Wed, 06 Sep 2017

Package propr updated to version 3.0.7 with previous version 3.0.6 dated 2017-08-01

Title: Calculating Proportionality Between Vectors of Compositional Data
Description: The bioinformatic evaluation of gene co-expression often begins with correlation-based analyses. However, this approach lacks statistical validity when applied to relative data. This includes, for example, biological count data generated by high-throughput RNA-sequencing, chromatin immunoprecipitation (ChIP), ChIP-sequencing, Methyl-Capture sequencing, and other techniques. This package implements several metrics for proportionality, including phi [Lovell et al (2015) <DOI:10.1371/journal.pcbi.1004075>] and rho [Erb and Notredame (2016) <DOI:10.1007/s12064-015-0220-8>]. This package also implements several metrics for differential proportionality. Unlike correlation, these measures give the same result for both relative and absolute data.
Author: Thomas Quinn [aut, cre], David Lovell [aut], Ionas Erb [aut], Anders Bilgrau [ctb], Greg Gloor [ctb]
Maintainer: Thomas Quinn <contacttomquinn@gmail.com>

Diff between propr versions 3.0.6 dated 2017-08-01 and 3.0.7 dated 2017-09-06

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Package openssl updated to version 0.9.7 with previous version 0.9.6 dated 2016-12-30

Title: Toolkit for Encryption, Signatures and Certificates Based on OpenSSL
Description: Bindings to OpenSSL libssl and libcrypto, plus custom SSH pubkey parsers. Supports RSA, DSA and EC curves P-256, P-384 and P-521. Cryptographic signatures can either be created and verified manually or via x509 certificates. AES can be used in cbc, ctr or gcm mode for symmetric encryption; RSA for asymmetric (public key) encryption or EC for Diffie Hellman. High-level envelope functions combine RSA and AES for encrypting arbitrary sized data. Other utilities include key generators, hash functions (md5, sha1, sha256, etc), base64 encoder, a secure random number generator, and 'bignum' math methods for manually performing crypto calculations on large multibyte integers.
Author: Jeroen Ooms [cre, aut], Oliver Keyes [ctb]
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

Diff between openssl versions 0.9.6 dated 2016-12-30 and 0.9.7 dated 2017-09-06

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Package madrat updated to version 1.22.1 with previous version 1.8.0 dated 2017-05-29

Title: May All Data be Reproducible and Transparent (MADRaT) *
Description: Provides a framework which should improve reproducibility and transparency in data processing. It provides functionality such as automatic meta data creation and management, rudimentary quality management, data caching, work-flow management and data aggregation. * The title is a wish not a promise. By no means we expect this package to deliver everything what is needed to achieve full reproducibility and transparency, but we believe that it supports efforts in this direction.
Author: Jan Philipp Dietrich [aut, cre], Lavinia Baumstark [aut], Anastasis Giannousakis [aut], Benjamin Leon Bodirsky [ctb], Ulrich Kreidenweis [ctb]
Maintainer: Jan Philipp Dietrich <dietrich@pik-potsdam.de>

Diff between madrat versions 1.8.0 dated 2017-05-29 and 1.22.1 dated 2017-09-06

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Package writexl updated to version 0.2 with previous version 0.1 dated 2017-08-30

Title: Export Data Frames to 'xlsx' Format
Description: Portable, light-weight data frame to 'xlsx' exporter based on 'libxlsxwriter'. No 'Java' or 'Excel' required.
Author: Jeroen Ooms [aut, cre], John McNamara [cph] (Author of libxlsxwriter (see AUTHORS and COPYRIGHT files for details))
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

Diff between writexl versions 0.1 dated 2017-08-30 and 0.2 dated 2017-09-06

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Package RGraphM updated to version 0.1.11 with previous version 0.1.10 dated 2017-08-26

