpour <\email{s.mohammadpour1111@gamlil.com}>, Mikis Stasinopoulos <\email{d.stasinopoulos@londonmet.ac.uk}>
Maintainer: Saeed Mohammadpour <s.mohammadpour1111@gmail.com>
Depends: R (>= 2.2.1), gamlss.dist, gamlss (>= 5.0-0), stats
Description: This is an add on package to 'GAMLSS'. The main purpose of this package is generating and fitting inflated distributions at any desired point (0, 1, 2, ...). The function gen.Kinf() generates K-inflated version of an existing discrete 'GAMLSS' family distribution.
License: GPL-2 | GPL-3
LazyData: True
URL: http://www.gamlss.org/
NeedsCompilation: no
Packaged: 2018-11-02 18:29:23 UTC; User
Repository: CRAN
Date/Publication: 2018-11-14 10:30:03 UTC

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New package flobr with initial version 0.1.0
Package: flobr
Title: Convert Files to and from Binary Objects (BLOBs)
Version: 0.1.0
Authors@R: person("Joe", "Thorley", email = "joe@poissonconsulting.ca", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-7683-4592"))
Description: Converts files to and from flobs. A flob is a file that was read into binary in integer-mode as little endian, saved as the single element of a named list (where the name is the extension of the original file) and then serialized before being coerced into a blob. Flobs are useful for writing and reading files to and from databases.
URL: https://github.com/poissonconsulting/flobr
BugReports: https://github.com/poissonconsulting/flobr/issues
Depends: R (>= 3.3.0)
Imports: err, checkr, blob, tools
Suggests: covr, spelling, testthat
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Language: en-CA
NeedsCompilation: no
Packaged: 2018-11-02 22:41:43 UTC; joe
Author: Joe Thorley [aut, cre] (<https://orcid.org/0000-0002-7683-4592>)
Maintainer: Joe Thorley <joe@poissonconsulting.ca>
Repository: CRAN
Date/Publication: 2018-11-14 10:40:06 UTC

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New package cNORM with initial version 1.0.1
Package: cNORM
Type: Package
Title: Continuous Norming
Version: 1.0.1
Author: Wolfgang Lenhard [cre, aut] (<https://orcid.org/0000-0002-8184-6889>), Alexandra Lenhard [aut], Sebastian Gary [ctb]
Maintainer: Wolfgang Lenhard <wolfgang.lenhard@uni-wuerzburg.de>
Date: 2018-10-24
Authors@R: c(person("Wolfgang", "Lenhard", role = c("cre","aut"), email="wolfgang.lenhard@uni-wuerzburg.de", comment=c(ORCID = "0000-0002-8184-6889")), person("Alexandra", "Lenhard", role=c("aut")), person("Sebastian", "Gary", role=c("ctb")))
Description: Conventional methods for producing standard scores in psychometrics or biometrics are often plagued with "jumps" or "gaps" (i.e., discontinuities) in norm tables and low confidence for assessing extreme scores. The continuous norming method introduced by A. Lenhard et al. (2016), <doi:10.1177/1073191116656437>, generates continuous test norm scores on the basis of the raw data from standardization samples, without requiring assumptions about the distribution of the raw data: Norm scores are directly established from raw data by modeling the latter ones as a function of both percentile scores and an explanatory variable (e.g., age). The method minimizes bias arising from sampling and measurement error, while handling marked deviations from normality, addressing bottom or ceiling effects and capturing almost all of the variance in the original norm data sample.
Depends: R (>= 3.1.0)
Imports: lattice (>= 0.20), leaps (>= 3.0.0), latticeExtra (>= 0.6)
Suggests: knitr, rmarkdown, shiny, shinycssloaders, foreign, readxl
License: AGPL-3
VignetteBuilder: knitr
RoxygenNote: 6.1.0
NeedsCompilation: no
Repository: CRAN
Encoding: UTF-8
LazyData: true
URL: https://www.psychometrica.de/cNorm_en.html, https://github.com/WLenhard/cNORM
BugReports: https://github.com/WLenhard/cNORM/issues
Packaged: 2018-11-02 19:51:43 UTC; gbpa005
Date/Publication: 2018-11-14 10:20:10 UTC

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Package nneo (with last version 0.1.0) was removed from CRAN

