Tue, 24 Sep 2019

Package raster updated to version 3.0-7 with previous version 3.0-2 dated 2019-08-22

Title: Geographic Data Analysis and Modeling
Description: Reading, writing, manipulating, analyzing and modeling of gridded spatial data. The package implements basic and high-level functions. Processing of very large files is supported. There is a also support for vector data operations such as intersections. See the manual and tutorials on <https://rspatial.org/> to get started.
Author: Robert J. Hijmans [cre, aut] (<https://orcid.org/0000-0001-5872-2872>), Jacob van Etten [ctb], Michael Sumner [ctb], Joe Cheng [ctb], Andrew Bevan [ctb], Roger Bivand [ctb], Lorenzo Busetto [ctb], Mort Canty [ctb], David Forrest [ctb], Aniruddha Ghosh [ctb], Duncan Golicher [ctb], Josh Gray [ctb], Jonathan A. Greenberg [ctb], Paul Hiemstra [ctb], Institute for Mathematics Applied Geosciences [cph], Charles Karney [ctb], Matteo Mattiuzzi [ctb], Steven Mosher [ctb], Jakub Nowosad [ctb], Edzer Pebesma [ctb], Oscar Perpinan Lamigueiro [ctb], Etienne B. Racine [ctb], Barry Rowlingson [ctb], Ashton Shortridge [ctb], Bill Venables [ctb], Rafael Wueest [ctb]
Maintainer: Robert J. Hijmans <r.hijmans@gmail.com>

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Package FunChisq updated to version 2.4.9.1 with previous version 2.4.8-1 dated 2019-09-08

Title: Model-Free Functional Chi-Squared and Exact Tests
Description: Statistical hypothesis testing methods for inferring model-free functional dependency using asymptotic chi-squared or exact distributions. Functional test statistics are asymmetric and functionally optimal, unique from other related statistics. Tests in this package reveal evidence for causality based on the causality-by-functionality principle. They include asymptotic functional chi-squared tests ('Zhang & Song' 2013) <arXiv:1311.2707> and an exact functional test ('Zhong & Song' 2019) <doi:10.1109/TCBB.2018.2809743>. The normalized functional chi-squared test was used by Best Performer 'NMSUSongLab' in HPN-DREAM (DREAM8) Breast Cancer Network Inference Challenges ('Hill et al' 2016) <doi:10.1038/nmeth.3773>. A function index ('Zhong & Song' in press) ('Kumar et al' 2018) <doi:10.1109/BIBM.2018.8621502> derived from the functional test statistic offers a new effect size measure for the strength of functional dependency, a better alternative to conditional entropy in many aspects. For continuous data, these tests offer an advantage over regression analysis when a parametric functional form cannot be assumed; for categorical data, they provide a novel means to assess directional dependency not possible with symmetrical Pearson's chi-squared or Fisher's exact tests.
Author: Yang Zhang [aut], Hua Zhong [aut] (<https://orcid.org/0000-0003-1962-2603>), Hien Nguyen [aut] (<https://orcid.org/0000-0002-7237-4752>), Ruby Sharma [aut], Sajal Kumar [aut], Joe Song [aut, cre] (<https://orcid.org/0000-0002-6883-6547>)
Maintainer: Joe Song <joemsong@cs.nmsu.edu>

