Mon, 03 Jun 2019

Package table.express updated to version 0.1.1 with previous version 0.1.0 dated 2019-05-31

Title: Build 'data.table' Expressions with Data Manipulation Verbs
Description: A specialization of 'dplyr' data manipulation verbs that parse and build expressions which are ultimately evaluated by 'data.table', letting it handle all optimizations. A set of additional verbs is also provided to facilitate some common operations on a subset of the data.
Author: Alexis Sarda-Espinosa [cre, aut]
Maintainer: Alexis Sarda-Espinosa <alexis.sarda@gmail.com>

Diff between table.express versions 0.1.0 dated 2019-05-31 and 0.1.1 dated 2019-06-03

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Package spectrino updated to version 2.0.0 with previous version 1.6.0 dated 2015-07-27

Title: Spectra Viewer, Organizer, Data Preparation and Property Blocks
Description: Spectra viewer, organizer, data preparation and property blocks from within R or stand-alone. Binary (application) part is installed separately using spnInstallApp() from spectrino package.
Author: Teodor Krastev <spectrino@sicyon.com>
Maintainer: Teodor Krastev <spectrino@sicyon.com>

Diff between spectrino versions 1.6.0 dated 2015-07-27 and 2.0.0 dated 2019-06-03

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New package robcp with initial version 0.2.4
Package: robcp
Title: Robust Change-Point Tests
Version: 0.2.4
Authors@R: c(person("Sheila", "Goerz", email = "sheila.goerz@tu-dortmund.de", role = c("aut", "cre")), person("Alexander", "Duerre", email = "alexander.duerre@udo.edu", role = "ctb"))
Description: Provides robust methods to detect change-points in uni- or multivariate time series. They can cope with corrupted data and heavy tails. One can detect changes in location, scale and dependence structure of a possibly multivariate time series. Procedures are based on Huberized versions of CUSUM tests proposed in Duerre and Fried (2019) <arXiv:1905.06201>.
Depends: R (>= 3.3.1)
License: GPL-3
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
Packaged: 2019-06-03 18:02:21 UTC; Sheila
Author: Sheila Goerz [aut, cre], Alexander Duerre [ctb]
Maintainer: Sheila Goerz <sheila.goerz@tu-dortmund.de>
Repository: CRAN
Date/Publication: 2019-06-03 23:50:14 UTC

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Package MultiRobust updated to version 1.0.5 with previous version 1.0.4 dated 2019-05-03

Title: Multiply Robust Methods for Missing Data Problems
Description: Multiply robust estimation for population mean (Han and Wang 2013) <doi:10.1093/biomet/ass087>, regression analysis (Han 2014) <doi:10.1080/01621459.2014.880058> (Han 2016) <doi:10.1111/sjos.12177> and quantile regression (Han et al. 2019) <doi:10.1111/rssb.12309>.
Author: Shixiao Zhang and Peisong Han
Maintainer: Shixiao Zhang <praetere@gmail.com>

Diff between MultiRobust versions 1.0.4 dated 2019-05-03 and 1.0.5 dated 2019-06-03

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Package naivebayes updated to version 0.9.6 with previous version 0.9.5 dated 2019-03-17

Title: High Performance Implementation of the Naive Bayes Algorithm
Description: In this implementation of the Naive Bayes classifier following class conditional distributions are available: Bernoulli, Categorical, Gaussian, Poisson and non-parametric representation of the class conditional density estimated via Kernel Density Estimation.
Author: Michal Majka
Maintainer: Michal Majka <michalmajka@hotmail.com>

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Package MTLR updated to version 0.2.1 with previous version 0.2.0 dated 2019-03-09

Title: Survival Prediction with Multi-Task Logistic Regression
Description: An implementation of Multi-Task Logistic Regression (MTLR) for R. This package is based on the method proposed by Yu et al. (2011) which utilized MTLR for generating individual survival curves by learning feature weights which vary across time. This model was further extended to account for left and interval censored data.
Author: Humza Haider
Maintainer: Humza Haider <hshaider@ualberta.ca>

Diff between MTLR versions 0.2.0 dated 2019-03-09 and 0.2.1 dated 2019-06-03

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Package PSTR updated to version 1.2.4 with previous version 1.2.3 dated 2018-12-09

Title: Panel Smooth Transition Regression Modelling
Description: Provides the Panel Smooth Transition Regression (PSTR) modelling. The modelling procedure consists of three stages: Specification, Estimation and Evaluation. The package offers sharp tools helping the package user(s) to conduct model specification tests, to do PSTR model estimation, and to do model evaluation. The tests implemented in the package allow for cluster-dependency and are heteroskedasticity-consistent. The wild bootstrap and wild cluster bootstrap tests are also implemented. Parallel computation (as an option) is implemented in some functions, especially the bootstrap tests. The package suits tasks running many cores on super-computation servers.
Author: Yukai Yang [aut, cre] (<https://orcid.org/0000-0002-2623-8549>)
Maintainer: Yukai Yang <yukai.yang@statistik.uu.se>

Diff between PSTR versions 1.2.3 dated 2018-12-09 and 1.2.4 dated 2019-06-03

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New package PowerfulMaxEigenpair with initial version 0.1.0
Package: PowerfulMaxEigenpair
Type: Package
Title: Powerful Algorithm for Maximal Eigenpair
Version: 0.1.0
Date: 2019-06-03
Author: Yueshuang Li <liyueshuang@mail.bnu.edu.cn> and Xiaojun Mao <maoxj@fudan.edu.cn>
Maintainer: Xiaojun Mao <maoxj@fudan.edu.cn>
Description: An implementation for using powerful algorithm to compute the maximal eigenpair of Hermitizable tridiagonal matrices in R. It provides two algorithms to find the maximal and the next to maximal eigenpairs under the tridiagonal matrix. Besides, it also provides two auxiliary algorithms to generate tridiagonal matrix and solve the linear equation by Thomas algorithm. Several examples are included in the vignettes to illustrate the usage of the functions.
License: MIT + file LICENSE
URL: http://github.com/mxjki/PowerfulMaxEigenpair
BugReports: http://github.com/mxjki/PowerfulMaxEigenpair/issues
Depends: R (>= 3.6.0), stats
Encoding: UTF-8
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-06-03 13:59:54 UTC; xiaojunmao
Repository: CRAN
Date/Publication: 2019-06-03 17:20:03 UTC

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New package nlr with initial version 0.1-2
Package: nlr
Type: Package
Title: Nonlinear Regression Modelling using Robust Methods
Version: 0.1-2
Date: 2019-06-03
Author: Hossein Riazoshams
Maintainer: Hossein Riazoshams <riazihosein@gmail.com>
Description: Non-Linear Robust package is developed to handle the problem of outliers in nonlinear regression, using robust statistics. It covers classic methods in nonlinear regression as well. It has facilities to fit models in the case of auto correlated and heterogeneous variance cases, while it include tools to detecting outliers in nonlinear regression. (Riazoshams H, Midi H, and Ghilagaber G, (2018, ISBN:978-1-118-73806-1). Robust Nonlinear Regression, with Application using R, John Wiley and Sons.)
License: GPL-2
LazyData: yes
Imports: MASS,nlme, robcor, TSA,tseries,stats, GA, quantreg
Depends: R (>= 3.6.0), methods
URL: http://www.riazoshams.com/nlr/
NeedsCompilation: no
Packaged: 2019-06-03 16:02:21 UTC; HRIAZ
Repository: CRAN
Date/Publication: 2019-06-03 18:00:03 UTC

