Fri, 18 May 2018

Package dbscan updated to version 1.1-2 with previous version 1.1-0 dated 2017-03-19

Title: Density Based Clustering of Applications with Noise (DBSCAN) and Related Algorithms
Description: A fast reimplementation of several density-based algorithms of the DBSCAN family for spatial data. Includes the DBSCAN (density-based spatial clustering of applications with noise) and OPTICS (ordering points to identify the clustering structure) clustering algorithms HDBSCAN (hierarchical DBSCAN) and the LOF (local outlier factor) algorithm. The implementations use the kd-tree data structure (from library ANN) for faster k-nearest neighbor search. An R interface to fast kNN and fixed-radius NN search is also provided.
Author: Michael Hahsler [aut, cre, cph], Matthew Piekenbrock [aut, cph], Sunil Arya [ctb, cph], David Mount [ctb, cph]
Maintainer: Michael Hahsler <mhahsler@lyle.smu.edu>

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Package Rcpp updated to version 0.12.17 with previous version 0.12.16 dated 2018-03-13

Title: Seamless R and C++ Integration
Description: The 'Rcpp' package provides R functions as well as C++ classes which offer a seamless integration of R and C++. Many R data types and objects can be mapped back and forth to C++ equivalents which facilitates both writing of new code as well as easier integration of third-party libraries. Documentation about 'Rcpp' is provided by several vignettes included in this package, via the 'Rcpp Gallery' site at <http://gallery.rcpp.org>, the paper by Eddelbuettel and Francois (2011, <doi:10.18637/jss.v040.i08>), the book by Eddelbuettel (2013, <doi:10.1007/978-1-4614-6868-4>) and the paper by Eddelbuettel and Balamuta (2018, <doi:10.1080/00031305.2017.1375990>); see 'citation("Rcpp")' for details.
Author: Dirk Eddelbuettel, Romain Francois, JJ Allaire, Kevin Ushey, Qiang Kou, Nathan Russell, Douglas Bates and John Chambers
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package PhysicalActivity updated to version 0.2-2 with previous version 0.1-1 dated 2011-11-16

Title: Process Accelerometer Data for Physical Activity Measurement
Description: It provides a function "wearingMarking" for classification of monitor wear and nonwear time intervals in accelerometer data collected to assess physical activity. The package also contains functions for making plot for accelerometer data and obtaining the summary of various information including daily monitor wear time and the mean monitor wear time during valid days. The revised package version 0.2-1 improved the functions in the previous version regarding speed and robustness. In addition, several functions were added: "markDelivery" can classify days for ActiGraph delivery by mail; "markPAI" can categorize physical activity intensity level based on user-defined cut-points of accelerometer counts. It also supports importing ActiGraph AGD files with "readActigraph" and "queryActigraph" functions. The package also better supports time zones and daylight saving.
Author: Leena Choi [aut, cre], Cole Beck [aut], Zhouwen Liu [aut], Charles E. Matthews [aut], Maciej S. Buchowski [aut]
Maintainer: Leena Choi <leena.choi@Vanderbilt.Edu>

Diff between PhysicalActivity versions 0.1-1 dated 2011-11-16 and 0.2-2 dated 2018-05-18

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Package rsolr (with last version 0.0.8) was removed from CRAN

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

2017-08-06 0.0.8
2017-04-10 0.0.4

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Package randgeo updated to version 0.3.0 with previous version 0.2.0 dated 2017-02-28

Title: Generate Random 'WKT' or 'GeoJSON'
Description: Generate random positions (latitude/longitude), Well-known text ('WKT') points or polygons, or 'GeoJSON' points or polygons.
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>>), Noam Ross [aut], Samuel Bosch [aut]
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

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Package EValue updated to version 1.1.4 with previous version 1.1.3 dated 2018-04-03

Title: Sensitivity Analyses for Unmeasured Confounding in Observational Studies and Meta-Analyses
Description: Conducts sensitivity analyses for unmeasured confounding for either an observational study or a meta-analysis of observational studies. For a single observational study, the package reports E-values, defined as the minimum strength of association on the risk ratio scale that an unmeasured confounder would need to have with both the treatment and the outcome to fully explain away a specific treatment-outcome association, conditional on the measured covariates. One can use one of the evalues.XX() functions to compute E-values for the relevant outcome types. Outcome types include risk ratios, odds ratio with common or rare outcomes, hazard ratios with common or rare outcomes, and standardized differences in outcomes. Optionally, one can use the bias_plot() function to plot the bias factor as a function of two sensitivity parameters. (See VanderWeele & Ding, 2017 [<http://annals.org/aim/article/2643434>] for details.) For a meta-analysis, use the function confounded_meta to compute point estimates and inference for: (1) the proportion of studies with true causal effect sizes more extreme than a specified threshold of scientific importance; and (2) the minimum bias factor and confounding strength required to reduce to less than a specified threshold the proportion of studies with true effect sizes of scientifically significant size. The functions sens_plot() and sens_table() create plots and tables for visualizing these meta-analysis metrics across a range of bias values, and scrape_meta helps scrape study-level data from a published forest plot or summary table to obtain the needed estimates when these are not reported. (See Mathur & VanderWeele [<https://osf.io/jkhfg/>] for details.) Most of the analyses available in this package can also be conducted using web-based graphical interfaces (for a single observational study: <https://mmathur.shinyapps.io/evalue/>; for a meta-analysis: <https://mmathur.shinyapps.io/meta_gui_2/>).
Author: Maya B. Mathur, Peng Ding, Tyler J. VanderWeele
Maintainer: Maya B. Mathur <mmathur@stanford.edu>

Diff between EValue versions 1.1.3 dated 2018-04-03 and 1.1.4 dated 2018-05-18

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Package covr updated to version 3.1.0 with previous version 3.0.1 dated 2017-11-07