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New package dbarts with initial version 0.9-13
Package: dbarts
Version: 0.9-13
Date: 2019-09-22
Title: Discrete Bayesian Additive Regression Trees Sampler
Authors@R: c( person("Vincent", "Dorie", role = c("aut", "cre"), email = "vdorie@gmail.com", comment = c(ORCID = "0000-0002-9576-3064")), person("Hugh", "Chipman", role = "aut", email = "hugh.chipman@gmail.com"), person("Robert", "McCulloch", role = "aut", email = "robert.mcculloch1@gmail.com"), person("Armon", "Dadgar", role = "ctb", comment = "adaptive radix tree"), person("R Core Team", role = "ctb", comment = "basis of RNG"), person("Guido U", "Draheim", role = "ctb", comment = "ax_check_compile_flag.m4"), person("Maarten", "Bosmans", role = "ctb", comment = "ax_check_compile_flag.m4"), person("Christophe", "Tournayre", role = "ctb", comment = "ax_compiler_ext.m4, ax_ext.m4"), person("Michael", "Petch", role = "ctb", comment = "ax_compiler_ext.m4, ax_ext.m4, ax_gcc_x86_avx_xgetbv.m4, ax_gcc_x86_cpuid.m4"), person("Rafael", "de Lucena Valle", role = "ctb", comment = "ax_compiler_ext.m4, ax_ext.m4"), person("Steven G.", "Johnson", role = "ctb", comment = c("ax_compiler_vendor.m4, ax_gcc_x86_cpuid.m4, ax_pthread.m4", ORCID = "0000-0001-7327-4967")), person("Matteo", "Frigo", role = "ctb", comment = "ax_compiler_vendor.m4, ax_gcc_x86_cpuid.m4"), person("John", "Zaitseff", role = "ctb", comment = "ax_compiler_vendor.m4"), person("Todd", "Veldhuizen", role = "ctb", comment = "ax_cxx_namespace_std.m4"), person("Luc", "Maisonobe", role = "ctb", comment = "ax_cxx_namespace_std.m4"), person("Scott", "Pakin", role = "ctb", comment = c("ax_func_posix_memalign.m4", ORCID = "0000-0002-5220-1985")), person("Daniel", "Richard G.", role = "ctb", comment = "ax_pthread.m4"))
Depends: R (>= 3.1-0)
Imports: stats, methods, graphics, parallel
Suggests: testthat (>= 0.9-0)
Description: Fits Bayesian additive regression trees (BART; Chipman, George, and McCulloch (2010) <doi:10.1214/09-AOAS285>) while allowing the updating of predictors or response so that BART can be incorporated as a conditional model in a Gibbs/MH sampler. Also serves as a drop-in replacement for package 'BayesTree'.
License: GPL (>= 2)
NeedsCompilation: yes
Biarch: yes
URL: https://github.com/vdorie/dbarts
BugReports: https://github.com/vdorie/dbarts/issues
Packaged: 2019-09-22 16:03:02 UTC; vdorie
Author: Vincent Dorie [aut, cre] (<https://orcid.org/0000-0002-9576-3064>), Hugh Chipman [aut], Robert McCulloch [aut], Armon Dadgar [ctb] (adaptive radix tree), R Core Team [ctb] (basis of RNG), Guido U Draheim [ctb] (ax_check_compile_flag.m4), Maarten Bosmans [ctb] (ax_check_compile_flag.m4), Christophe Tournayre [ctb] (ax_compiler_ext.m4, ax_ext.m4), Michael Petch [ctb] (ax_compiler_ext.m4, ax_ext.m4, ax_gcc_x86_avx_xgetbv.m4, ax_gcc_x86_cpuid.m4), Rafael de Lucena Valle [ctb] (ax_compiler_ext.m4, ax_ext.m4), Steven G. Johnson [ctb] (ax_compiler_vendor.m4, ax_gcc_x86_cpuid.m4, ax_pthread.m4, <https://orcid.org/0000-0001-7327-4967>), Matteo Frigo [ctb] (ax_compiler_vendor.m4, ax_gcc_x86_cpuid.m4), John Zaitseff [ctb] (ax_compiler_vendor.m4), Todd Veldhuizen [ctb] (ax_cxx_namespace_std.m4), Luc Maisonobe [ctb] (ax_cxx_namespace_std.m4), Scott Pakin [ctb] (ax_func_posix_memalign.m4, <https://orcid.org/0000-0002-5220-1985>), Daniel Richard G. [ctb] (ax_pthread.m4)
Maintainer: Vincent Dorie <vdorie@gmail.com>
Repository: CRAN
Date/Publication: 2019-09-24 15:40:12 UTC

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Package QPot (with last version 1.5) was removed from CRAN

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

2019-04-06 1.5
2019-03-27 1.4
2016-04-03 1.1
2015-10-23 1.0

Permanent link
Package spectralGraphTopology (with last version 0.1.2) was removed from CRAN

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

2019-09-22 0.1.2

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Package BMTME (with last version 1.0.9) was removed from CRAN