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Package MPSEM updated to version 0.3-6 with previous version 0.3-4 dated 2018-05-16

Title: Modeling Phylogenetic Signals using Eigenvector Maps
Description: Computational tools to represent phylogenetic signals using adapted eigenvector maps.
Author: Guillaume Guenard, with contribution from Pierre Legendre
Maintainer: Guillaume Guenard <guillaume.guenard@gmail.com>

Diff between MPSEM versions 0.3-4 dated 2018-05-16 and 0.3-6 dated 2019-06-03

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Package TreeSearch updated to version 0.3.2 with previous version 0.3.0 dated 2019-03-21

Title: Phylogenetic Tree Search Using Custom Optimality Criteria
Description: Searches for phylogenetic trees that are optimal using a user-defined criterion. Implements Profile Parsimony (Faith and Trueman, 2001) <doi:10.1080/10635150118627>, and Successive Approximations (Farris, 1969) <doi:10.2307/2412182>. Handles inapplicable data using the algorithm of Brazeau, Guillerme and Smith (2019) <doi:10.1093/sysbio/syy083>.
Author: Martin R. Smith [aut, cre, cph] (<https://orcid.org/0000-0001-5660-1727>), Emmanuel Paradis [cph] (<https://orcid.org/0000-0003-3092-2199>), Klaus Schliep [cph] (<https://orcid.org/0000-0003-2941-0161>), Martin Brazeau [cph] (<https://orcid.org/0000-0002-0650-1282>)
Maintainer: Martin R. Smith <martin.smith@durham.ac.uk>

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Package secr updated to version 3.2.1 with previous version 3.2.0 dated 2019-01-25

Title: Spatially Explicit Capture-Recapture
Description: Functions to estimate the density and size of a spatially distributed animal population sampled with an array of passive detectors, such as traps, or by searching polygons or transects. Models incorporating distance-dependent detection are fitted by maximizing the likelihood. Tools are included for data manipulation and model selection.
Author: Murray Efford
Maintainer: Murray Efford <murray.efford@otago.ac.nz>

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Package AMR updated to version 0.7.0 with previous version 0.6.1 dated 2019-03-29

Title: Antimicrobial Resistance Analysis
Description: Functions to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods.
Author: Matthijs S. Berends [aut, cre] (<https://orcid.org/0000-0001-7620-1800>), Christian F. Luz [aut] (<https://orcid.org/0000-0001-5809-5995>), Erwin E. A. Hassing [ctb], Corinna Glasner [aut, ths] (<https://orcid.org/0000-0003-1241-1328>), Alex W. Friedrich [aut, ths] (<https://orcid.org/0000-0003-4881-038X>), Bhanu N. M. Sinha [aut, ths] (<https://orcid.org/0000-0003-1634-0010>)
Maintainer: Matthijs S. Berends <m.s.berends@umcg.nl>

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Permanent link

Package statVisual updated to version 1.1.8 with previous version 1.0.9 dated 2019-04-16

Title: Statistical Visualization Tools
Description: Visualization functions in the applications of translational medicine (TM) and biomarker (BM) development to compare groups by statistically visualizing data and/or results of analyses, such as visualizing data by displaying in one figure different groups' histograms, boxplots, densities, scatter plots, error-bar plots, or trajectory plots, by displaying scatter plots of top principal components or dendrograms with data points colored based on group information, or visualizing volcano plots to check the results of whole genome analyses for gene differential expression.
Author: Wenfei Zhang [aut, cre], Weiliang Qiu [aut, ctb], Xuan Lin [aut, ctb], Donghui Zhang [aut, ctb]
Maintainer: Wenfei Zhang <Wenfei.Zhang@sanofi.com>

Diff between statVisual versions 1.0.9 dated 2019-04-16 and 1.1.8 dated 2019-06-03

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Package recmap updated to version 1.0.5 with previous version 1.0.1 dated 2019-03-06

Title: Compute the Rectangular Statistical Cartogram
Description: Provides an interface and a C++ implementation of the RecMap MP2 construction heuristic (Panse C. (2018) <doi:10.18637/jss.v086.c01>). This algorithm draws maps according to a given statistical value (e.g., election results, population or epidemiological data). The basic idea of the RecMap algorithm is that each map region (e.g., different countries) is represented by a rectangle. The area of each rectangle represents the statistical value given as input (maintain zero cartographic error). Documentation about the usage of the recmap algorithm is provided by a vignette included in this package.
Author: Christian Panse [aut, cre] (<https://orcid.org/0000-0003-1975-3064>)
Maintainer: Christian Panse <Christian.Panse@gmail.com>

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New package multicross with initial version 1.0.0
Package: multicross
Type: Package
Title: A Graph-Based Test for Comparing Multivariate Distributions in the Multi Sample Framework
Version: 1.0.0
Author: Somabha Mukherjee <somabha@wharton.upenn.edu> Divyansh Agarwal <divyansh.agarwal@pennmedicine.upenn.edu> Bhaswar Bhattacharya <bhaswar@wharton.upenn.edu> Nancy R. Zhang <nzh@wharton.upenn.edu>
Maintainer: Divyansh Agarwal <divyansh.agarwal@pennmedicine.upenn.edu>
Description: We introduce a nonparametric, graphical test based on optimal matching for assessing whether multiple unknown multivariate probability distributions are equal. This method is consistent, and does not make any distributional assumptions on the data. Our procedure combines data that belong to different classes or groups to create a graph on the pooled data, and then utilizes the number of edges connecting data points from different classes to examine equality of distributions among the classes.
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: nbpMatching (>= 1.5.1), crossmatch (>= 1.3-1), MASS (>= 7.3-49), stats (>= 3.5.0),
Suggests: ape
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-01 11:46:59 UTC; divyanshagarwal
Repository: CRAN
Date/Publication: 2019-06-03 14:40:07 UTC

More information about multicross at CRAN
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Package mlogit updated to version 0.4-2 with previous version 0.4-1 dated 2019-02-01

Title: Multinomial Logit Models
Description: Maximum Likelihood estimation of random utility discrete choice models, as described in Kenneth Train (2012) Discrete Choice Methods with Simulations <doi:10.1017/CBO9780511805271>.
Author: Yves Croissant [aut, cre]
Maintainer: Yves Croissant <yves.croissant@univ-reunion.fr>

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New package json64 with initial version 0.1.3
Package: json64
Type: Package
Title: A 'Base64' Encode/Decode Package with Support for JSON Output/Input and UTF-8
Version: 0.1.3
Author: Mauricio Santelices
Maintainer: Mauricio Santelices <m.santelicesa@gmail.com>
Description: Encode/Decode 'base64', with support for JSON format, using two functions: j_encode() and j_decode(). 'Base64' is a group of similar binary-to-text encoding schemes that represent binary data in an ASCII string format by translating it into a radix-64 representation, used when there is a need to encode binary data that needs to be stored and transferred over media that are designed to deal with textual data, ensuring that the data will remain intact and without modification during transport. <https://developer.mozilla.org/en-US/docs/Web/API/WindowBase64/Base64_encoding_and_decoding> On the other side, JSON (JavaScript Object Notation) is a lightweight data-interchange format. Easy to read, write, parse and generate. It is based on a subset of the JavaScript Programming Language. JSON is a text format that is completely language independent but uses conventions that are familiar to programmers of the C-family of languages, including C, C++, C#, Java, JavaScript, Perl, Python, and many others. JSON structure is built around name:value pairs and ordered list of values. <https://www.json.org> The first function, j_encode(), let you transform a data.frame or list to a 'base64' encoded JSON (or JSON string). The j_decode() function takes a 'base64' string (could be an encoded JSON) and transform it to a data.frame (or list, depending of the JSON structure).
License: MIT + file LICENSE
Imports: jsonlite
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-01 16:36:04 UTC; Mauricio
Repository: CRAN
Date/Publication: 2019-06-03 14:20:03 UTC