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

2017-06-15 0.1.0

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New package solitude with initial version 0.1.0
Package: solitude
Type: Package
Title: An Implementation of Isolation Forest
Version: 0.1.0
Authors@R: person("Komala Sheshachala", "Srikanth", email = "sri.teach@gmail.com", role = c("aut", "cre"))
Description: Isolation forest is anomaly detection method introduced by the paper Isolation based Anomaly Detection (Liu, Ting and Zhou <doi:10.1145/2133360.2133363>).
URL: https://github.com/talegari/solitude
BugReports: https://github.com/talegari/solitude/issues
Imports: ranger (>= 0.10.0), data.table (>= 1.11.4), igraph (>= 1.2.2)
Depends: R (>= 3.4.0)
License: GPL-3
Encoding: UTF-8
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-11-02 04:02:53 UTC; srikanth
Author: Komala Sheshachala Srikanth [aut, cre]
Maintainer: Komala Sheshachala Srikanth <sri.teach@gmail.com>
Repository: CRAN
Date/Publication: 2018-11-14 09:20:03 UTC

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New package rJST with initial version 1.0
Package: rJST
Type: Package
Title: Joint Sentiment Topic Modelling
Version: 1.0
Date: 2018-11-02
Authors@R: c(person(given='Max', family='Boiten',role=c('cre','aut'),email='max_boiten@live.nl'), person(given='Chenghua', family='Lin', role='cph'), person(given='Yulan', family='He', role='cph'))
Maintainer: Max Boiten <max_boiten@live.nl>
Description: Estimates the Joint Sentiment Topic model and its reversed variety, as described by Lin and He, 2009 <DOI:10.1145/1645953.1646003> and Lin, He, Everson and Ruger (2012) <DOI:10.1109/TKDE.2011.48>.
License: GPL-3
Imports: magrittr, quanteda, reshape2, Rcpp (>= 0.12.12), RcppProgress, SnowballC
Depends: methods
Suggests: knitr, rmarkdown
LinkingTo: Rcpp, RcppArmadillo, RcppProgress
Collate: 'RcppExports.R' 'dictionary.R' 'topNwords.R' 'jst_reversed.R' 'jst.R' 'get_parameter.R' 'rJST.R'
Encoding: UTF-8
RoxygenNote: 6.0.1
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2018-11-02 14:52:44 UTC; max_b
Author: Max Boiten [cre, aut], Chenghua Lin [cph], Yulan He [cph]
Repository: CRAN
Date/Publication: 2018-11-14 09:10:03 UTC

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New package pkgverse with initial version 0.0.1
Package: pkgverse
Version: 0.0.1
Title: Build a Meta-Package Universe
Description: Build your own universe of packages similar to the 'tidyverse' package <https://tidyverse.org/> with this meta-package creator. Create a package-verse, or meta package, by supplying a custom name for the collection of packages and the vector of desired package names to include– and optionally supply a destination directory, an indicator of whether to keep the created package directory, and/or a vector of verbs implement via the 'usethis' <http://usethis.r-lib.org/> package.
Authors@R: person("Michael Wayne", "Kearney", , "kearneymw@missouri.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-0730-4694"))
Encoding: UTF-8
LazyData: true
ByteCompile: true
RoxygenNote: 6.1.0.9000
Imports: devtools, usethis, utils
License: CC0
URL: https://pkgverse.mikewk.com
BugReports: https://github.com/mkearney/pkgverse/issues
NeedsCompilation: no
Packaged: 2018-11-02 01:16:21 UTC; mwk
Author: Michael Wayne Kearney [aut, cre] (<https://orcid.org/0000-0002-0730-4694>)
Maintainer: Michael Wayne Kearney <kearneymw@missouri.edu>
Repository: CRAN
Date/Publication: 2018-11-14 09:10:06 UTC

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New package metsyn with initial version 0.1.2
Package: metsyn
Type: Package
Title: Interface with the Meteo France Synop Data API
Version: 0.1.2
Date: 2018-11-01
Authors@R: person("Paul", "Poncet", , "paulponcet@yahoo.fr", role = c("aut", "cre"))
Description: Provides an interface with the Meteo France Synop data API (see <https://donneespubliques.meteofrance.fr/?fond=produit&id_produit=90&id_rubrique=32> for more information). The Meteo France Synop data are made of meteorological data recorded every three hours on 62 French meteorological stations.
License: MIT + file LICENSE
LazyData: TRUE
Depends: R (>= 3.1.3)
Imports: foreach, readr, stringr, tibble, utils
URL: https://github.com/paulponcet/metsyn
BugReports: https://github.com/paulponcet/metsyn/issues
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-11-02 16:22:09 UTC; YL1101
Author: Paul Poncet [aut, cre]
Maintainer: Paul Poncet <paulponcet@yahoo.fr>
Repository: CRAN
Date/Publication: 2018-11-14 09:20:06 UTC