Title: Test Coverage for Packages
Description: Track and report code coverage for your package and (optionally) upload the results to a coverage service like 'Codecov' <http://codecov.io> or 'Coveralls' <http://coveralls.io>. Code coverage is a measure of the amount of code being exercised by a set of tests. It is an indirect measure of test quality and completeness. This package is compatible with any testing methodology or framework and tracks coverage of both R code and compiled C/C++/FORTRAN code.
Author: Jim Hester [aut, cre], Willem Ligtenberg [ctb], Kirill Müller [ctb], Henrik Bengtsson [ctb], Steve Peak [ctb], Kirill Sevastyanenko [ctb], Jon Clayden [ctb], Robert Flight [ctb], Eric Brown [ctb], Brodie Gaslam [ctb], Will Beasley [ctb], Robert Krzyzanowski [ctb], Markus Wamser [ctb], Karl Forner [ctb], Gergely Daróczi [ctb], Jouni Helske [ctb], Kun Ren [ctb], Jeroen Ooms [ctb], Ken Williams [ctb], Chris Campbell [ctb], David Hugh-Jones [ctb], Qin Wang [ctb]
Maintainer: Jim Hester <james.f.hester@gmail.com>

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Package rjson updated to version 0.2.19 with previous version 0.2.18 dated 2018-05-06

Title: JSON for R
Description: Converts R object into JSON objects and vice-versa.
Author: Alex Couture-Beil <rjson_pkg@mofo.ca>
Maintainer: Alex Couture-Beil <rjson_pkg@mofo.ca>

Diff between rjson versions 0.2.18 dated 2018-05-06 and 0.2.19 dated 2018-05-18

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Package rdist updated to version 0.0.3 with previous version 0.0.2 dated 2017-05-12

Title: Calculate Pairwise Distances
Description: A common framework for calculating distance matrices.
Author: Nello Blaser [aut, cre]
Maintainer: Nello Blaser <nello.blaser@uib.no>

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Package miniUI updated to version 0.1.1.1 with previous version 0.1.1 dated 2016-01-15

Title: Shiny UI Widgets for Small Screens
Description: Provides UI widget and layout functions for writing Shiny apps that work well on small screens.
Author: Joe Cheng [cre, aut], RStudio [cph]
Maintainer: Joe Cheng <joe@rstudio.com>

Diff between miniUI versions 0.1.1 dated 2016-01-15 and 0.1.1.1 dated 2018-05-18

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Package Biocomb updated to version 0.4 with previous version 0.3 dated 2017-03-22

Title: Feature Selection and Classification with the Embedded Validation Procedures for Biomedical Data Analysis
Description: Contains functions for the data analysis with the emphasis on biological data, including several algorithms for feature ranking, feature selection, classification algorithms with the embedded validation procedures. The functions can deal with numerical as well as with nominal features. Includes also the functions for calculation of feature AUC (Area Under the ROC Curve) and HUM (hypervolume under manifold) values and construction 2D- and 3D- ROC curves. Provides the calculation of Area Above the RCC (AAC) values and construction of Relative Cost Curves (RCC) to estimate the classifier performance under unequal misclassification costs problem. There exists the special function to deal with missing values, including different imputing schemes.
Author: Natalia Novoselova,Junxi Wang,Frank Pessler,Frank Klawonn
Maintainer: Natalia Novoselova <novos65@mail.ru>

Diff between Biocomb versions 0.3 dated 2017-03-22 and 0.4 dated 2018-05-18

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Package RUnit updated to version 0.4.32 with previous version 0.4.31 dated 2015-11-06

Title: R Unit Test Framework
Description: R functions implementing a standard Unit Testing framework, with additional code inspection and report generation tools.
Author: Matthias Burger <burgerm@users.sourceforge.net>, Klaus Juenemann <k.junemann@gmx.net>, Thomas Koenig <thomas.koenig@epigenomics.com>
Maintainer: Roman Zenka <zenka.roman@mayo.edu>

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New package BBI with initial version 0.2.0
Package: BBI
Type: Package
Title: Benthic Biotic Indices Calculation from Composition Data
Version: 0.2.0
Authors@R: person("Tristan", "Cordier", email = "tristan.cordier@gmail.com", role = c("aut", "cre"))
Author: Tristan Cordier [aut, cre]
Maintainer: Tristan Cordier <tristan.cordier@gmail.com>
Depends: vegan
Description: Set of functions to calculate Benthic Biotic Indices from composition data, obtained whether from morphotaxonomic inventories or sequencing data. Based on reference ecological weights publicly available for a set of commonly used marine biotic indices, such as AMBI (A Marine Biotic Index, Borja et al., 2000) <doi:10.1016/S0025-326X(00)00061-8> NSI (Norwegian Sensitivity Index) and ISI (Indicator Species Index) (Rygg 2013, <ISBN:978-82-577-6210-0>). It provides the ecological quality status of the samples based on each BBI as well as the normalized Ecological Quality Ratio.
License: AGPL-3 | file LICENSE
Encoding: UTF-8
BugReports: https://github.com/trtcrd/BBI/issues
URL: https://github.com/trtcrd/BBI
NeedsCompilation: no
Packaged: 2018-05-18 16:05:19 UTC; tristan
Repository: CRAN
Date/Publication: 2018-05-18 16:19:31 UTC

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New package SIBERG with initial version 2.0.2
Package: SIBERG
Type: Package
LazyData: true
Date: 2018-05-18
Title: Systematic Identification of Bimodally Expressed Genes Using RNAseq Data
Version: 2.0.2
Author: Pan Tong, Kevin R. Coombes
Maintainer: Kevin R. Coombes <krc@silicovore.com>
Description: Provides models to identify bimodally expressed genes from RNAseq data based on the Bimodality Index. SIBERG models the RNAseq data in the finite mixture modeling framework and incorporates mechanisms for dealing with RNAseq normalization. Three types of mixture models are implemented, namely, the mixture of log normal, negative binomial, or generalized Poisson distribution. See Tong et al. (2013) <doi:10.1093/bioinformatics/bts713>.
License: Apache License (== 2.0)
Imports: mclust
Suggests: edgeR, doParallel
URL: http://oompa.r-forge.r-project.org/
NeedsCompilation: no
Packaged: 2018-05-18 15:17:27 UTC; Kevin
Depends: R (>= 2.10)
Repository: CRAN
Date/Publication: 2018-05-18 15:41:42 UTC