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

2019-09-24 1.0.9

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Package genderizeR (with last version 2.1.1) was removed from CRAN

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

2019-08-04 2.1.1

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Package sjmisc updated to version 2.8.2 with previous version 2.8.1 dated 2019-06-17

Title: Data and Variable Transformation Functions
Description: Collection of miscellaneous utility functions, supporting data transformation tasks like recoding, dichotomizing or grouping variables, setting and replacing missing values. The data transformation functions also support labelled data, and all integrate seamlessly into a 'tidyverse'-workflow.
Author: Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>), Iago Giné-Vázquez [ctb], Alexander Bartel [ctb] (<https://orcid.org/0000-0002-1280-6138>)
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

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Package devtools updated to version 2.2.1 with previous version 2.2.0 dated 2019-09-07

Title: Tools to Make Developing R Packages Easier
Description: Collection of package development tools.
Author: Hadley Wickham [aut], Jim Hester [aut, cre], Winston Chang [aut], RStudio [cph], R Core team [ctb] (Some namespace and vignette code extracted from base R)
Maintainer: Jim Hester <jim.hester@rstudio.com>

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Package socialmixr updated to version 0.1.5 with previous version 0.1.4 dated 2019-07-24

Title: Social Mixing Matrices for Infectious Disease Modelling
Description: Provides methods for sampling contact matrices from diary data for use in infectious disease modelling, as discussed in Mossong et al. (2008) <doi:10.1371/journal.pmed.0050074>.
Author: Sebastian Funk [aut, cre]
Maintainer: Sebastian Funk <sebastian.funk@lshtm.ac.uk>

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Package curl updated to version 4.2 with previous version 4.1 dated 2019-09-16

Title: A Modern and Flexible Web Client for R
Description: The curl() and curl_download() functions provide highly configurable drop-in replacements for base url() and download.file() with better performance, support for encryption (https, ftps), gzip compression, authentication, and other 'libcurl' goodies. The core of the package implements a framework for performing fully customized requests where data can be processed either in memory, on disk, or streaming via the callback or connection interfaces. Some knowledge of 'libcurl' is recommended; for a more-user-friendly web client see the 'httr' package which builds on this package with http specific tools and logic.
Author: Jeroen Ooms [aut, cre] (<https://orcid.org/0000-0002-4035-0289>), Hadley Wickham [ctb], RStudio [cph]
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

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Package DELTD updated to version 1.3.1 with previous version 1.2.1 dated 2019-09-23

Title: Density Estimation by Life Time Distributions
Description: It plots densities by using asymmetrical kernels which belong to life time distributions and calculate its related MSE. For details see Chen (2000), Jin and Kawczak (2003) and Salha et al. (2014) <doi:10.12988/pms.2014.4616>.
Author: Javaria Ahmad Khan, Atif Akbar.
Maintainer: Javaria Ahmad Khan <jakhan0@yahoo.com>

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New package spate with initial version 1.6
Package: spate
Title: Spatio-Temporal Modeling of Large Data Using a Spectral SPDE Approach
Version: 1.6
Date: 2019-09-17
Author: Fabio Sigrist, Hans R. Kuensch, Werner A. Stahel
Maintainer: Fabio Sigrist <fabiosigrist@gmail.com>
Depends: R (>= 2.10), mvtnorm, truncnorm
SystemRequirements: fftw3 (>= 3.1.2)
Description: Functionality for spatio-temporal modeling of large data sets is provided. A Gaussian process in space and time is defined through a stochastic partial differential equation (SPDE). The SPDE is solved in the spectral space, and after discretizing in time and space, a linear Gaussian state space model is obtained. When doing inference, the main computational difficulty consists in evaluating the likelihood and in sampling from the full conditional of the spectral coefficients, or equivalently, the latent space-time process. In comparison to the traditional approach of using a spatio-temporal covariance function, the spectral SPDE approach is computationally advantageous. See Sigrist, Kuensch, and Stahel (2015) <doi:10.1111/rssb.12061> for more information on the methodology. This package aims at providing tools for two different modeling approaches. First, the SPDE based spatio-temporal model can be used as a component in a customized hierarchical Bayesian model (HBM). The functions of the package then provide parameterizations of the process part of the model as well as computationally efficient algorithms needed for doing inference with the HBM. Alternatively, the adaptive MCMC algorithm implemented in the package can be used as an algorithm for doing inference without any additional modeling. The MCMC algorithm supports data that follow a Gaussian or a censored distribution with point mass at zero. Covariates can be included in the model through a regression term.
License: GPL-2
LazyData: true
NeedsCompilation: yes
Packaged: 2019-09-24 08:29:12 UTC; fabiosigrist
Repository: CRAN
Date/Publication: 2019-09-24 10:10:03 UTC