More information about json64 at CRAN
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Package jacpop updated to version 0.6 with previous version 0.5 dated 2016-07-25

Title: Jaccard Index for Population Structure Identification
Description: Uses the Jaccard similarity index to account for population structure in sequencing studies. This method was specifically designed to detect population stratification based on rare variants, hence it will be especially useful in rare variant analysis.
Author: Dmitry Prokopenko
Maintainer: Dmitry Prokopenko <dmitry.prokopenko@uni-bonn.de>

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New package swissdd with initial version 1.0.0
Package: swissdd
Type: Package
Title: Get Swiss Federal and Cantonal Vote Results from Opendata.swiss
Imports: purrr, dplyr, tidyr, jsonlite, magrittr, tibble, curl
Version: 1.0.0
Authors@R: c( person("Thomas", "Lo Russo", email = "th.lorusso@gmail.com", role = c("cre","aut")), person("Thomas", "Willi", email = "thomas.willi@uzh.ch", role = "aut"))
Description: Builds upon the real time data service as well as the archive for national votes <https://opendata.swiss/api/3/action/package_show?id=echtzeitdaten-am-abstimmungstag-zu-eidgenoessischen-abstimmungsvorlagen> and cantonal votes <https://opendata.swiss/api/3/action/package_show?id=echtzeitdaten-am-abstimmungstag-zu-kantonalen-abstimmungsvorlagen>. It brings the results of Swiss popular votes, aggregated at the geographical level of choice, into R.
URL: https://github.com/politanch/swissdd
BugReports: https://github.com/politanch/swissdd/issues
License: GPL-2
Encoding: UTF-8
Suggests: testthat
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-05-31 14:01:59 UTC; tlo1
Author: Thomas Lo Russo [cre, aut], Thomas Willi [aut]
Maintainer: Thomas Lo Russo <th.lorusso@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-03 13:10:03 UTC

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Package spectralGraphTopology updated to version 0.1.1 with previous version 0.1.0 dated 2019-05-08

Title: Learning Graphs from Data via Spectral Constraints
Description: Block coordinate descent estimators to learn k-component, bipartite, and k-component bipartite graphs from data by imposing spectral constraints on the eigenvalues and eigenvectors of the Laplacian and adjacency matrices. Those estimators leverages spectral properties of the graphical models as a prior information, which turn out to play key roles in unsupervised machine learning tasks such as clustering and community detection. This package is based on the paper "A Unified Framework for Structured Graph Learning via Spectral Constraints" by S. Kumar et al (2019) <arXiv:1904.09792>.
Author: Ze Vinicius [cre, aut], Daniel P. Palomar [aut]
Maintainer: Ze Vinicius <jvmirca@gmail.com>

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Package shadow updated to version 0.6.1 with previous version 0.6.0 dated 2019-01-07

Title: Geometric Shadow Calculations
Description: Functions for calculating: (1) shadow height, (2) logical shadow flag, (3) shadow footprint, (4) Sky View Factor and (5) radiation load. Basic required inputs include a polygonal layer of obstacle outlines along with their heights (i.e. "extruded polygons"), sun azimuth and sun elevation. The package also provides functions for related preliminary calculations: breaking polygons into line segments, determining azimuth of line segments, shifting segments by azimuth and distance, constructing the footprint of a line-of-sight between an observer and the sun, and creating a 3D grid covering the surface area of extruded polygons.
Author: Michael Dorman [aut, cre], Evyatar Erell [ctb], Itai Kloog [ctb], Adi Vulkan [ctb]
Maintainer: Michael Dorman <dorman@post.bgu.ac.il>

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Package robis updated to version 2.1.8 with previous version 2.1.6 dated 2019-05-31

Title: Ocean Biogeographic Information System (OBIS) Client
Description: Client for the Ocean Biogeographic Information System (<https://obis.org>).
Author: Pieter Provoost [cre, aut], Samuel Bosch [aut], Ward Appeltans [ctb], OBIS [cph]
Maintainer: Pieter Provoost <pieterprovoost@gmail.com>

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Package pmml updated to version 2.0.0 with previous version 1.5.7 dated 2019-01-25

Title: Generate PMML for Various Models
Description: The Predictive Model Markup Language (PMML) is an XML-based language which provides a way for applications to define machine learning, statistical and data mining models and to share models between PMML compliant applications. More information about the PMML industry standard and the Data Mining Group can be found at <http://www.dmg.org>. The generated PMML can be imported into any PMML consuming application, such as Zementis Predictive Analytics products, which integrate with web services, relational database systems and deploy natively on Hadoop in conjunction with Hive, Spark or Storm, as well as allow predictive analytics to be executed for IBM z Systems mainframe applications and real-time, streaming analytics platforms. The package isofor (used for anomaly detection) can be installed with devtools::install_github("Zelazny7/isofor").
Author: Dmitriy Bolotov [aut, cre], Tridivesh Jena [aut], Graham Williams [aut], Wen-Ching Lin [aut], Michael Hahsler [aut], Hemant Ishwaran [aut], Udaya B. Kogalur [aut], Rajarshi Guha [aut], Software AG [cph]
Maintainer: Dmitriy Bolotov <rpmmlsupport@softwareag.com>

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New package pinochet with initial version 0.1.0
Package: pinochet
Type: Package
Title: Data About the Victims of the Pinochet Regime, 1973-1990
Version: 0.1.0
Authors@R: c( person(given = "Danilo", family = "Freire", email = "danilofreire@gmail.com", role = c("aut", "cre")), person(given = "Lucas", family = "Mingardi", email = "lucasmingardi@gmail.com", role = "aut"), person(given = "Robert", family = "McDonnell", email = "robertmylesmcdonnell@gmail.com", role = "aut") )
Description: Packages data about the victims of the Pinochet regime as compiled by the Chilean National Commission for Truth and Reconciliation Report (1991, ISBN:9780268016463).
License: MIT + file LICENSE
URL: http://github.com/danilofreire/pinochet
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1.9000
Depends: R (>= 3.5.0)
Suggests: devtools, kableExtra, knitr, lubridate, rmarkdown, rnaturalearthdata, sf, tidyverse, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-05-31 23:15:42 UTC; politicaltheory
Author: Danilo Freire [aut, cre], Lucas Mingardi [aut], Robert McDonnell [aut]
Maintainer: Danilo Freire <danilofreire@gmail.com>
Repository: CRAN
Date/Publication: 2019-06-03 13:50:03 UTC

