Thu, 10 Oct 2019

Package rocTree updated to version 1.1.0 with previous version 1.0.0 dated 2019-03-24

Title: Receiver Operating Characteristic (ROC)-Guided Classification and Survival Tree
Description: Receiver Operating Characteristic (ROC)-guided survival trees and ensemble algorithms are implemented, providing a unified framework for tree-structured analysis with censored survival outcomes. A time-invariant partition scheme on the survivor population was considered to incorporate time-dependent covariates. Motivated by ideas of randomized tests, generalized time-dependent ROC curves were used to evaluate the performance of survival trees and establish the optimality of the target hazard/survival function. The optimality of the target hazard function motivates us to use a weighted average of the time-dependent area under the curve (AUC) on a set of time points to evaluate the prediction performance of survival trees and to guide splitting and pruning. A detailed description of the implemented methods can be found in Sun et al. (2019) <arXiv:1809.05627>.
Author: Yifei Sun [aut], Mei-Cheng Wang [aut], Sy Han Chiou [aut, cre]
Maintainer: Sy Han Chiou <schiou@utdallas.edu>

Diff between rocTree versions 1.0.0 dated 2019-03-24 and 1.1.0 dated 2019-10-10

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Package MachineShop updated to version 1.6.0 with previous version 1.5.0 dated 2019-08-01

Title: Machine Learning Models and Tools
Description: Meta-package for statistical and machine learning with a unified interface for model fitting, prediction, performance assessment, and presentation of results. Approaches for model fitting and prediction of numerical, categorical, or censored time-to-event outcomes include traditional regression models, regularization methods, tree-based methods, support vector machines, neural networks, ensembles, data preprocessing, filtering, and model tuning and selection. Performance metrics are provided for model assessment and can be estimated with independent test sets, split sampling, cross-validation, or bootstrap resampling. Resample estimation can be executed in parallel for faster processing and nested in cases of model tuning and selection. Modeling results can be summarized with descriptive statistics; calibration curves; variable importance; partial dependence plots; confusion matrices; and ROC, lift, and other performance curves.
Author: Brian J Smith [aut, cre]
Maintainer: Brian J Smith <brian-j-smith@uiowa.edu>

Diff between MachineShop versions 1.5.0 dated 2019-08-01 and 1.6.0 dated 2019-10-10

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Package HMR updated to version 1.0.0 with previous version 0.4.2 dated 2017-04-03

Title: Flux Estimation with Static Chamber Data
Description: Statistical analysis of static chamber concentration data for trace gas flux estimation.
Author: Asger R. Pedersen <asger@clin.au.dk>
Maintainer: Asger R. Pedersen <asger@clin.au.dk>

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Package bwimage updated to version 1.2 with previous version 1.0 dated 2019-06-28

Title: Describe Image Patterns in Natural Structures
Description: A computational tool to describe patterns in black and white images from natural structures. 'bwimage' implemented functions for exceptionally broad subject. For instance, 'bwimage' provide examples that range from calculation of canopy openness, description of patterns in vertical vegetation structure, to patterns in bird nest structure.
Author: Carlos Biagolini-Jr.
Maintainer: Carlos Biagolini-Jr.<c.biagolini@gmail.com>