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Package shinyAce updated to version 0.4.1 with previous version 0.4.0 dated 2019-07-09

Title: Ace Editor Bindings for Shiny
Description: Ace editor bindings to enable a rich text editing environment within Shiny.
Author: Vincent Nijs [aut, cre], Forest Fang [aut], Trestle Technology, LLC [aut], Jeff Allen [aut], Institut de Radioprotection et de Surete Nucleaire [cph], Ajax.org B.V. [ctb, cph] (Ace)
Maintainer: Vincent Nijs <radiant@rady.ucsd.edu>

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Package rMVP updated to version 0.99.16 with previous version 0.99.15 dated 2019-08-30

Title: Memory-Efficient, Visualize-Enhanced, Parallel-Accelerated GWAS Tool
Description: A memory-efficient, visualize-enhanced, parallel-accelerated Genome-Wide Association Study (GWAS) tool. It can (1) effectively process large data, (2) rapidly evaluate population structure, (3) efficiently estimate variance components several algorithms, (4) implement parallel-accelerated association tests of markers three methods, (5) globally efficient design on GWAS process computing, (6) enhance visualization of related information. 'rMVP' contains three models GLM (Alkes Price (2006) <DOI:10.1038/ng1847>), MLM (Jianming Yu (2006) <DOI:10.1038/ng1702>) and FarmCPU (Xiaolei Liu (2016) <doi:10.1371/journal.pgen.1005767>); variance components estimation methods EMMAX (Hyunmin Kang (2008) <DOI:10.1534/genetics.107.080101>;), FaSTLMM (method: Christoph Lippert (2011) <DOI:10.1038/nmeth.1681>, R implementation from 'GAPIT2': You Tang and Xiaolei Liu (2016) <DOI:10.1371/journal.pone.0107684> and 'SUPER': Qishan Wang and Feng Tian (2014) <DOI:10.1371/journal.pone.0107684>), and HE regression (Xiang Zhou (2017) <DOI:10.1214/17-AOAS1052>).
Author: Lilin Yin [aut], Haohao Zhang [aut], Zhenshuang Tang [aut], Jingya Xu [aut], Dong Yin [aut], Zhiwu Zhang [aut], Xiaohui Yuan [aut], Mengjin Zhu [aut], Shuhong Zhao [aut], Xinyun Li [aut], Qishan Wang [ctb], Feng Tian [ctb], Hyunmin Kang [ctb], Xiang Zhou [ctb], Xiaolei Liu [cre, aut, cph]
Maintainer: Xiaolei Liu <xiaoleiliu@mail.hzau.edu.cn>

Diff between rMVP versions 0.99.15 dated 2019-08-30 and 0.99.16 dated 2019-09-24

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More information about rMVP at CRAN
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Package otrimle updated to version 1.3 with previous version 1.2 dated 2019-09-23

Title: Robust Model-Based Clustering
Description: Performs robust cluster analysis allowing for outliers and noise that cannot be fitted by any cluster. The data are modelled by a mixture of Gaussian distributions and a noise component, which is an improper uniform distribution covering the whole Euclidean space. Parameters are estimated by (pseudo) maximum likelihood. This is fitted by a EM-type algorithm. See Coretto and Hennig (2016) <doi:10.1080/01621459.2015.1100996>, and Coretto and Hennig (2017) <http://jmlr.org/papers/v18/16-382.html>.
Author: Pietro Coretto [aut, cre], Christian Hennig [aut]
Maintainer: Pietro Coretto <pcoretto@unisa.it>

Diff between otrimle versions 1.2 dated 2019-09-23 and 1.3 dated 2019-09-24

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Package microbenchmark updated to version 1.4-7 with previous version 1.4-6 dated 2018-10-18