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New package PakPMICS2018bh with initial version 0.1.0
Package: PakPMICS2018bh
Type: Package
Title: Multiple Indicator Cluster Survey (MICS) 2017-18 Birth History of Children Questionnaire Data for Punjab, Pakistan
Version: 0.1.0
Author: Muhammad Yaseen [aut, cre] , Muhammad Usman [ctb]
Maintainer: Muhammad Yaseen <myaseen208@gmail.com>
Description: Provides data set and function for exploration of Multiple Indicator Cluster Survey (MICS) 2017-18 Household questionnaire data for Punjab, Pakistan. The results of the present survey are critically important for the purposes of SDG monitoring, as the survey produces information on 32 global SDG indicators. The data was collected from 53,840 households selected at the second stage with systematic random sampling out of a sample of 2,692 clusters selected using Probability Proportional to size sampling. Six questionnaires were used in the survey: (1) a household questionnaire to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; (2) a water quality testing questionnaire administered in three households in each cluster of the sample; (3) a questionnaire for individual women administered in each household to all women age 15-49 years; (4) a questionnaire for individual men administered in every second household to all men age 15-49 years; (5) an under-5 questionnaire, administered to mothers (or caretakers) of all children under 5 living in the household; and (6) a questionnaire for children age 5-17 years, administered to the mother (or caretaker) of one randomly selected child age 5-17 years living in the household (<http://www.mics.unicef.org/surveys>).
Depends: R (>= 3.5.0)
Imports: tibble
License: GPL-2
URL: https://github.com/myaseen208/PakPMICS2018bh, https://myaseen208.github.io/PakPMICS2018bh/
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Note: Department of Mathematics and Statistics, University of Agriculture Faisalabad, Faisalabad-Pakistan.
Suggests: testthat, R.rsp
VignetteBuilder: R.rsp
NeedsCompilation: no
Packaged: 2019-06-01 06:03:34 UTC; myaseen
Repository: CRAN
Date/Publication: 2019-06-03 14:00:03 UTC

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New package lmboot with initial version 0.0.1
Package: lmboot
Type: Package
Title: Bootstrap in Linear Models
Version: 0.0.1
Date: 2019-05-13
Authors@R: person("Megan", "Heyman", email="heyman@rose-hulman.edu", role=c("aut","cre"))
Description: Various efficient and robust bootstrap methods are implemented for linear models with least squares estimation. Functions within this package allow users to create bootstrap sampling distributions for model parameters, test hypotheses about parameters, and visualize the bootstrap sampling or null distributions. Methods implemented for linear models include the wild bootstrap by Wu (1986) <doi:10.1214/aos/1176350142>, the residual and paired bootstraps by Efron (1979, ISBN:978-1-4612-4380-9), the delete-1 jackknife by Quenouille (1956) <doi:10.2307/2332914>, and the Bayesian bootstrap by Rubin (1981) <doi:10.1214/aos/1176345338>.
Depends: R (>= 3.5.0)
Imports: evd (>= 2.3.0), stats (>= 3.6.0)
License: GPL-2
RoxygenNote: 6.1.1
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-05-31 16:54:35 UTC; heyman
Author: Megan Heyman [aut, cre]
Maintainer: Megan Heyman <heyman@rose-hulman.edu>
Repository: CRAN
Date/Publication: 2019-06-03 13:10:11 UTC

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New package gargle with initial version 0.1.3
Package: gargle
Title: Utilities for Working with Google APIs
Version: 0.1.3
Authors@R: c(person(given = "Jennifer", family = "Bryan", role = c("aut", "cre"), email = "jenny@rstudio.com", comment = c(ORCID = "0000-0002-6983-2759")), person(given = "Craig", family = "Citro", role = "aut", email = "craigcitro@google.com"), person(given = "Hadley", family = "Wickham", role = "aut", email = "hadley@rstudio.com", comment = c(ORCID = "0000-0003-4757-117X")), person(given = "Google Inc", role = "cph"), person(given = "RStudio", role = c("cph", "fnd")))
Description: Provides utilities for working with Google APIs <https://developers.google.com/apis-explorer>. This includes functions and classes for handling common credential types and for preparing, executing, and processing HTTP requests.
License: MIT + file LICENSE
URL: https://gargle.r-lib.org, https://github.com/r-lib/gargle
BugReports: https://github.com/r-lib/gargle/issues
Depends: R (>= 3.2)
Imports: fs (>= 1.3.1), glue (>= 1.3.0), httr (>= 1.4.0), jsonlite, rlang, stats, withr
Suggests: covr, knitr, rmarkdown, sodium, testthat
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-05-27 16:19:50 UTC; jenny
Author: Jennifer Bryan [aut, cre] (<https://orcid.org/0000-0002-6983-2759>), Craig Citro [aut], Hadley Wickham [aut] (<https://orcid.org/0000-0003-4757-117X>), Google Inc [cph], RStudio [cph, fnd]
Maintainer: Jennifer Bryan <jenny@rstudio.com>
Repository: CRAN
Date/Publication: 2019-06-03 13:10:16 UTC

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New package volesti with initial version 1.0.2
Package: volesti
Type: Package
License: LGPL-3
Title: Volume Approximation and Sampling of Convex Polytopes
Author: Vissarion Fisikopoulos <vissarion.fisikopoulos@gmail.com> [aut, cph, cre], Apostolos Chalkis <tolis.chal@gmail.com> [cph, aut], contributors in file inst/AUTHORS
Copyright: file inst/COPYRIGHTS
Description: Provides an R interface for 'volesti' C++ package. 'volesti' computes estimations of volume of polytopes given by a set of points or linear inequalities or Minkowski sum of segments (zonotopes). There are two algorithms for volume estimation (I.Z. Emiris and V. Fisikopoulos (2014) <arXiv:1312.2873> and B. Cousins, S. Vempala (2016) <arXiv:1409.6011>) as well as algorithms for sampling, rounding and rotating polytopes. Moreover, 'volesti' provides algorithms for estimating copulas (L. Cales, A. Chalkis, I.Z. Emiris, V. Fisikopoulos (2018) <arXiv:1803.05861>).
Version: 1.0.2
Date: 2019-05-10
Maintainer: Vissarion Fisikopoulos <vissarion.fisikopoulos@gmail.com>
Depends: Rcpp (>= 0.12.17)
Imports: methods
LinkingTo: Rcpp, RcppEigen, BH
Suggests: testthat
Encoding: UTF-8
RoxygenNote: 6.1.1
BugReports: https://github.com/GeomScale/volume_approximation/issues
NeedsCompilation: yes
Packaged: 2019-06-03 11:34:53 UTC; vissarion
Repository: CRAN
Date/Publication: 2019-06-03 12:50:03 UTC

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Package quantreg updated to version 5.40 with previous version 5.38 dated 2018-12-18

Title: Quantile Regression
Description: Estimation and inference methods for models of conditional quantiles: Linear and nonlinear parametric and non-parametric (total variation penalized) models for conditional quantiles of a univariate response and several methods for handling censored survival data. Portfolio selection methods based on expected shortfall risk are also included.
Author: Roger Koenker [cre, aut], Stephen Portnoy [ctb] (Contributions to Censored QR code), Pin Tian Ng [ctb] (Contributions to Sparse QR code), Achim Zeileis [ctb] (Contributions to dynrq code essentially identical to his dynlm code), Philip Grosjean [ctb] (Contributions to nlrq code), Brian D Ripley [trl, ctb] (Initial (2001) R port from S (to my everlasting shame -- how could I have been so slow to adopt R!) and for numerous other suggestions and useful advice)
Maintainer: Roger Koenker <rkoenker@illinois.edu>