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New package BivRegBLS with initial version 1.1.1
Package: BivRegBLS
Type: Package
Title: Tolerance Interval and EIV Regression - Method Comparison Studies
Version: 1.1.1
Date: 2019-10-10
Authors@R: c(person(given="Bernard G",family="Francq",email="BivRegBLS@gmail.com",role=c("cre","aut")),person(given="Marion",family="Berger",email="marion.berger@sanofi.com",role=c("aut")),person(given="Christophe",family="Agut",role=c("ctb")), person(given="Guy",family="Mathieu",role=c("ctb")), person(given="Armand",family="Berges",role=c("ctb")), person(given="Franck",family="Pellissier",role=c("ctb")), person(given="Veronique",family="Onado",role=c("ctb")))
Maintainer: Bernard G Francq <BivRegBLS@gmail.com>
Description: Assess the agreement in method comparison studies by tolerance intervals and errors-in-variables (EIV) regressions. The Ordinary Least Square regressions (OLSv and OLSh), the Deming Regression (DR), and the (Correlated)-Bivariate Least Square regressions (BLS and CBLS) can be used with unreplicated or replicated data. The BLS() and CBLS() are the two main functions to estimate a regression line, while XY.plot() and MD.plot() are the two main graphical functions to display, respectively an (X,Y) plot or (M,D) plot with the BLS or CBLS results. Four hyperbolic statistical intervals are provided: the Confidence Interval (CI), the Confidence Bands (CB), the Prediction Interval and the Generalized prediction Interval. Assuming no proportional bias, the (M,D) plot (Band-Altman plot) may be simplified by calculating univariate tolerance intervals (beta-expectation (type I) or beta-gamma content (type II)). Major updates from last version 1.0.0 are: title shortened, include the new functions BLS.fit() and CBLS.fit() as shortcut of the, respectively, functions BLS() and CBLS(). References: B.G. Francq, B. Govaerts (2016) <doi:10.1002/sim.6872>, B.G. Francq, B. Govaerts (2014) <doi:10.1016/j.chemolab.2014.03.006>, B.G. Francq, B. Govaerts (2014) <http://publications-sfds.fr/index.php/J-SFdS/article/view/262>, B.G. Francq (2013), PhD Thesis, UCLouvain, Errors-in-variables regressions to assess equivalence in method comparison studies, <https://dial.uclouvain.be/pr/boreal/object/boreal%3A135862/datastream/PDF_01/view>.
Depends: R (>= 3.1.0), ellipse
License: AGPL-3
RoxygenNote: 6.1.1
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-10-10 21:02:59 UTC; Bernard
Author: Bernard G Francq [cre, aut], Marion Berger [aut], Christophe Agut [ctb], Guy Mathieu [ctb], Armand Berges [ctb], Franck Pellissier [ctb], Veronique Onado [ctb]
Repository: CRAN
Date/Publication: 2019-10-10 22:40:06 UTC

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Package bacistool updated to version 0.9.9 with previous version 0.9.8 dated 2018-08-24

Title: Bayesian Classification and Information Sharing (BaCIS) Tool for the Design of Multi-Group Phase II Clinical Trials
Description: Provides the design of multi-group phase II clinical trials with binary outcomes using the hierarchical Bayesian classification and information sharing (BaCIS) model. Subgroups are classified into two clusters on the basis of their outcomes mimicking the hypothesis testing framework. Subsequently, information sharing takes place within subgroups in the same cluster, rather than across all subgroups. This method can be applied to the design and analysis of multi-group clinical trials with binary outcomes. Reference: Nan Chen and J. Jack Lee (2019) <doi:10.1002/bimj.201700275>.
Author: Nan Chen and J. Jack Lee
Maintainer: Nan Chen <nchen2@mdanderson.org>

Diff between bacistool versions 0.9.8 dated 2018-08-24 and 0.9.9 dated 2019-10-10

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Package popRange (with last version 1.1.3) was removed from CRAN

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

2014-10-13 1.1.3
2014-10-04 1.1.2
2014-04-07 1.1.1
2014-03-20 1.1
2014-03-12 1.0

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Package xgxr updated to version 1.0.4 with previous version 1.0.3 dated 2019-09-28

Title: Exploratory Graphics for Pharmacometrics
Description: Supports a structured approach for exploring PKPD data <https://opensource.nibr.com/xgx>. It also contains helper functions for enabling the modeler to follow best R practices (by appending the program name, figure name location, and draft status to each plot). In addition, it enables the modeler to follow best graphical practices (by providing a theme that reduces chart ink, and by providing time-scale, log-scale, and reverse-log-transform-scale functions for more readable axes). Finally, it provides some data checking and summarizing functions for rapidly exploring pharmacokinetics and pharmacodynamics (PKPD) datasets.
Author: Andrew Stein [aut, cre], Alison Margolskee [aut], Fariba Khanshan [aut], Konstantin Krismer [aut] (<https://orcid.org/0000-0001-8994-3416>), Matthew Fidler [ctb] (<https://orcid.org/0000-0001-8538-6691>), Novartis Pharma AG [cph, fnd]
Maintainer: Andrew Stein <andy.stein@gmail.com>