Title: Accurate Timing Functions
Description: Provides infrastructure to accurately measure and compare the execution time of R expressions.
Author: Olaf Mersmann [aut], Claudia Beleites [ctb], Rainer Hurling [ctb], Ari Friedman [ctb], Joshua M. Ulrich [cre]
Maintainer: Joshua M. Ulrich <josh.m.ulrich@gmail.com>

Diff between microbenchmark versions 1.4-6 dated 2018-10-18 and 1.4-7 dated 2019-09-24

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New package BMTME with initial version 1.0.9
Package: BMTME
Title: Bayesian Multi-Trait Multi-Environment for Genomic Selection Analysis
Version: 1.0.9
Date: 2019-9-23
Language: en-US
Authors@R: c(person("Francisco Javier", "Luna-Vazquez", email = "frahik@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-5370-7152")), person("Fernando H.", "Toledo", role = "aut"), person("Osval Antonio", "Montesinos-Lopez", email= "oamontes1@ucol.mx", role = "aut", comment = c(ORCID = "0000-0002-3973-6547")), person("Abelardo", "Montesinos-Lopez", role = "aut"), person("Jose", "Crossa", role = "aut", comment = c(ORCID = "0000-0001-9429-5855")))
Maintainer: Francisco Javier Luna-Vazquez <frahik@gmail.com>
Description: Genomic selection and prediction models with the capacity to use multiple traits and environments, through ready-to-use Bayesian models. It consists a group of functions that help to create regression models for some genomic models proposed by Montesinos-López, et al. (2016) <doi:10.1534/g3.116.032359> also in Montesinos-López et al. (2018) <doi:10.1534/g3.118.200728> and Montesinos-López et al. (2018) <doi:10.2134/agronj2018.06.0362>.
Depends: R (>= 3.5)
License: LGPL-3
Encoding: UTF-8
LazyData: true
Type: Package
RoxygenNote: 6.1.1
URL: https://github.com/frahik/BMTME
BugReports: https://github.com/frahik/BMTME/issues/new
NeedsCompilation: yes
Collate: BME.R BMTME.R BMTME_Package.R BMORS.R BMORSEnv.R cholesky.R datasets.R detectCore.R RandomPartition.R RcppExports.R utils.R
Imports: BGLR, doSNOW, dplyr, foreach, matrixcalc, mvtnorm, progress, snow, tidyr
LinkingTo: Rcpp, RcppArmadillo
SystemRequirements: C++11
Suggests: covr, testthat,
Packaged: 2019-09-24 05:21:56 UTC; frahik
Author: Francisco Javier Luna-Vazquez [aut, cre] (<https://orcid.org/0000-0002-5370-7152>), Fernando H. Toledo [aut], Osval Antonio Montesinos-Lopez [aut] (<https://orcid.org/0000-0002-3973-6547>), Abelardo Montesinos-Lopez [aut], Jose Crossa [aut] (<https://orcid.org/0000-0001-9429-5855>)
Repository: CRAN
Date/Publication: 2019-09-24 10:10:17 UTC

More information about BMTME at CRAN
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Package DLMtool updated to version 5.4.0 with previous version 5.3.1 dated 2019-04-29

Title: Data-Limited Methods Toolkit
Description: Development, simulation testing, and implementation of management procedures for data-limited fisheries (see Carruthers & Hordyk (2018) <doi:10.1111/2041-210X.13081>).
Author: Tom Carruthers [aut, cre], Adrian Hordyk [aut], M. Bryan [ctb], HF. Geremont [ctb], C. Grandin [ctb], W. Harford [ctb], Q. Huynh [ctb], C. Walters [ctb]
Maintainer: Tom Carruthers <t.carruthers@fisheries.ubc.ca>

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Package SVN updated to version 1.0.1 with previous version 1.0 dated 2019-04-10

Title: Statistically Validated Networks
Description: Determines networks of significant synchronization between the discrete states of nodes; see Tumminello et al <doi:10.1371/journal.pone.0017994>.
Author: Damien Challet
Maintainer: Damien Challet <damien.challet@gmail.com>