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Package ppgmmga updated to version 1.1 with previous version 1.0.1 dated 2018-10-15

Title: Projection Pursuit Based on Gaussian Mixtures and Evolutionary Algorithms
Description: Projection Pursuit (PP) algorithm for dimension reduction based on Gaussian Mixture Models (GMMs) for density estimation using Genetic Algorithms (GAs) to maximise an approximated negentropy index.
Author: Alessio Serafini [aut, cre] (<https://orcid.org/0000-0002-8579-5695>), Luca Scrucca [aut] (<https://orcid.org/0000-0003-3826-0484>)
Maintainer: Alessio Serafini <srf.alessio@gmail.com>

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Package pomp updated to version 2.1 with previous version 1.19 dated 2018-12-13

Title: Statistical Inference for Partially Observed Markov Processes
Description: Tools for data analysis with partially observed Markov process (POMP) models (also known as stochastic dynamical systems, hidden Markov models, and nonlinear, non-Gaussian, state-space models). The package provides facilities for implementing POMP models, simulating them, and fitting them to time series data by a variety of frequentist and Bayesian methods. It is also a versatile platform for implementation of inference methods for general POMP models.
Author: Aaron A. King [aut, cre], Edward L. Ionides [aut], Carles Breto [aut], Stephen P. Ellner [ctb], Matthew J. Ferrari [ctb], Bruce E. Kendall [ctb], Michael Lavine [ctb], Dao Nguyen [ctb], Daniel C. Reuman [ctb], Helen Wearing [ctb], Simon N. Wood [ctb], Sebastian Funk [ctb], Steven G. Johnson [ctb], Eamon O'Dea [ctb]
Maintainer: Aaron A. King <kingaa@umich.edu>

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 pomp-2.1/pomp/inst/include/pomp.h         |   78 +-
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 pomp-2.1/pomp/src/dprior.c                |   94 +-
 pomp-2.1/pomp/src/dprocess.c              |  409 ++++++------
 pomp-2.1/pomp/src/euler.c                 |  437 +++++++-----
 pomp-2.1/pomp/src/gompertz.c              |   71 +-
 pomp-2.1/pomp/src/init.c                  |   24 
 pomp-2.1/pomp/src/lookup_table.c          |   55 -
 pomp-2.1/pomp/src/ou2.c                   |   43 -
 pomp-2.1/pomp/src/partrans.c              |  198 +++--
 pomp-2.1/pomp/src/pfilter.c               |   90 --
 pomp-2.1/pomp/src/pomp.h                  |   78 +-
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 pomp-2.1/pomp/src/pomp_defines.h          |   95 +-
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 pomp-2.1/pomp/src/probe.c                 |   66 -
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 pomp-2.1/pomp/src/rmeasure.c              |  309 +++++----
 pomp-2.1/pomp/src/rprior.c                |  141 ++--
 pomp-2.1/pomp/src/rprocess.c              |   82 +-
 pomp-2.1/pomp/src/simulate.c              |  226 ++----
 pomp-2.1/pomp/src/skeleton.c              |  440 +++++++++----
 pomp-2.1/pomp/src/ssa.c                   |  296 ++++----
 pomp-2.1/pomp/src/synth_lik.c             |    8 
 pomp-2.1/pomp/src/trajectory.c            |  377 +++--------
 pomp-2.1/pomp/src/transformations.c       |only
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 286 files changed, 11312 insertions(+), 8982 deletions(-)

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Package PMwR updated to version 0.11-1 with previous version 0.11-0 dated 2019-04-01

Title: Portfolio Management with R
Description: Functions and examples for 'Portfolio Management with R': backtesting investment and trading strategies, computing profit/loss and returns, analysing trades, handling lists of transactions, reporting, and more.
Author: Enrico Schumann [aut, cre] (<https://orcid.org/0000-0001-7601-6576>)
Maintainer: Enrico Schumann <es@enricoschumann.net>

Diff between PMwR versions 0.11-0 dated 2019-04-01 and 0.11-1 dated 2019-06-03

 ChangeLog                        |   32 ++-
 DESCRIPTION                      |   12 -
 MD5                              |   64 +++---
 NEWS                             |   14 +
 R/NAVseries.R                    |    2 
 R/btest.R                        |   11 -
 R/div_adjust.R                   |   33 +--
 R/drawdowns.R                    |    6 
 R/internal.R                     |   19 -
 R/position.R                     |    4 
 R/quote32.R                      |    6 
 R/rebalance.R                    |   42 ++-
 R/scale1.R                       |   26 +-
 R/streaks.R                      |    4 
 R/trades.R                       |    9 
 R/unit_prices.R                  |    4 
 R/valuation.R                    |   18 -
 build/vignette.rds               |binary
 inst/doc/An_overview_of_PMwR.pdf |binary
 inst/doc/Computing_returns.pdf   |binary
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 inst/doc/FinTeX.pdf              |binary
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 inst/doc/q32.pdf                 |binary
 inst/unitTests/runTests.R        |    4 
 inst/unitTests/test_results.txt  |   17 -
 inst/unitTests/ut_PMwR.R         |  415 ++++++++++++++++++++++-----------------
 man/PMwR-package.Rd              |    6 
 man/btest.Rd                     |    5 
 man/drawdowns.Rd                 |   11 -
 man/pl.Rd                        |   11 -
 man/rebalance.Rd                 |   22 +-
 man/streaks.Rd                   |   33 ++-
 33 files changed, 491 insertions(+), 339 deletions(-)

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New package LeMaRns with initial version 0.1.0
Package: LeMaRns
Title: Length-Based Multispecies Analysis by Numerical Simulation
Version: 0.1.0
Date: 2019-06-01
Authors@R: c(person("Michael A.", "Spence", email = "michael.spence@cefas.co.uk", role = c("aut", "cre"),comment = c(ORCID = "0000-0002-3445-7979")), person("Hayley J.", "Bannister", email = "hayley.bannister@cefas.co.uk", role = c("aut"),comment = c(ORCID = "0000-0002-2546-5168")), person("Johnathan E.", "Ball", email = "johnathan.ball@cefas.co.uk", role = c("aut")), person("Paul J.", "Dolder", email = "paul.dolder@cefas.co.uk", role = c("aut"),comment = c(ORCID = "0000-0002-4179-712X")), person("Robert B.", "Thorpe", email = "robert.thorpe@cefas.co.uk", role = c("aut"),comment = c(ORCID = "0000-0001-8193-6932")),person("Christopher A.", "Griffiths", email = "chris.griffiths@cefas.co.uk", role = c("ctb")))
Description: Set up, run and explore the outputs of the Length-based Multispecies model (LeMans; Hall et al. 2006 <doi:10.1139/f06-039>), focused on the marine environment.
Depends: R (>= 3.5.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
LinkingTo: Rcpp, RcppArmadillo
Imports: Rcpp, abind, methods
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Collate: 'NS_par.R' 'RcppExports.R' 'calc_M1.R' 'calc_Q.R' 'calc_growth.R' 'calc_indicators.R' 'calc_mature.R' 'param_setup.R' 'run_LeMans.R' 'calc_output.R' 'calc_phi.R' 'calc_prefs.R' 'calc_ration_growthfac.R' 'calc_recruits.R' 'calc_suit_vect.R' 'get_Catch.R' 'get_SSB.R' 'get_indicators.R' 'other.R' 'plot_SSB.R' 'plot_indicators.R'
NeedsCompilation: yes
Packaged: 2019-05-31 13:11:50 UTC; HB04
Author: Michael A. Spence [aut, cre] (<https://orcid.org/0000-0002-3445-7979>), Hayley J. Bannister [aut] (<https://orcid.org/0000-0002-2546-5168>), Johnathan E. Ball [aut], Paul J. Dolder [aut] (<https://orcid.org/0000-0002-4179-712X>), Robert B. Thorpe [aut] (<https://orcid.org/0000-0001-8193-6932>), Christopher A. Griffiths [ctb]
Maintainer: Michael A. Spence <michael.spence@cefas.co.uk>
Repository: CRAN
Date/Publication: 2019-06-03 12:40:09 UTC