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Package esquisse updated to version 0.1.7 with previous version 0.1.6 dated 2018-10-26

Title: Explore and Visualize Your Data Interactively
Description: A 'shiny' gadget to create 'ggplot2' charts interactively with drag-and-drop to map your variables. You can quickly visualize your data accordingly to their type, export to 'PNG' or 'PowerPoint', and retrieve the code to reproduce the chart.
Author: Fanny Meyer [aut], Victor Perrier [aut, cre], Ian Carroll [ctb] (Facets support)
Maintainer: Victor Perrier <victor.perrier@dreamrs.fr>

Diff between esquisse versions 0.1.6 dated 2018-10-26 and 0.1.7 dated 2018-11-14

 DESCRIPTION                          |    8 ++--
 MD5                                  |   24 ++++++------
 NAMESPACE                            |   11 +++++
 NEWS.md                              |    7 +++
 R/esquisserServer.R                  |    6 +--
 R/esquisserUI.R                      |   24 +++++++++++-
 R/ggplot_helpers.R                   |   35 +++++++++++++-----
 R/ggplot_to_ppt.R                    |   15 ++++---
 R/input-dragula.R                    |   20 ++++++++--
 R/module-chartControls.R             |   67 +++++++++++++++++++++--------------
 R/module-code.R                      |   12 ++++++
 R/module-filterData.R                |    1 
 inst/www/dragula/dragula-bindings.js |    2 -
 13 files changed, 163 insertions(+), 69 deletions(-)

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New package dlbayes with initial version 0.1.0
Package: dlbayes
Type: Package
Title: Use Dirichlet Laplace Prior to Solve Linear Regression Problem and Do Variable Selection
Version: 0.1.0
Author: Shijia Zhang; Meng Li
Maintainer: Shijia Zhang <zsj27@mail.ustc.edu.cn>
Description: The Dirichlet Laplace shrinkage prior in Bayesian linear regression and variable selection, featuring: utility functions in implementing Dirichlet-Laplace priors such as visualization; scalability in Bayesian linear regression; penalized credible regions for variable selection.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: GIGrvg, expm, glmnet, MASS, LaplacesDemon, stats, graphics
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-11-02 14:16:54 UTC; 75747
Repository: CRAN
Date/Publication: 2018-11-14 09:20:09 UTC

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Package DescToolsAddIns updated to version 1.1 with previous version 1.0 dated 2018-03-10

Title: Some Functions to be Used as Shortcuts in 'RStudio'
Description: 'RStudio' as of recently offers the option to define addins and assign shortcuts to them. This package contains addins for a few most frequently used functions in a data scientist's (at least mine) daily work (like str(), example(), plot(), head(), view(), Desc()). Most of these functions will use the current selection in the editor window and send the specific command to the console while instantly executing it. Assigning shortcuts to these addins will save you quite a few keystrokes.
Author: Andri Signorell
Maintainer: Andri Signorell <andri@signorell.net>

Diff between DescToolsAddIns versions 1.0 dated 2018-03-10 and 1.1 dated 2018-11-14

 DESCRIPTION             |    8 +--
 MD5                     |   12 ++---
 NAMESPACE               |    6 +-
 NEWS                    |   11 +++++
 R/AddIns.R              |  102 ++++++++++++++++++++++++++++++++++++++++++++----
 inst/rstudio/addins.dcf |   26 ++++++++++--
 man/DescToolsAddIns.Rd  |   20 +++++++--
 7 files changed, 156 insertions(+), 29 deletions(-)