Diff between xgxr versions 1.0.3 dated 2019-09-28 and 1.0.4 dated 2019-10-10

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New package SwimmeR with initial version 0.1.0.0
Package: SwimmeR
Title: Formatting and Conversions for Swimming Times
Version: 0.1.0.0
Authors@R: person(given = "Greg", family = "Pilgrim", role = c("aut", "cre"), email = "gpilgrim2670@gmail.com")
Description: There are two goals for 'SwimmeR' as presently constructed. First, it converts swimming times (performances) between the computationally useful format of seconds, reported to the 100ths place (eg 95.37) and the conventional reporting format (1:35.37) used in the swimming community. Secondly 'SwimmeR' converts times between the various pool sizes used in competitive swimming, namely 50m length (LCM), 25m length (SCM) and 25y length (SCY).
License: MIT + file LICENSE
Imports: purrr, dplyr, stringr, tibble, utils
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: testthat (>= 2.1.0)
NeedsCompilation: no
Packaged: 2019-10-09 12:12:00 UTC; gpilgrim
Author: Greg Pilgrim [aut, cre]
Maintainer: Greg Pilgrim <gpilgrim2670@gmail.com>
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2019-10-10 14:40:03 UTC

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Package wppExplorer updated to version 2.3-2 with previous version 2.1-1 dated 2017-08-18

Title: Explorer of World Population Prospects
Description: Explore data in the 'wpp2019' (or 2017, 2015, ...) package using a 'shiny' interface.
Author: Hana Sevcikova <hanas@uw.edu>
Maintainer: Hana Sevcikova <hanas@uw.edu>

Diff between wppExplorer versions 2.1-1 dated 2017-08-18 and 2.3-2 dated 2019-10-10

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New package simTargetCov with initial version 1.0
Package: simTargetCov
Type: Package
Title: Data Transformation or Simulation with Empirical Covariance Matrix
Version: 1.0
Date: 2019-10-02
Author: Anthony Christidis <anthony.christidis@stat.ubc.ca>, Stefan Van Aelst <stefan.vanaelst@kuleuven.be>, Ruben Zamar <ruben@stat.ubc.ca>
Maintainer: Anthony Christidis <anthony.christidis@stat.ubc.ca>
Description: Transforms or simulates data with a target empirical covariance matrix supplied by the user. The method to obtain the data with the target empirical covariance matrix is described in Section 5.1 of Christidis, Van Aelst and Zamar (2019) <arXiv:1812.05678>.
License: GPL (>= 2)
Biarch: true
Imports: MASS, stats
Depends:
RoxygenNote: 6.1.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-10-07 19:10:24 UTC; antho
Repository: CRAN
Date/Publication: 2019-10-10 13:30:02 UTC

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New package MatchThem with initial version 0.8.1
Package: MatchThem
Title: Matching Multiply Imputed Datasets
Description: Provides the necessary tools for the pre-processing technique of matching in multiply imputed datasets, to improve the robustness and transparency of deriving causal inferences from studying these datasets. This package includes functions to perform propensity score matching within or across the imputed datasets as well as to estimate weights (including inverse propensity score weights) of observations, to analyze each matched or weighted datasets using parametric or non-parametric statistical models, and to combine the obtained results from these models according to Rubin’s rules. Please see the package repository <https://github.com/FarhadPishgar/MatchThem> for details.
Version: 0.8.1
Authors@R: c(person("Farhad", "Pishgar", role = c("aut","cre"), email = "Farhad.Pishgar@Gmail.com"), person("Clémence", "Leyrat", role = "ctb", email = "Clemence.Leyrat@lshtm.ac.uk"))
Maintainer: Farhad Pishgar <Farhad.Pishgar@Gmail.com>
Depends: graphics, MatchIt, methods, mice, WeightIt, R (>= 3.5.0)
Imports: stats
Suggests: Amelia, cobalt
URL: https://github.com/FarhadPishgar/MatchThem
BugReports: https://github.com/FarhadPishgar/MatchThem/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-09 14:08:05 UTC; Farhad
Author: Farhad Pishgar [aut, cre], Clémence Leyrat [ctb]
Repository: CRAN
Date/Publication: 2019-10-10 13:40:02 UTC