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New package justifier with initial version 0.1.0
Package: justifier
Title: Human and Machine-Readable Justifications and Justified Decisions Based on 'YAML'
Version: 0.1.0
Authors@R: person(given = "Gjalt-Jorn Ygram", family = "Peters", role = c("aut", "cre"), email = "gjalt-jorn@behaviorchange.eu")
Maintainer: Gjalt-Jorn Ygram Peters <gjalt-jorn@behaviorchange.eu>
Description: Leverages the 'yum' package to implement a 'YAML' ('YAML Ain't Markup Language', a human friendly standard for data serialization; see <https:yaml.org>) standard for documenting justifications, such as for decisions taken during the planning, execution and analysis of a study or during the development of a behavior change intervention as illustrated by Marques & Peters (2019) <doi:10.17605/osf.io/ndxha>. These justifications are both human- and machine-readable, facilitating efficient extraction and organisation.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
URL: https://r-packages.gitlab.io/justifier
BugReports: https://gitlab.com/r-packages/justifier/issues
Suggests: covr, knitr, rmarkdown, testthat
Imports: data.tree (>= 0.7.8), DiagrammeR (>= 1.0.0), purrr (>= 0.3.0), ufs (>= 0.2.0), yum (>= 0.0.1)
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-05-31 10:52:20 UTC; gjalt
Author: Gjalt-Jorn Ygram Peters [aut, cre]
Repository: CRAN
Date/Publication: 2019-06-03 12:30:18 UTC

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New package GuessCompx with initial version 1.0.3
Package: GuessCompx
Type: Package
Title: Empirically Estimates Algorithm Complexity
Version: 1.0.3
Author: Marc Agenis <marc.agenis@gmail.com> and Neeraj Bokde <neerajdhanraj@gmail.com>
Maintainer: Marc Agenis <marc.agenis@gmail.com>
Description: Make an empirical guess on the time and memory complexities of an algorithm or a function. Tests multiple, increasing size random samples of your data and tries to fit various complexity functions o(n), o(n2), o(log(n)), etc. Based on best fit, it predicts the full computation time on your whole dataset. Results are plotted with 'ggplot2'.
BugReports: https://github.com/agenis/GuessCompx/issues
URL: https://github.com/agenis/GuessCompx
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: dplyr, reshape2, ggplot2, lubridate, boot
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-05-31 12:02:07 UTC; Neeraj
Repository: CRAN
Date/Publication: 2019-06-03 12:50:34 UTC

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New package grangers with initial version 0.1.0
Package: grangers
Title: Inference on Granger-Causality in the Frequency Domain
Version: 0.1.0
Author: Matteo Farne' <matteo.farne2@unibo.it>, Angela Montanari <angela.montanari@unibo.it>
Maintainer: Matteo Farne' <matteo.farne2@unibo.it>
Description: Contains five functions performing the calculation of unconditional and conditional Granger-causality spectra, bootstrap inference on both, and inference on the difference between them via the bootstrap approach of Farne' and Montanari, 2018 <arXiv:1803.00374>.
Depends: R (>= 3.5)
License: GPL (>= 2)
URL: https://github.com/MatFar88/grangers
Imports: vars, tseries
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-05-30 23:14:59 UTC; Calif
Repository: CRAN
Date/Publication: 2019-06-03 12:50:13 UTC

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Package generalhoslem updated to version 1.3.4 with previous version 1.3.3 dated 2018-09-20

Title: Goodness of Fit Tests for Logistic Regression Models
Description: Functions to assess the goodness of fit of binary, multinomial and ordinal logistic models. Included are the Hosmer-Lemeshow tests (binary, multinomial and ordinal) and the Lipsitz and Pulkstenis-Robinson tests (ordinal).
Author: Matthew Jay [aut, cre]
Maintainer: Matthew Jay <matthew.jay.15@ucl.ac.uk>

Diff between generalhoslem versions 1.3.3 dated 2018-09-20 and 1.3.4 dated 2019-06-03

 DESCRIPTION                  |   12 +--
 MD5                          |   18 ++---
 R/lipsitz.test.R             |   84 ++++++++++++-----------
 R/logitgof.R                 |   31 +++++---
 R/pulkrob.chisq.R            |  149 +++++++++++++++++++----------------------
 R/pulkrob.deviance.R         |  153 ++++++++++++++++++++-----------------------
 build/partial.rdb            |binary
 man/generalhoslem-package.Rd |    3 
 man/lipsitz.test.Rd          |    2 
 man/logitgof.Rd              |    5 +
 10 files changed, 232 insertions(+), 225 deletions(-)

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New package gen2stage with initial version 1.0
Package: gen2stage
Type: Package
Title: Generalized Two-Stage Designs for Phase II Single-Arm Studies
Version: 1.0
Depends: R (>= 2.0.0), graphics, stats, clinfun
Author: Seongho Kim
Maintainer: Seongho Kim <biostatistician.kim@gmail.com>
Description: One can find single-stage and two-stage designs for a phase II single-arm study with either efficacy or safety/toxicity endpoints as described in Kim and Wong (2019) <doi:10.29220/CSAM.2019.26.2.163>.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2019-05-31 14:38:22 UTC; kimse
Repository: CRAN
Date/Publication: 2019-06-03 12:50:22 UTC

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Package EGAnet updated to version 0.5 with previous version 0.4 dated 2019-05-02

Title: Exploratory Graph Analysis - A Framework for Estimating the Number of Dimensions in Multivariate Data Using Network Psychometrics
Description: An implementation of the Exploratory Graph Analysis (EGA) framework for dimensionality assessment. EGA is part of a new area called network psychometrics that focuses on the estimation of undirected network models in psychological datasets. EGA estimates the number of dimensions or factors using graphical lasso or Triangulated Maximally Filtered Graph (TMFG) and a weighted network community analysis. A bootstrap method for verifying the stability of the estimation is also available. The fit of the structure suggested by EGA can be verified using confirmatory factor analysis and a direct way to convert the EGA structure to a confirmatory factor model is also implemented. Documentation and examples are available. Golino, H. F., & Epskamp, S. (2017) <doi:10.1371/journal.pone.0174035>. Golino, H. F., & Demetriou, A. (2017) <doi:10.1016/j.intell.2017.02.007> Golino, H., Shi, D., Garrido, L. E., Christensen, A. P., Nieto, M. D., Sadana, R., & Thiyagarajan, J. A. (2018) <doi:10.31234/osf.io/gzcre>. Christensen, A. P. & Golino, H.F. (2019) <doi:10.31234/osf.io/9deay>.
Author: Hudson Golino [aut, cre], Alexander Christensen [aut], Maria Dolores Nieto [ctb], Luis Eduardo Garrido [ctb]
Maintainer: Hudson Golino <hfg9s@virginia.edu>