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New package scopr with initial version 0.3.1
Package: scopr
Title: Read Ethoscope Data
Date: 2018-05-17
Version: 0.3.1
Authors@R: c( person("Quentin", "Geissmann", role = c("aut", "cre"), email = "qgeissmann@gmail.com") )
Description: Handling of behavioural data from the Ethoscope platform (Geissmann, Garcia Rodriguez, Beckwith, French, Jamasb and Gilestro (2017) <DOI:10.1371/journal.pbio.2003026>). Ethoscopes (<http://gilestrolab.github.io/ethoscope/>) are an open source/open hardware framework made of interconnected raspberry pis (<https://www.raspberrypi.org>) designed to quantify the behaviour of multiple small animals in a distributed and real-time fashion. The default tracking algorithm records primary variables such as xy coordinates, dimensions and speed.
Depends: R (>= 3.00), behavr
Imports: data.table, readr, stringr, RSQLite, memoise
Suggests: testthat, covr, knitr, ggetho, zeitgebr
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/rethomics/scopr
BugReports: https://github.com/rethomics/scopr/issues
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-05-18 14:42:35 UTC; quentin
Author: Quentin Geissmann [aut, cre]
Maintainer: Quentin Geissmann <qgeissmann@gmail.com>
Repository: CRAN
Date/Publication: 2018-05-18 15:36:59 UTC

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Package rsurface updated to version 1.1.0 with previous version 1.0.2 dated 2017-09-26

Title: Design of Rotatable Central Composite Experiments and Response Surface Analysis
Description: Produces tables with the level of replication (number of replicates) and the experimental uncoded values of the quantitative factors to be used for rotatable Central Composite Design (CCD) experimentation and a 2-D contour plot of the corresponding variance of the predicted response according to Mead et al. (2012) <doi:10.1017/CBO9781139020879> design_ccd(), and analyzes CCD data with response surface methodology ccd_analysis(). A rotatable CCD provides values of the variance of the predicted response that are concentrically distributed around the average treatment combination used in the experimentation, which with uniform precision (implied by the use of several replicates at the average treatment combination) improves greatly the search and finding of an optimum response. These properties of a rotatable CCD represent undeniable advantages over the classical factorial design, as discussed by Panneton et al. (1999) <doi:10.13031/2013.13267> and Mead et al. (2012) <doi:10.1017/CBO9781139020879.018> among others.
Author: Timothy Schwinghamer [aut, cre], Dutilleul Pierre [aut, cph]
Maintainer: Timothy Schwinghamer <timothy.schwinghamer@mail.mcgill.ca>

Diff between rsurface versions 1.0.2 dated 2017-09-26 and 1.1.0 dated 2018-05-18

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New package mmabig with initial version 1.0-0
Package: mmabig
Type: Package
Title: Multiple Mediation Analysis for Big Data Sets
Version: 1.0-0
Date: 2018-05-16
Author: Qingzhao Yu and Bin Li
Maintainer: Qingzhao Yu <qyu@lsuhsc.edu>
Depends: R (>= 2.14.1), glmnet, mma, splines, survival, car
Imports: gplots
Description: Used for general multiple mediation analysis with big data sets.
License: GPL (>= 2)
URL: https://www.r-project.org, https://publichealth.lsuhsc.edu/Faculty_pages/qyu/index.html
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-05-18 14:53:12 UTC; qyu
Repository: CRAN
Date/Publication: 2018-05-18 15:28:47 UTC

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Package GenAlgo updated to version 2.1.4 with previous version 2.1.3 dated 2017-07-13

Title: Classes and Methods to Use Genetic Algorithms for Feature Selection
Description: Defines classes and methods that can be used to implement genetic algorithms for feature selection. The idea is that we want to select a fixed number of features to combine into a linear classifier that can predict a binary outcome, and can use a genetic algorithm heuristically to select an optimal set of features.
Author: Kevin R. Coombes
Maintainer: Kevin R. Coombes <krc@silicovore.com>

Diff between GenAlgo versions 2.1.3 dated 2017-07-13 and 2.1.4 dated 2018-05-18

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New package npsr with initial version 0.1.1
Package: npsr
Version: 0.1.1
Type: Package
Title: Validate Instrumental Variables using NPS
Authors@R: c(person("Fabian", "Sellmann", email="fa.sllmnn@gmail.com", role = c("aut", "cre")), person("Bojan", "Nicolic", email="bojan@bnikolic.co.uk", role=c("ctb", "cph")), person("Jörn", "Grahl", email="grahl@wiso.uni-koeln.de", role="ths"))
Maintainer: Fabian Sellmann <fa.sllmnn@gmail.com>
Description: An R implementation of the Necessary and Probably Sufficient (NPS) test for finding valid instrumental variables, as suggested by Amit Sharma (2016, Working Paper) <http://amitsharma.in/pubs/necessary_probably_sufficient_iv_test.pdf>. The NPS test, compares the likelihood that a given set of observational data of the three variables Z, X and Y is generated by a valid instrumental variable model (Z -> X -> Y) to the likelihood that the data is generated by an invalid IV model.
License: GPL-2
Encoding: UTF-8
LazyData: true
Collate: npsCommon.R npsInvalid.R npsMain.R npsNecessary.R npsValid.R RNested.R
Imports: infotheo, MASS, gmp
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-05-18 13:53:56 UTC; Fabian
Author: Fabian Sellmann [aut, cre], Bojan Nicolic [ctb, cph], Jörn Grahl [ths]
Repository: CRAN
Date/Publication: 2018-05-18 14:33:18 UTC

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New package multDM with initial version 1.0
Package: multDM
Type: Package
Title: Multivariate Version of the Diebold-Mariano Test
Version: 1.0
Date: 2018-05-18
Authors@R: person("Krzysztof", "Drachal", role = c("aut","cre"), email="kdrachal@wne.uw.edu.pl", comment = "Faculty of Economic Sciences, University of Warsaw, Poland")
Author: Krzysztof Drachal [aut, cre] (Faculty of Economic Sciences, University of Warsaw, Poland)
Maintainer: Krzysztof Drachal <kdrachal@wne.uw.edu.pl>
Description: Allows to perform the multivariate version of the Diebold-Mariano test for equal predictive ability of multiple forecast comparison. Main reference: Mariano, R.S., Preve, D. (2012) <doi:10.1016/j.jeconom.2012.01.014>.
License: GPL-3
LazyData: TRUE
URL: https://CRAN.R-project.org/package=multDM
Note: Research funded by the Polish National Science Centre grant under the contract number DEC-2015/19/N/HS4/00205.
NeedsCompilation: no
Packaged: 2018-05-18 11:16:53 UTC; Krzysiek
Repository: CRAN
Date/Publication: 2018-05-18 14:04:45 UTC

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Package filesstrings updated to version 2.4.0 with previous version 2.2.0 dated 2018-04-18