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Package EBPRS updated to version 1.2.0 with previous version 1.1.5 dated 2019-08-07

Title: Derive Polygenic Risk Score Based on Emprical Bayes Theory
Description: EB-PRS is a novel method that leverages information for effect sizes across all the markers to improve the prediction accuracy. No parameter tuning is needed in the method, and no external information is needed. This R-package provides the calculation of polygenic risk scores from the given training summary statistics and testing data. We can use EB-PRS to extract main information, estimate Empirical Bayes parameters, derive polygenic risk scores for each individual in testing data, and evaluate the PRS according to AUC and predictive r2.
Author: Shuang Song [aut, cre], Wei Jiang [aut], Lin Hou [aut] and Hongyu Zhao [aut]
Maintainer: Shuang Song <song-s19@mails.tsinghua.edu.cn>

Diff between EBPRS versions 1.1.5 dated 2019-08-07 and 1.2.0 dated 2019-10-10

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New package dodgr with initial version 0.2.5
Package: dodgr
Title: Distances on Directed Graphs
Version: 0.2.5
Authors@R: c( person("Mark", "Padgham", email="mark.padgham@email.com", role=c("aut", "cre")), person("Andreas", "Petutschnig", role="aut"), person("Robin", "Lovelace", role="ctb"), person("Andrew", "Smith", role="ctb"), person("Malcolm", "Morgan", role="ctb"), person("Shane", "Saunders", role="cph", comment="Original author of included code for priority heaps"))
Description: Distances on dual-weighted directed graphs using priority-queue shortest paths (Padgham (2019) <doi:10.32866/6945>). Weighted directed graphs have weights from A to B which may differ from those from B to A. Dual-weighted directed graphs have two sets of such weights. A canonical example is a street network to be used for routing in which routes are calculated by weighting distances according to the type of way and mode of transport, yet lengths of routes must be calculated from direct distances.
Depends: R (>= 3.5.0)
License: GPL-3
Imports: callr, digest, igraph, magrittr, methods, osmdata, Rcpp (>= 0.12.6), RcppParallel
Suggests: dplyr, geodist, ggplot2, igraphdata, jsonlite, knitr, purrr, rbenchmark, RColorBrewer, rmarkdown, roxygen2, scales, sf, testthat, tidygraph
LinkingTo: Rcpp, RcppParallel
SystemRequirements: C++11, GNU make
VignetteBuilder: knitr
NeedsCompilation: yes
Encoding: UTF-8
LazyData: true
URL: https://github.com/ATFutures/dodgr
BugReports: https://github.com/ATFutures/dodgr/issues
RoxygenNote: 6.1.1
Packaged: 2019-10-06 19:54:34 UTC; markus
Author: Mark Padgham [aut, cre], Andreas Petutschnig [aut], Robin Lovelace [ctb], Andrew Smith [ctb], Malcolm Morgan [ctb], Shane Saunders [cph] (Original author of included code for priority heaps)
Maintainer: Mark Padgham <mark.padgham@email.com>
Repository: CRAN
Date/Publication: 2019-10-10 14:00:02 UTC

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Package collections updated to version 0.2.1 with previous version 0.2.0 dated 2019-10-02