Diff between EGAnet versions 0.4 dated 2019-05-02 and 0.5 dated 2019-06-03

 DESCRIPTION       |   34 ++++----
 MD5               |   18 ++--
 NAMESPACE         |    6 +
 R/EGA.R           |  225 ++++++++++++++++++++++++++++++++++++++++++++++--------
 R/bootEGA.R       |    2 
 R/entropyFit.R    |  212 +++++++++++++++++++++++---------------------------
 R/vn.entropy.R    |only
 man/EGA.Rd        |   18 ++--
 man/bootEGA.Rd    |    2 
 man/entropyFit.Rd |   18 ----
 man/vn.entropy.Rd |only
 11 files changed, 345 insertions(+), 190 deletions(-)

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New package cpsurvsim with initial version 1.1.0
Package: cpsurvsim
Type: Package
Title: Simulating Survival Data from Change-Point Hazard Distributions
Version: 1.1.0
Date: 2019-05-07
Author: Camille Hochheimer [aut, cre]
Authors@R: person("Camille", "Hochheimer", email = "hochheimercj@vcu.edu", role = c("aut", "cre"))
Maintainer: Camille Hochheimer <hochheimercj@vcu.edu>
Description: Simulates time-to-event data with type I right censoring using two methods: the inverse CDF method and our proposed memoryless method. The latter method takes advantage of the memoryless property of survival and simulates a separate distribution between change-points. We include two parametric distributions: exponential and Weibull. Inverse CDF method draws on the work of Rainer Walke (2010), <https://www.demogr.mpg.de/papers/technicalreports/tr-2010-003.pdf>.
Depends: R (>= 3.5.0)
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Imports: plyr (>= 1.8.0), stats, Hmisc, knitr (>= 1.21)
Suggests: rmarkdown
RoxygenNote: 6.1.1
VignetteBuilder: knitr
URL: http://github.com/camillejo/cpsurvsim
BugReports: http://github.com/camillejo/cpsurvsim/issues
NeedsCompilation: no
Packaged: 2019-05-31 15:46:32 UTC; Camille
Repository: CRAN
Date/Publication: 2019-06-03 13:00:07 UTC

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Permanent link

New package utile.tools with initial version 0.1.2
Package: utile.tools
Version: 0.1.2
Date: 2019-05-29
Title: Tools for Summarizing Data for Publication
Description: A variety of tools for preparing and summarizing data for publication purposes. Function verbs include "tabulate" for creating usable tabulated data from models, "paste" for generating human-readable statistics from a variety of summarizable data types, "calc" for reliably calculating differences between data points, and "test" for conducting simple statistical tests which return human-readable results.
Authors@R: c(person('Eric', 'Finnesgard', email = 'finnesgard.eric@mayo.edu', role = c('aut', 'cre')))
License: LGPL (>= 2)
Encoding: UTF-8
LazyData: TRUE
Depends: R (>= 3.4.0)
Imports: tibble, dplyr, lubridate, rlang, glue, purrr, stringr, survival
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-05-30 11:46:10 UTC; m130239
Author: Eric Finnesgard [aut, cre]
Maintainer: Eric Finnesgard <finnesgard.eric@mayo.edu>
Repository: CRAN
Date/Publication: 2019-06-03 11:50:03 UTC

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Package uCAREChemSuiteCLI updated to version 0.2.0 with previous version 0.1.2 dated 2018-06-07

Title: Resistome Predicter
Description: This suite of packages is developed to predicts resistome for unknown chemical compounds. It utilizes two algorithms viz. deterministic model and stochastic model (manuscript under preparation) for the prediction of drug class. Once the drug class is predicted, the resistome profile of Escherichia coli and Pseudomonas aeruginosa for the drug class is fetched from the database.
Author: Saurav Bhaskar Saha and Pramod Wasudeo Ramteke
Maintainer: Saurav Bhaskar Saha <saurav.saha@shiats.edu.in>

Diff between uCAREChemSuiteCLI versions 0.1.2 dated 2018-06-07 and 0.2.0 dated 2019-06-03

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Package spectral updated to version 1.3 with previous version 1.0.1 dated 2016-09-15

Title: Common Methods of Spectral Data Analysis
Description: Fourier and Hilbert transforms are utilized to perform several types of spectral analysis on the supplied data. Fragmented and irregularly spaced data can be processed in terms of Lomb-Scargle method. Both, FFT as well as LOMB methods take multivariate data. A user friendly interface helps to interpret the results.
Author: Martin Seilmayer
Maintainer: Martin Seilmayer <m.seilmayer@hzdr.de>

Diff between spectral versions 1.0.1 dated 2016-09-15 and 1.3 dated 2019-06-03

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New package mSimCC with initial version 0.0.1
Package: mSimCC
Type: Package
Title: Micro Simulation Model for Cervical Cancer Prevention
Version: 0.0.1
Date: 2019-05-23
Author: David Moriña, Pedro Puig and Mireia Diaz
Maintainer: David Moriña Soler <david.morina@uab.cat>
Description: Micro simulation model to reproduce natural history of cervical cancer and cost-effectiveness evaluation of prevention strategies. See Georgalis L, de Sanjose S, Esnaola M, Bosch F X, Diaz M (2016) <doi:10.1097/CEJ.0000000000000202> for more details.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.1.1), parallel, doParallel, foreach
NeedsCompilation: yes
Packaged: 2019-06-03 05:29:47 UTC; dmorinya
Repository: CRAN
Date/Publication: 2019-06-03 11:20:03 UTC

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Package gap.datasets updated to version 0.0.4 with previous version 0.0.2 dated 2017-11-27

Title: Datasets for 'gap'
Description: Datasets associated with the 'gap' package. Currently, it includes an example data for regional association plot (CDKN), an example data for a genomewide association meta-analysis (OPG), Manhattan plots with (hr1420, mhtdata) and without (w4) gene annotations.
Author: Jing Hua Zhao with suggestions from R-Core
Maintainer: Jing Hua Zhao <jinghuazhao@hotmail.com>

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Package climextRemes updated to version 0.2.1 with previous version 0.2.0 dated 2018-02-06

Title: Tools for Analyzing Climate Extremes
Description: Functions for fitting GEV and POT (via point process fitting) models for extremes in climate data, providing return values, return probabilities, and return periods for stationary and nonstationary models. Also provides differences in return values and differences in log return probabilities for contrasts of covariate values. Functions for estimating risk ratios for event attribution analyses, including uncertainty. Under the hood, many of the functions use functions from 'extRemes', including for fitting the statistical models. Details are given in Paciorek, Stone, and Wehner (2018) <doi:10.1016/j.wace.2018.01.002>.
Author: Christopher Paciorek [aut, cre], Harinarayan Krishnan [ctb]
Maintainer: Christopher Paciorek <paciorek@stat.berkeley.edu>