Title: Handy File and String Manipulation
Description: Convenient functions for moving files, deleting directories, and a variety of string operations that facilitate manipulating files and extracting information from strings.
Author: Rory Nolan [aut, cre, cph] (<https://orcid.org/0000-0002-5239-4043>>), Sergi Padilla-Parra [ths] (<https://orcid.org/0000-0002-8010-9481>>)
Maintainer: Rory Nolan <rorynoolan@gmail.com>

Diff between filesstrings versions 2.2.0 dated 2018-04-18 and 2.4.0 dated 2018-05-18

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Package CompareCausalNetworks updated to version 0.2.2 with previous version 0.2.0 dated 2018-04-16

Title: Interface to Diverse Estimation Methods of Causal Networks
Description: Unified interface for the estimation of causal networks, including the methods 'backShift' (from package 'backShift'), 'bivariateANM' (bivariate additive noise model), 'bivariateCAM' (bivariate causal additive model), 'CAM' (causal additive model) (from package 'CAM'), 'hiddenICP' (invariant causal prediction with hidden variables), 'ICP' (invariant causal prediction) (from package 'InvariantCausalPrediction'), 'GES' (greedy equivalence search), 'GIES' (greedy interventional equivalence search), 'LINGAM', 'PC' (PC Algorithm), 'FCI' (fast causal inference), 'RFCI' (really fast causal inference) (all from package 'pcalg') and regression.
Author: Christina Heinze-Deml <heinzedeml@stat.math.ethz.ch>, Nicolai Meinshausen <meinshausen@stat.math.ethz.ch>
Maintainer: Christina Heinze-Deml <heinzedeml@stat.math.ethz.ch>

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Package biclust updated to version 2.0.0 with previous version 1.2.0 dated 2015-05-12

Title: BiCluster Algorithms
Description: The main function biclust() provides several algorithms to find biclusters in two-dimensional data: Cheng and Church (2000, ISBN:1-57735-115-0), spectral (2003) <doi:10.1101/gr.648603>, plaid model (2005) <doi:10.1016/j.csda.2004.02.003>, xmotifs (2003) <doi:10.1142/9789812776303_0008> and bimax (2006) <doi:10.1093/bioinformatics/btl060>. In addition, the package provides methods for data preprocessing (normalization and discretisation), visualisation, and validation of bicluster solutions.
Author: Sebastian Kaiser, Rodrigo Santamaria, Tatsiana Khamiakova, Martin Sill, Roberto Theron, Luis Quintales, Friedrich Leisch and Ewoud De Troyer.
Maintainer: Sebastian Kaiser <Sebastian.Kaiser@stat.uni-muenchen.de>

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Package Umpire updated to version 1.3.5 with previous version 1.3.4 dated 2017-07-11

Title: Simulating Realistic Gene Expression Data
Description: The Ultimate Microrray Prediction, Reality and Inference Engine (UMPIRE) is a package to facilitate the simulation of realistic microarray data sets with link to associate outcomes. See Zhang and Coombes (2012) <doi:10.1186/1471-2105-13-S13-S1>.
Author: Kevin R. Coombes, Jiexin Zhang
Maintainer: Kevin R. Coombes <krc@silicovore.com>

Diff between Umpire versions 1.3.4 dated 2017-07-11 and 1.3.5 dated 2018-05-18

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New package tryCatchLog with initial version 1.0.2
Package: tryCatchLog
Title: Advanced 'tryCatch()' and 'try()' Functions
Version: 1.0.2
Authors@R: person("Jürgen", "Altfeld", email = "jaltfeld@altfeld-im.de", role = c("aut", "cre", "cph"))
Description: Advanced tryCatch() and try() functions for better error handling (logging, stack trace with source code references and support for post-mortem analysis).
Imports: utils, futile.logger
Depends: R (>= 3.1.0)
License: GPL-3 | file LICENSE
URL: https://github.com/aryoda/tryCatchLog
BugReports: https://github.com/aryoda/tryCatchLog/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-05-17 17:47:09 UTC; juergen
Author: Jürgen Altfeld [aut, cre, cph]
Maintainer: Jürgen Altfeld <jaltfeld@altfeld-im.de>
Repository: CRAN
Date/Publication: 2018-05-18 12:27:18 UTC

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Package stR updated to version 0.4 with previous version 0.3 dated 2017-01-06

Title: STR Decomposition
Description: Methods for decomposing seasonal data: STR (a Seasonal-Trend decomposition procedure based on Regression) and Robust STR. In some ways, STR is similar to Ridge Regression and Robust STR can be related to LASSO. They allow for multiple seasonal components, multiple linear covariates with constant, flexible and seasonal influence. Seasonal patterns (for both seasonal components and seasonal covariates) can be fractional and flexible over time; moreover they can be either strictly periodic or have a more complex topology. The methods provide confidence intervals for the estimated components. The methods can be used for forecasting.
Author: Alexander Dokumentov, Rob J Hyndman
Maintainer: Alexander Dokumentov <alexander.dokumentov@gmail.com>

Diff between stR versions 0.3 dated 2017-01-06 and 0.4 dated 2018-05-18

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Package randomForestSRC updated to version 2.6.1 with previous version 2.6.0 dated 2018-05-02

Title: Random Forests for Survival, Regression, and Classification (RF-SRC)
Description: A unified treatment of Breiman's random forests for survival, regression and classification problems based on Ishwaran and Kogalur's random survival forests (RSF) package. Now extended to include multivariate and unsupervised forests. Also includes quantile regression forests for univariate and multivariate training/testing settings. The package runs in both serial and parallel (OpenMP) modes.
Author: Hemant Ishwaran <hemant.ishwaran@gmail.com>, Udaya B. Kogalur <ubk@kogalur.com>
Maintainer: Udaya B. Kogalur <ubk@kogalur.com>

Diff between randomForestSRC versions 2.6.0 dated 2018-05-02 and 2.6.1 dated 2018-05-18

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New package permutes with initial version 0.1
Package: permutes
Title: Permutation Tests for Time Series Data
Version: 0.1
Authors@R: person("Cesko", "Voeten", email = "c.c.voeten@hum.leidenuniv.nl", role = c("aut", "cre"))
Author: Cesko Voeten [aut, cre]
Maintainer: Cesko Voeten <c.c.voeten@hum.leidenuniv.nl>
Description: Helps you determine the analysis window to use when analyzing densely-sampled time-series data, such as EEG data, using permutation testing (Maris & Oostenveld 2007) <doi:10.1016/j.jneumeth.2007.03.024>. These permutation tests can help identify the timepoints where significance of an effects begins and ends, and the results can be plotted in various types of heatmap for reporting.
Depends: R (>= 2.10), plyr, lmPerm, ggplot2, viridis
Suggests: doParallel, dplyr, tidyr, knitr
License: FreeBSD
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
BugReports: https://github.com/cvoeten/permutes/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-05-17 17:14:08 UTC; cesko
Repository: CRAN
Date/Publication: 2018-05-18 12:28:52 UTC