Title: Graph Matching Library for R
Description: This is a wrapper package for the graph matching library 'graphm'. The original 'graphm' C/C++ library can be found in <http://cbio.mines-paristech.fr/graphm/> . Latest version ( 0.52 ) of this library is slightly modified to fit 'Rcpp' usage and included in the source package. The development version of the package is also available at <https://github.com/adalisan/RGraphM> .
Author: Mikhail Zaslavskiy, Sancar Adali
Maintainer: Sancar Adali <sancar.adali@gmail.com>

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Package magclass updated to version 4.51.1 with previous version 4.39 dated 2017-05-26

Title: Data Class and Tools for Handling Spatial-Temporal Data
Description: Data class for increased interoperability working with spatial- temporal data together with corresponding functions and methods (conversions, basic calculations and basic data manipulation). The class distinguishes between spatial, temporal and other dimensions to facilitate the development and interoperability of tools build for it. Additional features are name-based addressing of data and internal consistency checks (e.g. checking for the right data order in calculations).
Author: Jan Philipp Dietrich, Benjamin Bodirsky, Misko Stevanovic, Lavinia Baumstark, Christoph Bertram, Markus Bonsch, Anastasis Giannousakis, Florian Humpenoeder, David Klein, Ina Neher, Michaja Pehl, Anselm Schultes, Xiaoxi Wang
Maintainer: Jan Philipp Dietrich <dietrich@pik-potsdam.de>

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Package DiagrammeR updated to version 0.9.2 with previous version 0.9.1 dated 2017-08-21

Title: Graph/Network Visualization
Description: Graph and network visualization using tabular data.
Author: Knut Sveidqvist [aut, cph] (mermaid.js library in htmlwidgets/lib, http://github.com/knsv/mermaid/), Mike Bostock [aut, cph] (d3.js library in htmlwidgets/lib, http://d3js.org), Chris Pettitt [aut, cph] (dagre-d3.js library in htmlwidgets/lib, http://github.com/cpettitt/dagre-d3), Mike Daines [aut, cph] (viz.js library in htmlwidgets/lib, http://github.com/mdaines/viz.js/), Richard Iannone [aut, cre] (R interface)
Maintainer: Richard Iannone <riannone@me.com>

Diff between DiagrammeR versions 0.9.1 dated 2017-08-21 and 0.9.2 dated 2017-09-06

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Package bupaR updated to version 0.3.0 with previous version 0.2.0 dated 2017-06-19

Title: Business Process Analytics in R
Description: Functionalities for process analysis in R. This packages implements an S3-class for event log objects, and related handler functions. Imports related packages for subsetting event data, computation of descriptive statistics, handling of Petri Net objects and visualization of process maps. See also packages 'edeaR','processmapR', 'eventdataR' and 'processmonitR'.
Author: Gert Janssenswillen
Maintainer: Gert Janssenswillen <gert.janssenswillen@uhasselt.be>

Diff between bupaR versions 0.2.0 dated 2017-06-19 and 0.3.0 dated 2017-09-06

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Package batchtools updated to version 0.9.6 with previous version 0.9.5 dated 2017-08-18

Title: Tools for Computation on Batch Systems
Description: As a successor of the packages 'BatchJobs' and 'BatchExperiments', this package provides a parallel implementation of the Map function for high performance computing systems managed by schedulers 'IBM Spectrum LSF' (<http://www-03.ibm.com/systems/spectrum-computing/products/lsf/>), 'OpenLava' (<http://www.openlava.org/>), 'Univa Grid Engine'/'Oracle Grid Engine' (<http://www.univa.com/>), 'Slurm' (<http://slurm.schedmd.com/>), 'TORQUE/PBS' (<http://www.adaptivecomputing.com/products/open-source/torque/>), or 'Docker Swarm' (<https://docs.docker.com/swarm/>). A multicore and socket mode allow the parallelization on a local machines, and multiple machines can be hooked up via SSH to create a makeshift cluster. Moreover, the package provides an abstraction mechanism to define large-scale computer experiments in a well-organized and reproducible way.
Author: Michel Lang [cre, aut], Bernd Bischl [aut], Dirk Surmann [ctb]
Maintainer: Michel Lang <michellang@gmail.com>