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New package bayesreg with initial version 1.1
Package: bayesreg
Type: Package
Title: Bayesian Regression Models with Global-Local Shrinkage Priors
Version: 1.1
Date: 2019-06-03
Author: Daniel F. Schmidt [aut, cph, cre], Enes Makalic [aut, cph]
Maintainer: Daniel F. Schmidt <daniel.schmidt@monash.edu>
Description: Fits linear or logistic regression model using Bayesian global-local shrinkage prior hierarchies as described in Polson and Scott (2010) <doi:10.1093/acprof:oso/9780199694587.003.0017>. Handles ridge, lasso, horseshoe and horseshoe+ regression with logistic, Gaussian, Laplace or Student-t distributed targets using the algorithms summarized in Makalic and Schmidt (2016) <arXiv:1611.06649>.
License: GPL (>= 3)
Imports: stats (>= 3.0), pgdraw (>= 1.0)
Authors@R: c( person("Daniel F. Schmidt", email="daniel.schmidt@monash.edu", role = c("aut","cph","cre")), person("Enes Makalic", email="emakalic@unimelb.edu.au", role=c("aut","cph")) )
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-06-03 06:32:33 UTC; Daniel
Repository: CRAN
Date/Publication: 2019-06-03 11:30:19 UTC

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Package stima updated to version 1.2.1 with previous version 1.2 dated 2018-08-29

Title: Simultaneous Threshold Interaction Modeling Algorithm
Description: Regression trunk model estimation proposed by Dusseldorp and Meulman (2004) <doi:10.1007/bf02295641> and Dusseldorp, Conversano, Van Os (2010) <doi:10.1198/jcgs.2010.06089>, integrating a regression tree and a multiple regression model.
Author: Elise Dusseldorp [aut, cre, cph], Claudio Conversano [aut, cph], Cor Ninaber [ctb], Kristof Meers [ctb], Peter Neufeglise [trl], Juan Claramunt [ctb]
Maintainer: Elise Dusseldorp <elise.dusseldorp@fsw.leidenuniv.nl>

Diff between stima versions 1.2 dated 2018-08-29 and 1.2.1 dated 2019-06-03

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Package popsom updated to version 4.2.1 with previous version 4.2 dated 2017-06-01

Title: Functions for Constructing and Evaluating Self-Organizing Maps
Description: State of the art functions for constructing and evaluating self-organizing maps.
Author: Lutz Hamel [aut, cre], Benjamin Ott [aut], Gregory Breard [aut], Robert Tatoian [aut], Vishakh Gopu [aut]
Maintainer: Lutz Hamel <hamel@cs.uri.edu>

Diff between popsom versions 4.2 dated 2017-06-01 and 4.2.1 dated 2019-06-03

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Package sensmediation updated to version 0.3.0 with previous version 0.2.0 dated 2018-11-14

Title: Parametric Estimation and Sensitivity Analysis of Direct and Indirect Effects
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.
Author: Anita Lindmark <anita.lindmark@umu.se>
Maintainer: Anita Lindmark <anita.lindmark@umu.se>

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Package AeRobiology updated to version 2.0.1 with previous version 2.0 dated 2019-04-15

Title: A Computational Tool for Aerobiological Data
Description: Different tools for managing databases of airborne particles, elaborating the main calculations and visualization of results. In a first step, data are checked using tools for quality control and all missing gaps are completed. Then, the main parameters of the pollen season are calculated and represented graphically. Multiple graphical tools are available: pollen calendars, phenological plots, time series, tendencies, interactive plots, abundance plots...
Author: Jesus Rojo <Jesus.Rojo@uclm.es>, Antonio Picornell <picornell@uma.es>, Jose Oteros <OterosJose@gmail.com>
Maintainer: "Jose Oteros" <OterosJose@gmail.com>

Diff between AeRobiology versions 2.0 dated 2019-04-15 and 2.0.1 dated 2019-06-03

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Package binneR (with last version 2.0.11) was removed from CRAN

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

2019-03-19 2.0.11
2019-02-08 2.0.10
2019-01-16 2.0.7
2019-01-08 2.0.6
2018-12-12 2.0.5
2018-03-01 1.1.1

Permanent link
Package peakPantheR (with last version 1.2.0) was removed from CRAN

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

2018-07-10 1.2.0

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Package Miso (with last version 0.2.1) was removed from CRAN

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2019-03-09 0.2.1
2018-09-27 0.1.5
2018-08-30 0.1.4
2018-08-22 0.1.3
2018-01-17 0.1.1

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Package MSeasyTkGUI (with last version 5.3.3) was removed from CRAN

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2013-03-21 5.3.3
2012-08-16 5.3.1
2012-05-04 5.3
2011-09-19 5.2

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Package HiResTEC (with last version 0.54) was removed from CRAN

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2018-08-07 0.54
2018-05-07 0.52

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Package cliqueMS (with last version 0.3.1) was removed from CRAN

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2019-04-25 0.3.1
2019-01-30 0.3.0
2019-01-10 0.2.4
2018-11-15 0.2.3
2018-05-14 0.2.1

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Package LipidMS (with last version 1.0.0) was removed from CRAN

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2018-10-15 1.0.0
2018-07-12 0.1.0

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2018-05-15 2.0.3

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Package RAMClustR (with last version 1.0.6) was removed from CRAN

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2019-04-23 1.0.6
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2019-05-14 1.2.16
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2016-07-22 1.2.13

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Package MSeasy (with last version 5.3.3) was removed from CRAN

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2013-03-20 5.3.3
2012-08-16 5.3.1
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2011-09-19 5.2

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Package tsibble updated to version 0.8.1 with previous version 0.8.0 dated 2019-04-28

Title: Tidy Temporal Data Frames and Tools
Description: Provides a 'tbl_ts' class (the 'tsibble') to store and manage temporal data in a data-centric format, which is built on top of the 'tibble'. The 'tsibble' aims at easily manipulating and analysing temporal data, including counting and filling in time gaps, aggregate over calendar periods, performing rolling window calculations, and etc.
Author: Earo Wang [aut, cre] (<https://orcid.org/0000-0001-6448-5260>), Di Cook [aut, ths] (<https://orcid.org/0000-0002-3813-7155>), Rob Hyndman [aut, ths] (<https://orcid.org/0000-0002-2140-5352>), Mitchell O'Hara-Wild [aut] (<https://orcid.org/0000-0001-6729-7695>)
Maintainer: Earo Wang <earo.wang@gmail.com>

Diff between tsibble versions 0.8.0 dated 2019-04-28 and 0.8.1 dated 2019-06-03

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More information about tsibble at CRAN
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Package RCarb updated to version 0.1.3 with previous version 0.1.2 dated 2018-12-09

Title: Dose Rate Modelling of Carbonate-Rich Samples
Description: Translation of the 'MATLAB' program 'Carb' (Nathan and Mauz 2008 <DOI:10.1016/j.radmeas.2007.12.012>; Mauz and Hoffmann 2014) for dose rate modelling for carbonate-rich samples in the context of trapped charged dating (e.g., luminescence dating) applications.
Author: Sebastian Kreutzer [aut, trl, cre, dtc] (<https://orcid.org/0000-0002-0734-2199>), Roger P. Nathan [aut, cph], Barbara Mauz [aut, cph] (<https://orcid.org/0000-0003-1504-333X>)
Maintainer: Sebastian Kreutzer <sebastian.kreutzer@u-bordeaux-montaigne.fr>

Diff between RCarb versions 0.1.2 dated 2018-12-09 and 0.1.3 dated 2019-06-03

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More information about RCarb at CRAN
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