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Package suddengains updated to version 0.3.1 with previous version 0.3.0 dated 2019-08-20

Title: Identify Sudden Gains in Longitudinal Data
Description: Identify sudden gains based on the three criteria outlined by Tang and DeRubeis (1999) <doi:10.1037/0022-006X.67.6.894> to a selection of repeated measures. Sudden losses, defined as the opposite of sudden gains can also be identified. Two different datasets can be created, one including all sudden gains/losses and one including one selected sudden gain/loss for each case. It can extract scores around sudden gains/losses. It can plot the average change around sudden gains/losses and trajectories of individual cases.
Author: Milan Wiedemann [aut, cre] (<https://orcid.org/0000-0003-1991-282X>), Graham M Thew [ctb] (<https://orcid.org/0000-0003-2851-1315>), Richard Stott [ctb] (<https://orcid.org/0000-0003-2533-5504>), Anke Ehlers [ctb, ths] (<https://orcid.org/0000-0002-8742-0192>)
Maintainer: Milan Wiedemann <milan.wiedemann@gmail.com>

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Package cubeview updated to version 0.2.0 with previous version 0.1.0 dated 2019-03-15

Title: View 3D Raster Cubes Interactively
Description: Creates a 3D data cube view of a RasterStack/Brick, typically a collection/array of RasterLayers (along z-axis) with the same geographical extent (x and y dimensions) and resolution, provided by package 'raster'. Slices through each dimension (x/y/z), freely adjustable in location, are mapped to the visible sides of the cube. The cube can be freely rotated. Zooming and panning can be used to focus on different areas of the cube.
Author: Tim Appelhans [cre, aut], Stefan Woellauer [aut], three.js authors [ctb, cph] (three.js library)
Maintainer: Tim Appelhans <tim.appelhans@gmail.com>

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Package auditor updated to version 1.1.0 with previous version 1.0.0 dated 2019-08-31

Title: Model Audit - Verification, Validation, and Error Analysis
Description: Provides an easy to use unified interface for creating validation plots for any model. The 'auditor' helps to avoid repetitive work consisting of writing code needed to create residual plots. This visualizations allow to asses and compare the goodness of fit, performance, and similarity of models.
Author: Alicja Gosiewska [aut, cre] (<https://orcid.org/0000-0001-6563-5742>), Przemyslaw Biecek [aut, ths] (<https://orcid.org/0000-0001-8423-1823>), Hubert Baniecki [aut], Tomasz Mikołajczyk [aut], Michal Burdukiewicz [ctb], Szymon Maksymiuk [ctb]
Maintainer: Alicja Gosiewska <alicjagosiewska@gmail.com>

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Package PAFit updated to version 1.0.1.4 with previous version 1.0.1.2 dated 2019-04-11

Title: Generative Mechanism Estimation in Temporal Complex Networks
Description: Statistical methods for estimating preferential attachment and node fitness generative mechanisms in temporal complex networks are provided. Thong Pham et al. (2015) <doi:10.1371/journal.pone.0137796>. Thong Pham et al. (2016) <doi:10.1038/srep32558>.
Author: Thong Pham, Paul Sheridan, Hidetoshi Shimodaira
Maintainer: Thong Pham <thongphamthe@gmail.com>

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Package SMUT updated to version 1.1 with previous version 1.0.1 dated 2019-04-08

Title: Multi-SNP Mediation Intersection-Union Test
Description: Testing the mediation effect of multiple SNPs on an outcome through a mediator.
Author: Wujuan Zhong
Maintainer: Wujuan Zhong <zhongwujuan@gmail.com>

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Package fourPNO updated to version 1.1.0 with previous version 1.0.5 dated 2019-01-22

Title: Bayesian 4 Parameter Item Response Model
Description: Estimate Barton & Lord's (1981) <doi:10.1002/j.2333-8504.1981.tb01255.x> four parameter IRT model with lower and upper asymptotes using Bayesian formulation described by Culpepper (2016) <doi:10.1007/s11336-015-9477-6>.
Author: Steven Andrew Culpepper [aut, cre, cph] (<https://orcid.org/0000-0003-4226-6176>)
Maintainer: Steven Andrew Culpepper <sculpepp@illinois.edu>

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