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Package PCDimension updated to version 1.1.9 with previous version 1.1.8 dated 2018-01-09

Title: Finding the Number of Significant Principal Components
Description: Implements methods to automate the Auer-Gervini graphical Bayesian approach for determining the number of significant principal components. Automation uses clustering, change points, or simple statistical models to distinguish "long" from "short" steps in a graph showing the posterior number of components as a function of a prior parameter. See <doi:10.1101/237883>.
Author: Kevin R. Coombes, Min Wang
Maintainer: Kevin R. Coombes <krc@silicovore.com>

Diff between PCDimension versions 1.1.8 dated 2018-01-09 and 1.1.9 dated 2018-05-18

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Package NormPsy updated to version 1.0.8 with previous version 1.0.7 dated 2018-03-16

Title: Normalisation of Psychometric Tests
Description: Functions for normalizing psychometric test scores. The normalization aims at correcting the metrological properties of the psychometric tests such as the ceiling and floor effects and the curvilinearity (unequal interval scaling). Functions to compute and plot predictions in the natural scale of the psychometric test from the estimates of a linear mixed model estimated on the normalized scores are also provided. See Philipps et al (2014) <doi:10.1159/000365637> for details.
Author: Cecile Proust-Lima, Viviane Philipps
Maintainer: Cecile Proust-Lima <cecile.proust-lima@inserm.fr>

Diff between NormPsy versions 1.0.7 dated 2018-03-16 and 1.0.8 dated 2018-05-18

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Package nlcv updated to version 0.3.4 with previous version 0.3.3 dated 2018-05-06

Title: Nested Loop Cross Validation
Description: Nested loop cross validation for classification purposes for misclassification error rate estimation. The package supports several methodologies for feature selection: random forest, Student t-test, limma, and provides an interface to the following classification methods in the 'MLInterfaces' package: linear, quadratic discriminant analyses, random forest, bagging, prediction analysis for microarray, generalized linear model, support vector machine (svm and ksvm). Visualizations to assess the quality of the classifier are included: plot of the ranks of the features, scores plot for a specific classification algorithm and number of features, misclassification rate for the different number of features and classification algorithms tested and ROC plot. For further details about the methodology, please check: Markus Ruschhaupt, Wolfgang Huber, Annemarie Poustka, and Ulrich Mansmann (2004) <doi:10.2202/1544-6115.1078>.
Author: Willem Talloen, Tobias Verbeke
Maintainer: Laure Cougnaud <laure.cougnaud@openanalytics.eu>

Diff between nlcv versions 0.3.3 dated 2018-05-06 and 0.3.4 dated 2018-05-18

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New package MixSAL with initial version 1.0
Package: MixSAL
Type: Package
Title: Mixtures of Multivariate Shifted Asymmetric Laplace (SAL) Distributions
Version: 1.0
Date: 2018-05-010
Author: Brian C. Franczak [aut, cre], Ryan P. Browne [aut, cph], Paul D. McNicholas [aut, cph], Katherine L. Burak [ctb]
Depends: MASS (>= 3.1.3)
Maintainer: Brian C. Franczak <franczakb@macewan.ca>
Description: The current version of the 'MixSAL' package allows users to generate data from a multivariate SAL distribution or a mixture of multivariate SAL distributions, evaluate the probability density function of a multivariate SAL distribution or a mixture of multivariate SAL distributions, and fit a mixture of multivariate SAL distributions using the Expectation-Maximization (EM) algorithm (see Franczak et. al, 2014, <doi:10.1109/TPAMI.2013.216>, for details).
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2018-05-17 15:10:48 UTC; franczakb
Repository: CRAN
Date/Publication: 2018-05-18 12:10:24 UTC

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Package inline updated to version 0.3.15 with previous version 0.3.14 dated 2015-04-13

Title: Functions to Inline C, C++, Fortran Function Calls from R
Description: Functionality to dynamically define R functions and S4 methods with 'inlined' C, C++ or Fortran code supporting the .C and .Call calling conventions.
Author: Oleg Sklyar, Duncan Murdoch, Mike Smith, Dirk Eddelbuettel, Romain Francois, Karline Soetaert
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between inline versions 0.3.14 dated 2015-04-13 and 0.3.15 dated 2018-05-18

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Package compareGroups updated to version 3.4.0 with previous version 3.3.4 dated 2018-04-22

Title: Descriptive Analysis by Groups
Description: Create data summaries for quality control, extensive reports for exploring data, as well as publication-ready univariate or bivariate tables in several formats (plain text, HTML,LaTeX, PDF, Word or Excel. Create figures to quickly visualise the distribution of your data (boxplots, barplots, normality-plots, etc.). Display statistics (mean, median, frequencies, incidences, etc.). Perform the appropriate tests (t-test, Analysis of variance, Kruskal-Wallis, Fisher, log-rank, ...) depending on the nature of the described variable (normal, non-normal or qualitative). Summarize genetic data (Single Nucleotide Polymorphisms) data displaying Allele Frequencies and performing Hardy-Weinberg Equilibrium tests among other typical statistics and tests for these kind of data.
Author: Isaac Subirana, Joan Vila, Hector Sanz, Gavin Lucas, Judith Penafiel and David Gimenez
Maintainer: Isaac Subirana <isubirana@imim.es>

Diff between compareGroups versions 3.3.4 dated 2018-04-22 and 3.4.0 dated 2018-05-18