Diff between batchtools versions 0.9.5 dated 2017-08-18 and 0.9.6 dated 2017-09-06

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New package tsdf with initial version 1.1-2
Package: tsdf
Type: Package
Title: Two-/Three-Stage Designs for Phase 1&2 Clinical Trials
Version: 1.1-2
Date: 2017-09-06
Author: Wenchuan Guo, Bob Zhong
Maintainer: Wenchuan Guo <wguo007@ucr.edu>
Imports: gsDesign
Description: Calculate optimal Zhong's two-/three-stage Phase II designs (see Zhong (2012) <doi:10.1016/j.cct.2012.07.006>). Generate two-/three-stage dose finding decision table. This package also allows users to run dose-finding simulations based on customized decision table.
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-09-06 18:08:03 UTC; wguo25
Repository: CRAN
Date/Publication: 2017-09-06 18:20:14 UTC

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Package MALDIquantForeign updated to version 0.11 with previous version 0.10 dated 2015-10-31

Title: Import/Export Routines for 'MALDIquant'
Description: Functions for reading (tab, csv, Bruker fid, Ciphergen XML, mzXML, mzML, imzML, Analyze 7.5, CDF, mMass MSD) and writing (tab, csv, mMass MSD, mzML, imzML) different file formats of mass spectrometry data into/from 'MALDIquant' objects.
Author: Sebastian Gibb [aut, cre], Pietro Franceschi [ctb]
Maintainer: Sebastian Gibb <mail@sebastiangibb.de>

Diff between MALDIquantForeign versions 0.10 dated 2015-10-31 and 0.11 dated 2017-09-06

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New package csabounds with initial version 1.0.0
Package: csabounds
Title: Bounds on Distributional Treatment Effect Parameters
Version: 1.0.0
Authors@R: person("Brantly", "Callaway", email = "brantly.callaway@temple.edu", role = c("aut", "cre"))
Description: The joint distribution of potential outcomes is not typically identified under standard identifying assumptions such as selection on observables or even when individuals are randomly assigned to being treated. This package contains methods for obtaining tight bounds on distributional treatment effect parameters when panel data is available and under a Copula Stability Assumption as in Callaway (2017) <https://ssrn.com/abstract=3028251>.
Imports: stats, ggplot2, BMisc, pbapply, progress, qte
Depends: R (>= 3.0)
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-09-06 17:58:24 UTC; tug82594
Author: Brantly Callaway [aut, cre]
Maintainer: Brantly Callaway <brantly.callaway@temple.edu>
Repository: CRAN
Date/Publication: 2017-09-06 18:07:28 UTC

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New package SmoothWin with initial version 1.0.0
Package: SmoothWin
Type: Package
Version: 1.0.0
Date: 2017-09-06
Author: Hamed Haselimashhadi <hamedhaseli@gmail.com>
Maintainer: Hamed Haselimashhadi <hamedhaseli@gmail.com>
Depends: R (>= 2.0)
Description: The main function in the package utilizes a windowing function in the form of an exponential weighting function. The bandwidth and sharpness of the window are controlled by two parameters. Then, a penalized change point detection is used to identify the right shape of the window (see Charles Kervrann (2004) <doi:10.1007/978-3-540-24672-5_11>).
Title: Soft Windowing on Linear Regression
License: LGPL (>= 2)
Packaged: 2017-09-06 15:48:05 UTC; hamedhm
Imports: msgps
URL: http://hamedhaseli.webs.com
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2017-09-06 17:03:58 UTC

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New package FRegSigCom with initial version 0.1.0
Package: FRegSigCom
Type: Package
Title: Functional Regression using Signal Compression Approach
Version: 0.1.0
Author: Ruiyan Luo, Xin Qi
Maintainer: Ruiyan Luo <rluo@gsu.edu>
Description: Signal compression methods for function-on-function (FOF) regression with functional response and functional predictors, including linear models with both scalar and functional predictors for a small number of functional predictors, linear models with functional predictors for a large number of functional predictors, and nonlinear models. Ruiyan Luo and Xin Qi (2017) <doi:10.1080/01621459.2016.1164053>.
License: GPL-2
LazyData: TRUE
Imports: fda
Suggests: refund, MASS
Collate: 'multiple_function_on_function.R' 'nonlinear_function_on_function.R' 'high_dimensional_function_on_function.R'
RoxygenNote: 6.0.1.9000
NeedsCompilation: no
Packaged: 2017-09-06 14:32:33 UTC; Ruiyan
Repository: CRAN
Date/Publication: 2017-09-06 17:16:52 UTC