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New package BaMORC with initial version 1.0
Package: BaMORC
Type: Package
Title: Bayesian Model Optimized Reference Correction Method for Assigned and Unassigned Protein NMR Spectra
Version: 1.0
Depends: R (>= 3.1.0)
Date: 2018-10-18
Authors@R: c( person("Xi", "Chen", email = "billchenxi@gmail.com", comment = c(ORCID="0000-0001-7094-6748"), role = c("aut", "cre")), person("Andrey", "Smelter", email = "andrey.smeltor@gmail.com", comment = c(ORCID="0000-0003-3056-9225"), role = "aut"), person("Hunter", "Moseley", email = "hunter.moseley@uky.edu", comment = c(ORCID="0000-0003-3995-5368"), role = "aut") )
Description: Provides reference correction for protein NMR spectra. Bayesian Model Optimized Reference Correction (BaMORC) is utilizing Bayesian probabilistic framework to perform protein NMR referencing correction, currently for alpha and beta carbon-13 chemical shifts, without any resonance assignment and/or three-dimensional protein structure. For more detailed explanation, please refer to the paper "Automatic 13C Chemical Shift Reference Correction for Unassigned Protein NMR Spectra" <https://rdcu.be/4ly5> (Journal of Biomolecular NMR, Aug 2018)" <doi:10.1007/s10858-018-0202-5>.
URL: https://github.com/MoseleyBioinformaticsLab/BaMORC
BugReports: https://github.com/MoseleyBioinformaticsLab/BaMORC/issues
License: BSD_3_clause + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: data.table, tidyr, DEoptim, httr, docopt, stringr, jsonlite, readr, devtools, RBMRB, BMRBr
RoxygenNote: 6.1.0
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-11-02 13:12:01 UTC; bill
Author: Xi Chen [aut, cre] (<https://orcid.org/0000-0001-7094-6748>), Andrey Smelter [aut] (<https://orcid.org/0000-0003-3056-9225>), Hunter Moseley [aut] (<https://orcid.org/0000-0003-3995-5368>)
Maintainer: Xi Chen <billchenxi@gmail.com>
Repository: CRAN
Date/Publication: 2018-11-14 09:20:13 UTC

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Package StMoSim updated to version 3.1 with previous version 3.0 dated 2014-10-16

Title: Plots a QQ-Norm Plot with Several Gaussian Simulations
Description: Plots a QQ-Norm Plot with several Gaussian simulations.
Author: Matthias Salvisberg
Maintainer: Matthias Salvisberg <matthias.salvisberg@gmail.com>

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Package RBesT updated to version 1.3-5 with previous version 1.3-4 dated 2018-10-17

Title: R Bayesian Evidence Synthesis Tools
Description: Tool-set to support Bayesian evidence synthesis. This includes meta-analysis, (robust) prior derivation from historical data, operating characteristics and analysis (1 and 2 sample cases).
Author: Novartis Pharma AG [cph], Sebastian Weber [aut, cre], Beat Neuenschwander [ctb], Heinz Schmidli [ctb], Baldur Magnusson [ctb], Yue Li [ctb], Satrajit Roychoudhury [ctb], Trustees of Columbia University [cph] (src/init.cpp, tools/make_cc.R, R/stanmodels.R, src/Makevars, src/Makevars.win)
Maintainer: Sebastian Weber <sebastian.weber@novartis.com>

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Package packrat updated to version 0.5.0 with previous version 0.4.9-3 dated 2018-06-01

Title: A Dependency Management System for Projects and their R Package Dependencies
Description: Manage the R packages your project depends on in an isolated, portable, and reproducible way.
Author: Kevin Ushey, Jonathan McPherson, Joe Cheng, Aron Atkins, JJ Allaire
Maintainer: Kevin Ushey <kevin@rstudio.com>

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New package Modalclust with initial version 0.7
Package: Modalclust
Type: Package
Title: Hierarchical Modal Clustering
Version: 0.7
Date: 2018-11-11
Author: Surajit Ray and Yansong Cheng
Maintainer: Surajit Ray <surajit.ray@glasgow.ac.uk>
Description: Performs Modal Clustering (MAC) including Hierarchical Modal Clustering (HMAC) along with their parallel implementation (PHMAC) over several processors. These model-based non-parametric clustering techniques can extract clusters in very high dimensions with arbitrary density shapes. By default clustering is performed over several resolutions and the results are summarised as a hierarchical tree. Associated plot functions are also provided. There is a package vignette that provides many examples. This version adheres to CRAN policy of not spanning more than two child processes by default.
Depends: R (>= 2.14.0), mvtnorm, zoo, class
Suggests: parallel, MASS
License: GPL-2
Packaged: 2018-11-13 20:32:16 UTC; sray
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2018-11-14 08:20:03 UTC

More information about Modalclust at CRAN
Permanent link

Package LVGP updated to version 2.1.4 with previous version 2.1.3 dated 2018-07-31

Title: Latent Variable Gaussian Process Modeling with Qualitative and Quantitative Input Variables
Description: Fit response surfaces for datasets with latent-variable Gaussian process modeling, predict responses for new inputs, and plot latent variables locations in the latent space (only 1D or 2D). The input variables of the datasets can be quantitative, qualitative/categorical or mixed. The output variable of the datasets is a scalar (quantitative). The optimization of the likelihood function is done using a successive approximation/relaxation algorithm similar to another GP modeling package "GPM". The modeling method is published in "A Latent Variable Approach to Gaussian Process Modeling with Qualitative and Quantitative Factors" by Yichi Zhang, Siyu Tao, Wei Chen, and Daniel W. Apley (2018) <arXiv:1806.07504>. The package is developed in IDEAL of Northwestern University.
Author: Siyu Tao, Yichi Zhang
Maintainer: Siyu Tao <siyutao2020@u.northwestern.edu>