Title: High Performance Container Data Types
Description: Provides high performance container data types such as Queue, Stack, Deque, Dict and OrderedDict. Benchmarks <https://randy3k.github.io/collections/articles/benchmark.html> have shown that these containers are asymptotically more efficient than those offered by other packages.
Author: Randy Lai [aut, cre], Andrea Mazzoleni [cph] (tommy hash table library)
Maintainer: Randy Lai <randy.cs.lai@gmail.com>

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Package stars updated to version 0.4-0 with previous version 0.3-1 dated 2019-04-23

Title: Spatiotemporal Arrays, Raster and Vector Data Cubes
Description: Reading, manipulating, writing and plotting spatiotemporal arrays (raster and vector data cubes) in 'R', using 'GDAL' bindings provided by 'sf', and 'NetCDF' bindings by 'ncmeta' and 'RNetCDF'.
Author: Edzer Pebesma [aut, cre] (<https://orcid.org/0000-0001-8049-7069>), Michael Sumner [ctb] (<https://orcid.org/0000-0002-2471-7511>), Etienne Racine [ctb], Adriano Fantini [ctb], David Blodgett [ctb]
Maintainer: Edzer Pebesma <edzer.pebesma@uni-muenster.de>

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Package shiny updated to version 1.4.0 with previous version 1.3.2 dated 2019-04-22

Title: Web Application Framework for R
Description: Makes it incredibly easy to build interactive web applications with R. Automatic "reactive" binding between inputs and outputs and extensive prebuilt widgets make it possible to build beautiful, responsive, and powerful applications with minimal effort.
Author: Winston Chang [aut, cre], Joe Cheng [aut], JJ Allaire [aut], Yihui Xie [aut], Jonathan McPherson [aut], RStudio [cph], jQuery Foundation [cph] (jQuery library and jQuery UI library), jQuery contributors [ctb, cph] (jQuery library; authors listed in inst/www/shared/jquery-AUTHORS.txt), jQuery UI contributors [ctb, cph] (jQuery UI library; authors listed in inst/www/shared/jqueryui/AUTHORS.txt), Mark Otto [ctb] (Bootstrap library), Jacob Thornton [ctb] (Bootstrap library), Bootstrap contributors [ctb] (Bootstrap library), Twitter, Inc [cph] (Bootstrap library), Alexander Farkas [ctb, cph] (html5shiv library), Scott Jehl [ctb, cph] (Respond.js library), Stefan Petre [ctb, cph] (Bootstrap-datepicker library), Andrew Rowls [ctb, cph] (Bootstrap-datepicker library), Dave Gandy [ctb, cph] (Font-Awesome font), Brian Reavis [ctb, cph] (selectize.js library), Kristopher Michael Kowal [ctb, cph] (es5-shim library), es5-shim contributors [ctb, cph] (es5-shim library), Denis Ineshin [ctb, cph] (ion.rangeSlider library), Sami Samhuri [ctb, cph] (Javascript strftime library), SpryMedia Limited [ctb, cph] (DataTables library), John Fraser [ctb, cph] (showdown.js library), John Gruber [ctb, cph] (showdown.js library), Ivan Sagalaev [ctb, cph] (highlight.js library), R Core Team [ctb, cph] (tar implementation from R)
Maintainer: Winston Chang <winston@rstudio.com>

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More information about shiny at CRAN
Permanent link

Package metaSEM updated to version 1.2.3 with previous version 1.2.2 dated 2019-05-29

Title: Meta-Analysis using Structural Equation Modeling
Description: A collection of functions for conducting meta-analysis using a structural equation modeling (SEM) approach via the 'OpenMx' and 'lavaan' packages. It also implements various procedures to perform meta-analytic structural equation modeling on the correlation and covariance matrices.
Author: Mike Cheung [aut, cre] (<https://orcid.org/0000-0003-0113-0758>)
Maintainer: Mike Cheung <mikewlcheung@nus.edu.sg>