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New package bnclassify with initial version 0.3.3
Package: bnclassify
Title: Learning Discrete Bayesian Network Classifiers from Data
Description: Implements state-of-the art algorithms for learning discrete Bayesian network classifiers from data, including a number of those described in Bielza & Larranaga (2014) <doi:10.1145/2576868>, as well as functions for using these classifiers for prediction, assessing their predictive performance, and inspecting their properties.
Version: 0.3.3
Authors@R: c(person("Mihaljevic","Bojan",email="bmihaljevic@fi.upm.es",role=c("aut","cre")), person("Bielza","Concha",email="mcbielza@fi.upm.es",role="aut"), person("Larranaga","Pedro",email="pedro.larranaga@fi.upm.es",role="aut"), person("Wickham", "Hadley", role="ctb", comment="some code extracted from memoise package"))
URL: http://github.com/bmihaljevic/bnclassify
BugReports: http://github.com/bmihaljevic/bnclassify/issues
Depends: R (>= 3.2.0)
Imports: assertthat (>= 0.1), entropy(>= 1.2.0), graph(>= 1.42.0), matrixStats(>= 0.14.0), RBGL(>= 1.40.1), rpart(>= 4.1-8)
Suggests: gRain(>= 1.2-3), gRbase(>= 1.7-0.1), mlr(>= 2.2), testthat(>= 0.8.1), knitr(>= 1.10.5), microbenchmark(>= 1.4-2), ParamHelpers(>= 1.5), Rgraphviz(>= 2.8.1), rmarkdown(>= 0.7), covr
License: GPL (>= 2)
Maintainer: Mihaljevic Bojan <bmihaljevic@fi.upm.es>
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-09-06 11:14:51 UTC; bmihaljevic
Author: Mihaljevic Bojan [aut, cre], Bielza Concha [aut], Larranaga Pedro [aut], Wickham Hadley [ctb] (some code extracted from memoise package)
Repository: CRAN
Date/Publication: 2017-09-06 17:29:28 UTC

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New package UdderQuarterInfectionData with initial version 1.0.0
Package: UdderQuarterInfectionData
Type: Package
Title: Udder Quarter Infection Data
Version: 1.0.0
Date: 2017-09-06
Author: Hans Laevens, Luc Duchateau, Klara Goethals, Ewoud De Troyer and Paul Janssen
Maintainer: Luc Duchateau <Luc.Duchateau@ugent.be>
Description: The udder quarter infection data set contains infection times of individual cow udder quarters with Corynebacterium bovis (Laevens et al. 1997 <DOI:10.3168/jds.S0022-0302(97)76295-7>). Obviously, the four udder quarters are clustered within a cow, and udder quarters are sampled only approximately monthly, generating interval-censored data. The data set contains both covariates that change within a cow (e.g., front and rear udder quarters) and covariates that change between cows (e.g., parity [the number of previous calvings]). The correlation between udder infection times within a cow also is of interest, because this is a measure of the infectivity of the agent causing the disease. Various models have been applied to address the problem of interdependence for right-censored event times. These models, as applied to this data set, can be found back in the publications found in the reference list.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Imports: stats, utils
NeedsCompilation: no
Packaged: 2017-09-06 14:44:15 UTC; lucp8394
Repository: CRAN
Date/Publication: 2017-09-06 15:53:42 UTC

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Package clickR updated to version 0.3.29 with previous version 0.3.27 dated 2017-09-02