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New package childesr with initial version 0.1.0
Package: childesr
Type: Package
Title: Accessing the 'CHILDES' Database
Description: Tools for connecting to 'CHILDES', an open repository for transcripts of parent-child interaction. For more information on the underlying data, see <http://childes-db.stanford.edu>.
Version: 0.1.0
Authors@R: c( person("Mika", "Braginsky", email = "mika.br@gmail.com", role = c("aut", "cre")), person("Alessandro", "Sanchez", email = "amsan7@gmail.com", role = c("aut", "ctb")), person("Daniel", "Yurovsky", email = "dyurovsky@gmail.com", role = c("aut")), person("Kyle", "MacDonald", email = "kylem412@gmail.com", role = c("ctb")), person("Stephan", "Meylan", email = "meylan.stephan@gmail.com", role = c("ctb")) )
Depends: R (>= 3.4.0)
License: GPL-3
URL: https://github.com/langcog/childesr
BugReports: http://github.com/langcog/childesr/issues
Encoding: UTF-8
LazyData: true
Imports: DBI (>= 0.8), dbplyr (>= 1.2.1), dplyr (>= 0.7.4), jsonlite (>= 1.5), magrittr (>= 1.5), purrr (>= 0.2.4), RMySQL (>= 0.10.14)
Suggests: knitr, rmarkdown, curl
RoxygenNote: 6.0.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-05-17 19:20:29 UTC; mikabr
Author: Mika Braginsky [aut, cre], Alessandro Sanchez [aut, ctb], Daniel Yurovsky [aut], Kyle MacDonald [ctb], Stephan Meylan [ctb]
Maintainer: Mika Braginsky <mika.br@gmail.com>
Repository: CRAN
Date/Publication: 2018-05-18 12:32:18 UTC

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Package BootValidation updated to version 0.1.5 with previous version 0.1.3 dated 2017-11-14

Title: Adjusting for Optimism in 'glmnet' Regression using Bootstrapping
Description: Main objective of a predictive model is to provide accurated predictions of a new observations. Unfortunately we don't know how well the model performs. In addition, at the current era of omic data where p >> n, is not reasonable applying internal validation using data-splitting. Under this background a good method to assessing model performance is applying internal bootstrap validation (Harrell Jr, Frank E (2015) <doi:10.1007/978-1-4757-3462-1>.) This package provides bootstrap validation for the linear, logistic, multinomial and cox 'glmnet' models.
Author: Antonio Jose Canada Martinez
Maintainer: Antonio Jose Canada Martinez <ancamar2@gmail.com>

Diff between BootValidation versions 0.1.3 dated 2017-11-14 and 0.1.5 dated 2018-05-18

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New package uCAREChemSuiteCLI with initial version 0.1.0
Package: uCAREChemSuiteCLI
Type: Package
Title: Resistome Predicter
Version: 0.1.0
Date: 2018-05-16
Author: Saurav Bhaskar Saha, Vipul Gupta, Pramod Wasudeo Ramteke
Maintainer: Saurav Bhaskar Saha <saurav.saha@shiats.edu.in>
Description: Predicts Escherichia coli's resistome for candidate drug. 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 is fetched from the database for the predicted class.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Imports: ChemmineR, stats, utils, usethis
NeedsCompilation: no
Packaged: 2018-05-17 09:45:34 UTC; Saurav Saha
Repository: CRAN
Date/Publication: 2018-05-18 11:50:40 UTC

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Package tidyr updated to version 0.8.1 with previous version 0.8.0 dated 2018-01-29

Title: Easily Tidy Data with 'spread()' and 'gather()' Functions
Description: An evolution of 'reshape2'. It's designed specifically for data tidying (not general reshaping or aggregating) and works well with 'dplyr' data pipelines.
Author: Hadley Wickham [aut, cre], Lionel Henry [aut], RStudio [cph]
Maintainer: Hadley Wickham <hadley@rstudio.com>

Diff between tidyr versions 0.8.0 dated 2018-01-29 and 0.8.1 dated 2018-05-18

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Package rbgm updated to version 0.0.5 with previous version 0.0.4 dated 2016-07-22

Title: Tools for 'Box Geometry Model' (BGM) Files and Topology for the Atlantis Ecosystem Model
Description: Facilities for working with Atlantis box-geometry model (BGM) files. Atlantis is a deterministic, biogeochemical, whole-of-ecosystem model. Functions are provided to read from BGM files directly, preserving their internal topology, as well as helper functions to generate 'Spatial' objects. This functionality aims to simplify the creation and modification of box and geometry as well as the ability to integrate with other data sources.
Author: Michael D. Sumner [aut, cre]
Maintainer: Michael D. Sumner <mdsumner@gmail.com>

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Package smoothAPC updated to version 0.3 with previous version 0.2 dated 2017-09-14

Title: Smoothing of Two-Dimensional Demographic Data, Optionally Taking into Account Period and Cohort Effects
Description: The implemented method uses for smoothing bivariate thin plate splines, bivariate lasso-type regularization, and allows for both period and cohort effects. Thus the mortality rates are modelled as the sum of four components: a smooth bivariate function of age and time, smooth one-dimensional cohort effects, smooth one-dimensional period effects and random errors.
Author: Alexander Dokumentov, Rob J Hyndman
Maintainer: Alexander Dokumentov <alexander.dokumentov@gmail.com>

Diff between smoothAPC versions 0.2 dated 2017-09-14 and 0.3 dated 2018-05-18

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Package SeqFeatR updated to version 0.2.7 with previous version 0.2.6 dated 2018-03-06

Title: A Tool to Associate FASTA Sequences and Features
Description: Provides user friendly methods for the identification of sequence patterns that are statistically significantly associated with a property of the sequence. For instance, SeqFeatR allows to identify viral immune escape mutations for hosts of given HLA types. The underlying statistical method is Fisher's exact test, with appropriate corrections for multiple testing, or Bayes. Patterns may be point mutations or n-tuple of mutations. SeqFeatR offers several ways to visualize the results of the statistical analyses, see Budeus (2016) <doi:10.1371/journal.pone.0146409>.
Author: Bettina Budeus
Maintainer: Bettina Budeus <bettina.budeus@stud.uni-due.de>

Diff between SeqFeatR versions 0.2.6 dated 2018-03-06 and 0.2.7 dated 2018-05-18

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Package repr updated to version 0.15.0 with previous version 0.13 dated 2018-04-14

Title: Serializable Representations
Description: String and binary representations of objects for several formats / mime types.
Author: Philipp Angerer [aut, cre], Thomas Kluyver [aut], Jan Schulz [aut], abielr [ctb], Denilson Figueiredo de Sa [ctb], Jim Hester [ctb], karldw [ctb], Carson Sievert [ctb]
Maintainer: Philipp Angerer <phil.angerer@gmail.com>