Diff between metaSEM versions 1.2.2 dated 2019-05-29 and 1.2.3 dated 2019-10-10

 DESCRIPTION                     |   13 
 MD5                             |  135 +-
 NAMESPACE                       |    1 
 NEWS                            |   15 
 R/as.mxMatrix.R                 |    3 
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 R/summary.R                     |  228 ++--
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 README.md                       |    4 
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Package mapmisc updated to version 1.7.4 with previous version 1.7.2 dated 2018-04-09

Title: Utilities for Producing Maps
Description: A minimal, light-weight set of tools for producing nice looking maps in R, with support for map projections.
Author: Patrick Brown <patrick.brown@utoronto.ca>
Maintainer: Patrick Brown <patrick.brown@utoronto.ca>

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Package interpret updated to version 0.1.21 with previous version 0.1.20 dated 2019-10-07

Title: Fit Interpretable Models and Explain Blackbox Machine Learning
Description: Machine Learning package for training interpretable models and explaining blackbox systems. Historically, the most intelligible models were not very accurate, and the most accurate models were not intelligible. Microsoft Research has developed an algorithm called the Explainable Boosting Machine (EBM) which has both high accuracy and intelligibility. EBM uses machine learning techniques like bagging and boosting to breathe new life into traditional GAMs (Generalized Additive Models). This makes them as accurate as random forests and gradient boosted trees, and also enhances their intelligibility and editability. Details on the EBM algorithm can be found in the paper by Rich Caruana, Yin Lou, Johannes Gehrke, Paul Koch, Marc Sturm, and Noemie Elhadad (2015, <doi:10.1145/2783258.2788613>).
Author: Samuel Jenkins [aut], Harsha Nori [aut], Paul Koch [aut], Rich Caruana [aut, cre], Microsoft Corporation [cph]
Maintainer: Rich Caruana <interpretml@outlook.com>

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Package protolite updated to version 2.0 with previous version 1.9 dated 2019-07-02

Title: Highly Optimized Protocol Buffer Serializers
Description: Pure C++ implementations for reading and writing several common data formats based on Google protocol-buffers. Currently supports 'rexp.proto' for serialized R objects, 'geobuf.proto' for binary geojson, and 'mvt.proto' for vector tiles. This package uses the auto-generated C++ code by protobuf-compiler, hence the entire serialization is optimized at compile time. The 'RProtoBuf' package on the other hand uses the protobuf runtime library to provide a general- purpose toolkit for reading and writing arbitrary protocol-buffer data in R.
Author: Jeroen Ooms
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

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New package MEclustnet with initial version 1.2.2
Package: MEclustnet
Title: Fit the Mixture of Experts Latent Position Cluster Model to Network Data
Version: 1.2.2
Authors@R: c(person(given = "Isobel Claire", family = "Gormley", role = c("aut", "cre"), email = "claire.gormley@ucd.ie"), person(given = "Thomas Brendan", family = "Murphy", role = c("aut"), email = "brendan.murphy@ucd.ie"))
Description: Functions to facilitate model-based clustering of nodes in a network in a mixture of experts setting, which incorporates covariate information on the nodes in the modelling process. Isobel Claire Gormley and Thomas Brendan Murphy (2010) <doi:10.1016/j.stamet.2010.01.002>.
Imports: MASS, mvtnorm, nnet, ellipse, latentnet, vegan, e1071
Depends: R (>= 2.10)
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-10-10 08:50:57 UTC; clairegormley
Author: Isobel Claire Gormley [aut, cre], Thomas Brendan Murphy [aut]
Maintainer: Isobel Claire Gormley <claire.gormley@ucd.ie>
Repository: CRAN
Date/Publication: 2019-10-10 11:50:05 UTC

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Package iCiteR updated to version 0.2.0 with previous version 0.1.0 dated 2019-07-04