Title: Fix Data and Create Report Tables from Different Objects
Description: Fixes data errors in numerical, factor and date variables, checks data quality, performs exploratory analysis and creates report tables from models and summaries.
Author: Victoria Fornes Ferrer, David Hervas Marin
Maintainer: David Hervas Marin <ddhervas@yahoo.es>

Diff between clickR versions 0.3.27 dated 2017-09-02 and 0.3.29 dated 2017-09-06

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Package graphicalVAR updated to version 0.2.1 with previous version 0.2 dated 2017-03-27

Title: Graphical VAR for Experience Sampling Data
Description: Estimates within and between time point interactions in experience sampling data, using the Graphical VAR model in combination with LASSO and EBIC.
Author: Sacha Epskamp
Maintainer: Sacha Epskamp <mail@sachaepskamp.com>

Diff between graphicalVAR versions 0.2 dated 2017-03-27 and 0.2.1 dated 2017-09-06

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New package TNC with initial version 0.1.0
Package: TNC
Type: Package
Title: Temporal Network Centrality (TNC) Measures
Version: 0.1.0
Authors@R: person("Moritz", "Hanke", email = "hanke@leibniz-bips.de", role = c("aut", "cre"))
Description: Node centrality measures for temporal networks. Available measures are temporal degree centrality, temporal closeness centrality and temporal betweenness centrality defined by Kim and Anderson (2012) <doi:10.1103/PhysRevE.85.026107>. Applying the REN algorithm by Hanke and Foraita (2017) <doi:10.1186/s12859-017-1677-x> when calculating the centrality measures keeps the computational running time linear in the number of graph snapshots. Further, all methods can run in parallel up to the number of nodes in the network.
Depends: R (>= 3.4.1)
License: GPL-3
Encoding: UTF-8
LazyData: true
Suggests: igraph (>= 1.1.2), parallel (>= 3.4.1), testthat (>= 1.0.2)
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-09-06 12:50:23 UTC; momo
Author: Moritz Hanke [aut, cre]
Maintainer: Moritz Hanke <hanke@leibniz-bips.de>
Repository: CRAN
Date/Publication: 2017-09-06 13:06:13 UTC

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Package bootnet updated to version 1.0.1 with previous version 1.0.0 dated 2017-05-04

Title: Bootstrap Methods for Various Network Estimation Routines
Description: Bootstrap methods to assess accuracy and stability of estimated network structures and centrality indices. Allows for flexible specification of any undirected network estimation procedure in R, and offers default sets for 'qgraph', 'IsingFit', 'IsingSampler', 'glasso', 'huge' and 'parcor' packages.
Author: Sacha Epskamp and Eiko I. Fried
Maintainer: Sacha Epskamp <mail@sachaepskamp.com>

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Package SPEDInstabR updated to version 1.5 with previous version 1.4 dated 2017-06-05

Title: Estimation of the Relative Importance of Factors Affecting Species Distribution Based on Stability Concept
Description: From output files obtained from the software 'ModestR', the relative contribution of factors to explain species distribution is depicted using several plots. A global geographic raster file for each environmental variable may be also obtained with the mean relative contribution, considering all species present in each raster cell, of the factor to explain species distribution. Finally, for each variable it is also possible to compare the frequencies of any variable obtained in the cells where the species is present with the frequencies of the same variable in the cells of the extent.
Author: Cástor Guisande González
Maintainer: Cástor Guisande González <castor@uvigo.es>

Diff between SPEDInstabR versions 1.4 dated 2017-06-05 and 1.5 dated 2017-09-06

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Package SpatialPosition updated to version 1.2.0 with previous version 1.1.1 dated 2016-06-13

Title: Spatial Position Models
Description: Computes spatial position models: Stewart potentials, Reilly catchment areas, Huff catchment areas.
Author: Timothée Giraud [cre, aut], Hadrien Commenges [aut], Joël Boulier [ctb]
Maintainer: Timothée Giraud <timothee.giraud@cnrs.fr>

Diff between SpatialPosition versions 1.1.1 dated 2016-06-13 and 1.2.0 dated 2017-09-06