Diff between repr versions 0.13 dated 2018-04-14 and 0.15.0 dated 2018-05-18

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Package label.switching updated to version 1.7 with previous version 1.6 dated 2016-05-22

Title: Relabelling MCMC Outputs of Mixture Models
Description: The Bayesian estimation of mixture models (and more general hidden Markov models) suffers from the label switching phenomenon, making the MCMC output non-identifiable. This package can be used in order to deal with this problem using various relabelling algorithms.
Author: Panagiotis Papastamoulis
Maintainer: Panagiotis Papastamoulis <papapast@yahoo.gr>

Diff between label.switching versions 1.6 dated 2016-05-22 and 1.7 dated 2018-05-18

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Package GAparsimony updated to version 0.9.2 with previous version 0.9-1 dated 2017-08-03

Title: Searching Parsimony Models with Genetic Algorithms
Description: Methodology that combines feature selection, model tuning, and parsimonious model selection with Genetic Algorithms (GA) proposed in {Martinez-de-Pison} (2015) <DOI:10.1016/j.asoc.2015.06.012>. To this objective, a novel GA selection procedure is introduced based on separate cost and complexity evaluations.
Author: F.J. Martinez-de-Pison [aut, cre]
Maintainer: F.J. Martinez-de-Pison <fjmartin@unirioja.es>

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Package DstarM updated to version 0.3.0 with previous version 0.2.2 dated 2017-04-30

Title: Analyze Two Choice Reaction Time Data with the D*M Method
Description: A collection of functions to estimate parameters of a diffusion model via a D*M analysis. Build in models are: the Ratcliff diffusion model, the RWiener diffusion model, and Linear Ballistic Accumulator models. Custom models functions can be specified as long as they have a density function.
Author: Don van den Bergh, Stijn Verdonck, Francis Tuerlinckx
Maintainer: Don van den Bergh <donvdbergh@hotmail.com>

Diff between DstarM versions 0.2.2 dated 2017-04-30 and 0.3.0 dated 2018-05-18

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Package zeitgebr updated to version 0.3.2 with previous version 0.3.1 dated 2018-05-16

Title: Analysis of Circadian Behaviours
Description: Use behavioural variables to compute period, rhythmicity and other circadian parameters. Methods include computation of chi square periodograms (Sokolove and Bushell (1978) <DOI:10.1016/0022-5193(78)90022-X>), Lomb-Scargle periodograms (Lomb (1976) <DOI:10.1007/BF00648343>, Scargle (1982) <DOI:10.1086/160554>, Ruf (1999) <DOI:10.1076/brhm.30.2.178.1422>), and autocorrelation-based periodograms.
Author: Quentin Geissmann [aut, cre], Luis Garcia [aut]
Maintainer: Quentin Geissmann <qgeissmann@gmail.com>

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Package BusinessDuration updated to version 0.2.0 with previous version 0.1.0 dated 2018-03-13

Title: Calculates Business Duration Between Two Dates
Description: Calculates business duration between two dates. This excluding weekends, public holidays and non-business hours.
Author: Gnaneshwar G
Maintainer: Gnaneshwar G <gnaneshwar441@gmail.com>

Diff between BusinessDuration versions 0.1.0 dated 2018-03-13 and 0.2.0 dated 2018-05-18

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Package rlas updated to version 1.2.3 with previous version 1.2.1 dated 2018-04-13

Title: Read and Write 'las' and 'laz' Binary File Formats Used for Remote Sensing Data
Description: Read and write 'las' and 'laz' binary file formats. The LAS file format is a public file format for the interchange of 3-dimensional point cloud data between data users. The LAS specifications are approved by the American Society for Photogrammetry and Remote Sensing <https://www.asprs.org/committee-general/laser-las-file-format-exchange-activities.html>. The LAZ file format is an open and lossless compression scheme for binary LAS format versions 1.0 to 1.3 <https://www.laszip.org/>.
Author: Jean-Romain Roussel [aut, cre, cph], Florian De Boissieu [aut, ctb] (Enable the support of .lax file and extra byte attributes), Martin Isenburg [cph] (Is the author of the LASlib and LASzip libraries), David Auty [ctb] (Reviewed the documentation), Pierrick Marie [ctb] (Helped to compile LASlib code in R)
Maintainer: Jean-Romain Roussel <jean-romain.roussel.1@ulaval.ca>

Diff between rlas versions 1.2.1 dated 2018-04-13 and 1.2.3 dated 2018-05-18

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More information about rlas at CRAN
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Package numOSL updated to version 2.5 with previous version 2.4 dated 2018-04-25

Title: Numeric Routines for Optically Stimulated Luminescence Dating
Description: Package for optimizing regular numeric problems in optically stimulated luminescence dating, such as: equivalent dose calculation, dose rate determination, growth curve fitting, decay curve decomposition, statistical age model optimization, and statistical plot visualization.
Author: Jun Peng [aut, cre], Bo Li [aut], Jorge More [ctb], Burton Garbow [ctb], Kenneth Hillstrom [ctb], John Burkardt [ctb], Paul Gilbert [ctb], Ravi Varadhan [ctb]
Maintainer: Jun Peng <pengjun10@mails.ucas.ac.cn>

Diff between numOSL versions 2.4 dated 2018-04-25 and 2.5 dated 2018-05-18

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Package dtw updated to version 1.20-1 with previous version 1.18-1 dated 2015-09-01

Title: Dynamic Time Warping Algorithms
Description: A comprehensive implementation of dynamic time warping (DTW) algorithms in R. DTW computes the optimal (least cumulative distance) alignment between points of two time series. Common DTW variants covered include local (slope) and global (window) constraints, subsequence matches, arbitrary distance definitions, normalizations, minimum variance matching, and so on. Provides cumulative distances, alignments, specialized plot styles, etc.
Author: Toni Giorgino <toni.giorgino@gmail.com>,
Maintainer: Toni Giorgino <toni.giorgino@gmail.com>

Diff between dtw versions 1.18-1 dated 2015-09-01 and 1.20-1 dated 2018-05-18

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Package BayesX updated to version 0.3-0 with previous version 0.2-9 dated 2014-08-18

Title: R Utilities Accompanying the Software Package BayesX
Description: Functions for exploring and visualising estimation results obtained with BayesX, a free software for estimating structured additive regression models (<http://www.BayesX.org>). In addition, functions that allow to read, write and manipulate map objects that are required in spatial analyses performed with BayesX.
Author: Nikolaus Umlauf [aut, cre], Thomas Kneib [aut], Nadja Klein [aut], Felix Heinzl [ctb], Andreas Brezger [ctb], Daniel Sabanes Bove [ctb]
Maintainer: Nikolaus Umlauf <Nikolaus.Umlauf@uibk.ac.at>