Title: A Minimal Wrapper Around NIH's 'iCite' API
Description: A minimal wrapper around the NIH's 'iCite' API (<https://icite.od.nih.gov/api>). Given a vector of pubmed IDs, this package returns a dataframe of the information yielded by the 'iCite' API. The primary metrics yielded by 'iCite' are measurements of a paper's scientific influence and translational potential, but the API also returns other meta-data from the paper, including author names, publication journal, publication year, paper title, doi, and a number of other citation metrics.
Author: Travis Riddle [aut, cre]
Maintainer: Travis Riddle <travis.riddle@nih.gov>

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Package comat updated to version 0.7.0 with previous version 0.3.0 dated 2019-08-25

Title: Creates Co-Occurrence Matrices of Spatial Data
Description: Builds co-occurrence matrices based on spatial raster data. It includes creation of weighted co-occurrence matrices (wecoma) and integrated co-occurrence matrices (incoma; Vadivel et al. (2007) <doi:10.1016/j.patrec.2007.01.004>).
Author: Jakub Nowosad [aut, cre] (<https://orcid.org/0000-0002-1057-3721>), Maximillian H.K. Hesselbarth [ctb] (Co-author of underlying C++ code for get_class_index_map(), get_unique_values(), and rcpp_get_coma() functions), Marco Sciaini [ctb] (Co-author of underlying C++ code for get_class_index_map(), get_unique_values(), and rcpp_get_coma() functions), Sebastian Hanss [ctb] (Co-author of underlying C++ code for get_class_index_map(), get_unique_values(), and rcpp_get_coma() functions)
Maintainer: Jakub Nowosad <nowosad.jakub@gmail.com>

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Package catlearn updated to version 0.7.1 with previous version 0.6.2 dated 2019-03-18

Title: Formal Psychological Models of Categorization and Learning
Description: Formal psychological models of categorization and learning, independently-replicated data sets against which to test them, and simulation archives.
Author: Andy Wills, Lenard Dome, Charlotte Edmunds, Garrett Honke, Angus Inkster, René Schlegelmilch, Stuart Spicer
Maintainer: Andy Wills <andy@willslab.co.uk>

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Package ShortForm updated to version 0.4.4 with previous version 0.4.3 dated 2019-08-07

Title: Automatic Short Form Creation
Description: Performs automatic creation of short forms of scales with an ant colony optimization algorithm and a Tabu search. As implemented in the package, the ant colony algorithm randomly selects items to build a model of a specified length, then updates the probability of item selection according to the fit of the best model within each set of searches. The algorithm continues until the same items are selected by multiple ants a given number of times in a row. On the other hand, the Tabu search changes one parameter at a time to be either free, constrained, or fixed while keeping track of the changes made and putting changes that result in worse fit in a "tabu" list so that the algorithm does not revisit them for some number of searches. See Leite, Huang, & Marcoulides (2008) <doi:10.1080/00273170802285743> for an applied example of the ant colony algorithm, and Marcoulides & Falk (2018) <doi:10.1080/10705511.2017.1409074> for an applied example of the Tabu search.
Author: Anthony Raborn [aut, cre], Walter Leite [aut]
Maintainer: Anthony Raborn <anthony.w.raborn@gmail.com>

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Package MoonFinder updated to version 1.0.2 with previous version 1.0.1 dated 2019-02-22

Title: Identify Moonlighting ncRNAs
Description: Identify moonlighting non-coding RNAs at the genome level based on the functional annotation and interactome data of ncRNAs and proteins. MoonFinder provides an extensive framework for the detection of protein modules and establishment of RNA-module associations.
Author: Lixin Cheng
Maintainer: Lixin Cheng <easonlcheng@gmail.com>

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Package gitgadget updated to version 0.5.2 with previous version 0.4.4 dated 2019-08-30

Title: Rstudio Addin for Version Control and Assignment Management using Git
Description: An Rstudio addin for version control that allows users to clone repositories, create and delete branches, and sync forks on GitHub, GitLab, etc. Furthermore, the addin uses the GitLab API to allow instructors to create forks and merge requests for all students/teams with one click of a button.
Author: Vincent Nijs [aut, cre], Sanjiv Erat [aut]
Maintainer: Vincent Nijs <vnijs@ucsd.edu>

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