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Package ROptSpace updated to version 0.1.1 with previous version 0.1.0 dated 2017-09-05

Title: Matrix Reconstruction from a Few Entries
Description: Matrix reconstruction, also known as matrix completion, is the task of inferring missing entries of a partially observed matrix. This package provides a method called OptSpace, which was proposed by Keshavan, R.H., Oh, S., and Montanari, A. (2009) <doi:10.1109/ISIT.2009.5205567> for a case under low-rank assumption.
Author: Kisung You [aut, cre]
Maintainer: Kisung You <kyou@nd.edu>

Diff between ROptSpace versions 0.1.0 dated 2017-09-05 and 0.1.1 dated 2017-09-06

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Package graphon updated to version 0.1.1 with previous version 0.1.0 dated 2017-09-04

Title: A Collection of Graphon Estimation Methods
Description: Provides a not-so-comprehensive list of methods for estimating graphon, a symmetric measurable function, from a single or multiple of observed networks. For a detailed introduction on graphon and popular estimation techniques, see the paper by Orbanz, P. and Roy, D.M.(2014) <doi:10.1109/TPAMI.2014.2334607>. It also contains several auxiliary functions for generating sample networks using various network models and graphons.
Author: Kisung You [aut, cre]
Maintainer: Kisung You <kyou@nd.edu>

Diff between graphon versions 0.1.0 dated 2017-09-04 and 0.1.1 dated 2017-09-06

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Package graphkernels updated to version 1.3 with previous version 1.2 dated 2017-04-14

Title: Graph Kernels
Description: A fast C++ implementation for computing various graph kernels including (1) simple kernels between vertex and/or edge label histograms, (2) graphlet kernels, (3) random walk kernels (popular baselines), and (4) the Weisfeiler-Lehman graph kernel (state-of-the-art).
Author: Mahito Sugiyama
Maintainer: Mahito Sugiyama <mahito@nii.ac.jp>

Diff between graphkernels versions 1.2 dated 2017-04-14 and 1.3 dated 2017-09-06

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Package FactorsR updated to version 1.2 with previous version 1.1 dated 2017-02-17

Title: Identification of the Factors Affecting Species Richness
Description: It identifies the factors significantly related to species richness, and their relative contribution, using multiple regressions and support vector machine models. It uses an output file of 'ModestR' (<http://www.ipez.es/ModestR>) with data of richness of the species and environmental variables in a cell size defined by the user. The residuals of the support vector machine model are shown on a map. Negative residuals may be potential areas with undiscovered and/or unregistered species, or areas with decreased species richness due to the negative effect of anthropogenic factors.
Author: Cástor Guisande González
Maintainer: Cástor Guisande González <castor@uvigo.es>

Diff between FactorsR versions 1.1 dated 2017-02-17 and 1.2 dated 2017-09-06

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Package SIMMS updated to version 1.1.0 with previous version 1.0.2 dated 2015-09-21

Title: Subnetwork Integration for Multi-Modal Signatures
Description: Algorithms to create prognostic biomarkers using biological networks.
Author: Syed Haider, Michal Grzadkowski, Paul C. Boutros
Maintainer: Syed Haider <Syed.Haider@oicr.on.ca>

Diff between SIMMS versions 1.0.2 dated 2015-09-21 and 1.1.0 dated 2017-09-06

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New package Ohit with initial version 1.0.0
Package: Ohit
Type: Package
Title: OGA+HDIC+Trim and High-Dimensional Linear Regression Models
Version: 1.0.0
Date: 2017-09-06
Author: Hai-Tang Chiou, Ching-Kang Ing, Tze Leung Lai
Maintainer: Hai-Tang Chiou <htchiou1@gmail.com>
Imports: stats
Description: Ing and Lai (2011) <doi:10.5705/ss.2010.081> proposed a high-dimensional model selection procedure that comprises three steps: orthogonal greedy algorithm (OGA), high-dimensional information criterion (HDIC), and Trim. The first two steps, OGA and HDIC, are used to sequentially select input variables and determine stopping rules, respectively. The third step, Trim, is used to delete irrelevant variables remaining in the second step. This package aims at fitting a high-dimensional linear regression model via OGA+HDIC+Trim.
License: GPL-2
URL: http://mx.nthu.edu.tw/~cking/pdf/IngLai2011.pdf
Encoding: UTF-8
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-09-06 06:00:36 UTC; stat_pc
Repository: CRAN
Date/Publication: 2017-09-06 12:01:26 UTC