Diff between BayesX versions 0.2-9 dated 2014-08-18 and 0.3-0 dated 2018-05-18

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Package wrapr updated to version 1.4.1 with previous version 1.4.0 dated 2018-04-03

Title: Wrap R Tools for Debugging and Parametric Programming
Description: Tools for writing and debugging R code. Provides: 'let()' which converts non-standard evaluation interfaces to parametric standard evaluation interface, 'qc()' quoting concatenate, 'DebugFnW()' to capture function context on error for debugging, dot-pipe, ':=' named map builder, and lambda-abstraction.
Author: John Mount [aut, cre], Nina Zumel [aut], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

Diff between wrapr versions 1.4.0 dated 2018-04-03 and 1.4.1 dated 2018-05-18

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Package warbleR updated to version 1.1.13 with previous version 1.1.12 dated 2018-03-14

Title: Streamline Bioacoustic Analysis
Description: A tool to streamline the analysis of animal acoustic signal structure. The package offers functions for downloading avian vocalizations from the open-access online repository 'Xeno-Canto' <http://xeno-canto.org/>, displaying the geographic extent of the recordings, manipulating sound files, detecting acoustic signals, assessing performance of methods that measure acoustic similarity, conducting cross-correlations, dynamic time warping, measuring acoustic parameters and analysing interactive vocal signals, among others. Most functions working iteratively allow parallelization to improve computational efficiency.
Author: Marcelo Araya-Salas & Grace Smith Vidaurre
Maintainer: Marcelo Araya-Salas <araya-salas@cornell.edu>

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 warbleR-1.1.13/warbleR/DESCRIPTION                                                       |   17 
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 warbleR-1.1.13/warbleR/NAMESPACE                                                         |   57 +
 warbleR-1.1.13/warbleR/NEWS.md                                                           |   29 
 warbleR-1.1.13/warbleR/R/autodetec.R                                                     |   50 +
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 warbleR-1.1.13/warbleR/R/catalog2pdf.R                                                   |   29 
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 warbleR-1.1.13/warbleR/R/checkwavs.R                                                     |   39 +
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 warbleR-1.1.13/warbleR/R/consolidate.R                                                   |   35 +
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 warbleR-1.1.13/warbleR/R/cut_sels.R                                                      |   54 +
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 warbleR-1.1.13/warbleR/R/ffDTW.R                                                         |   41 +
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 warbleR-1.1.13/warbleR/R/lspec2pdf.R                                                     |   18 
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Package spt updated to version 2.5.1 with previous version 1.13-8-8 dated 2013-08-08

Title: Sierpinski Pedal Triangle
Description: A collection of algorithms related to Sierpinski pedal triangle (SPT).
Author: Bin Wang <bwang@southalabama.edu>.
Maintainer: Bin Wang <bwang@southalabama.edu>

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Package simsurv updated to version 0.2.2 with previous version 0.2.0 dated 2018-03-05

Title: Simulate Survival Data
Description: Simulate survival times from standard parametric survival distributions (exponential, Weibull, Gompertz), 2-component mixture distributions, or a user-defined hazard, log hazard, cumulative hazard, or log cumulative hazard function. Baseline covariates can be included under a proportional hazards assumption. Time dependent effects (i.e. non-proportional hazards) can be included by interacting covariates with linear time or a user-defined function of time. Clustered event times are also accommodated. The 2-component mixture distributions can allow for a variety of flexible baseline hazard functions reflecting those seen in practice. If the user wishes to provide a user-defined hazard or log hazard function then this is possible, and the resulting cumulative hazard function does not need to have a closed-form solution. Note that this package is modelled on the 'survsim' package available in the 'Stata' software (see Crowther and Lambert (2012) <http://www.stata-journal.com/sjpdf.html?articlenum=st0275> or Crowther and Lambert (2013) <doi:10.1002/sim.5823>).
Author: Sam Brilleman [cre, aut, cph], Alessandro Gasparini [ctb]
Maintainer: Sam Brilleman <sam.brilleman@monash.edu>

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Package rmcfs updated to version 1.2.11 with previous version 1.2.10 dated 2018-03-27

Title: The MCFS-ID Algorithm for Feature Selection and Interdependency Discovery
Description: MCFS-ID (Monte Carlo Feature Selection and Interdependency Discovery) is a Monte Carlo method-based tool for feature selection. It also allows for the discovery of interdependencies between the relevant features. MCFS-ID is particularly suitable for the analysis of high-dimensional, 'small n large p' transactional and biological data. M.Draminski, A.Rada-Iglesias, S.Enroth, C.Wadelius, J. Koronacki, J.Komorowski (2008) <doi:10.1093/bioinformatics/btm486>.
Author: Michal Draminski [aut, cre], Jacek Koronacki [aut], Julian Zubek [ctb]
Maintainer: Michal Draminski <michal.draminski@ipipan.waw.pl>

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Package Modeler updated to version 3.4.3 with previous version 3.4.2 dated 2017-07-13

Title: Classes and Methods for Training and Using Binary Prediction Models
Description: Defines classes and methods to learn models and use them to predict binary outcomes. These are generic tools, but we also include specific examples for many common classifiers.
Author: Kevin R. Coombes
Maintainer: Kevin R. Coombes <krc@silicovore.com>

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Package ggjoy updated to version 0.4.1 with previous version 0.4.0 dated 2017-09-15

Title: Joyplots in 'ggplot2'
Description: Joyplots provide a convenient way of visualizing changes in distributions over time or space. This package enables the creation of such plots in 'ggplot2'.
Author: Claus O. Wilke [cre, aut]
Maintainer: Claus O. Wilke <wilke@austin.utexas.edu>

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Package compareDF updated to version 1.3.1 with previous version 1.3.0 dated 2018-03-15

Title: Do a Git Style Diff of the Rows Between Two Dataframes with Similar Structure
Description: Compares two dataframes which have the same column structure to show the rows that have changed. Also gives a git style diff format to quickly see what has changes in addition to summary statistics.
Author: Alex Joseph [aut, cre]
Maintainer: Alex Joseph <alexsanjoseph@gmail.com>

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