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Package JFE updated to version 1.3 with previous version 1.2 dated 2018-03-02

Title: A Menu-Driven GUI for Data Analysis of Just Finance and Econometrics
Description: Support the decision analysis of international assets selection and portfolio backtesting.
Author: Ho Tsung-wu
Maintainer: Ho Tsung-wu <tsungwu@ntnu.edu.tw>

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Package histry updated to version 0.2.4 with previous version 0.2.2 dated 2018-06-25

Title: Enhanced Command History Tracking for R Sessions and Dynamic Documents
Description: Automatically tracks and makes programmatically available code evaluation history in R sessions and dynamic documents.
Author: Gabriel Becker [aut, cre]
Maintainer: Gabriel Becker <gabembecker@gmail.com>

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Package GJRM updated to version 0.1-5 with previous version 0.1-4 dated 2017-12-13

Title: Generalised Joint Regression Modelling
Description: Routines for fitting various joint (and univariate) regression models, with several types of covariate effects, in the presence of equations' errors association, endogeneity, non-random sample selection or partial observability.
Author: Giampiero Marra <giampiero.marra@ucl.ac.uk> and Rosalba Radice <rosalba.radice@city.ac.uk>
Maintainer: Giampiero Marra <giampiero.marra@ucl.ac.uk>

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Package palm updated to version 1.1.2 with previous version 1.1.1 dated 2018-05-03

Title: Fitting Point Process Models via the Palm Likelihood
Description: Functions to fit point process models using the Palm likelihood. First proposed by Tanaka, Ogata, and Stoyan (2008) <DOI:10.1002/bimj.200610339>, maximisation of the Palm likelihood can provide computationally efficient parameter estimation for point process models in situations where the full likelihood is intractable. This package is chiefly focused on Neyman-Scott point processes, but can also fit void processes. The development of this package was motivated by the analysis of capture-recapture surveys on which individuals cannot be identified---the data from which can conceptually be seen as a clustered point process. As such, some of the functions in this package are specifically for the estimation of cetacean density from two-camera aerial surveys.
Author: Ben Stevenson <ben.stevenson@auckland.ac.nz>
Maintainer: Ben Stevenson <ben.stevenson@auckland.ac.nz>

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Package anytime updated to version 0.3.3 with previous version 0.3.2 dated 2018-11-06

Title: Anything to 'POSIXct' or 'Date' Converter
Description: Convert input in any one of character, integer, numeric, factor, or ordered type into 'POSIXct' (or 'Date') objects, using one of a number of predefined formats, and relying on Boost facilities for date and time parsing.
Author: Dirk Eddelbuettel
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package HMMcopula updated to version 1.0.2 with previous version 1.0.1 dated 2018-10-28

Title: Markov Regime Switching Copula Models Estimation and Goodness of Fit
Description: R functions to estimate and perform goodness of fit test for several Markov regime switching and mixture bivariate copula models. The goodness of fit test is based on a Cramer von Mises statistic and uses the Rosenblatt transform and parametric bootstrap to estimate the p-value. The estimation of the copula parameters are based on the pseudo-maximum likelihood method using pseudo-observations defined as normalized ranks.
Author: Mamadou Yamar Thioub <mamadou-yamar.thioub@hec.ca>, Bouchra Nasri <bouchra.nasri@mail.mcgill.ca>, Romanic Pieugueu <romanic.pieugueu@gerad.ca>, and Bruno Remillard <bruno.remillard@hec.ca>
Maintainer: Mamadou Yamar Thioub <mamadou-yamar.thioub@hec.ca>

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 DESCRIPTION       |    8 +++----
 MD5               |   14 ++++++------
 R/EstHMMCop.R     |   61 ++++++++++++++++++++++++++++++++++++++++--------------
 R/EstMixtureCop.R |   32 +++++++++++++++++++++++-----
 R/GofHMMCop.R     |    3 ++
 R/GofMixtureCop.R |    2 -
 R/SimHMMCop.R     |   41 +++++++++++++++++++-----------------
 R/SimMixtureCop.R |    4 ++-
 8 files changed, 112 insertions(+), 53 deletions(-)

More information about HMMcopula at CRAN
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