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Package survPresmooth updated to version 1.1-10 with previous version 1.1-9 dated 2016-03-11

Title: Presmoothed Estimation in Survival Analysis
Description: Presmoothed estimators of survival, density, cumulative and non-cumulative hazard functions with right-censored survival data.
Author: Ignacio Lopez de Ullibarri <ilu@udc.es> [aut, cre], Maria Amalia Jacome <majacome@udc.es> [aut]
Maintainer: Ignacio Lopez de Ullibarri <ilu@udc.es>

Diff between survPresmooth versions 1.1-9 dated 2016-03-11 and 1.1-10 dated 2017-09-06

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Package metamisc updated to version 0.1.6 with previous version 0.1.5 dated 2017-06-22

Title: Diagnostic and Prognostic Meta-Analysis
Description: Meta-analysis of diagnostic and prognostic modeling studies. Summarize estimates of diagnostic test accuracy and prediction model performance. Validate, update and combine published prediction models.
Author: Thomas Debray [aut, cre], Valentijn de Jong [aut]
Maintainer: Thomas Debray <thomas.debray@gmail.com>

Diff between metamisc versions 0.1.5 dated 2017-06-22 and 0.1.6 dated 2017-09-06

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Package spartan updated to version 3.0.0 with previous version 2.3 dated 2015-10-19

Title: Simulation Parameter Analysis R Toolkit ApplicatioN: Spartan
Description: Computer simulations are becoming a popular technique to use in attempts to further our understanding of complex systems. SPARTAN, first described in our 2013 publication in PLoS Computational Biology, provided code for four techniques described in available literature which aid the analysis of simulation results, at both single and multiple timepoints in the simulation run. The first technique addresses aleatory uncertainty in the system caused through inherent stochasticity, and determines the number of replicate runs necessary to generate a representative result. The second examines how robust a simulation is to parameter perturbation, through the use of a one-at-a-time parameter analysis technique. Thirdly, a latin hypercube based sensitivity analysis technique is included which can elucidate non-linear effects between parameters and indicate implications of epistemic uncertainty with reference to the system being modelled. Finally, a further sensitivity analysis technique, the extended Fourier Amplitude Sampling Test (eFAST) has been included to partition the variance in simulation results between input parameters, to determine the parameters which have a significant effect on simulation behaviour. Version 1.3 added support for Netlogo simulations, aiding simulation developers who use Netlogo to build their simulations perform the same analyses. Version 2.0 added the ability to read all simulations in from a single CSV file in addition to the prescribed folder structure in previous versions. Version 3.0 offers significant additional functionality that permits the creation of emulations of simulation results, derived using the same sampling techniques in the global sensitivity analysis techniques, and the generation of combinations of these machine learning algorithms to one create one predictive tool, more commonly known as an ensemble model. Version 3.0 also improved the standard of the graphs produced in the original sensitivity analysis techniques, and introduced a polar plot to examine parameter sensitivity.
Author: Kieran Alden [cre, aut], Mark Read [aut], Paul Andrews [aut], Jason Cosgrove [aut], Mark Coles [aut], Jon Timmis [aut]
Maintainer: Kieran Alden <kieran.alden@gmail.com>

Diff between spartan versions 2.3 dated 2015-10-19 and 3.0.0 dated 2017-09-06

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 spartan-3.0.0/spartan/MD5                                                          |  271 ++++++----
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 spartan-3.0.0/spartan/vignettes                                                    |only
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More information about spartan at CRAN
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Package BIGDAWG updated to version 1.16 with previous version 1.14.2 dated 2017-07-19

Title: Case-Control Analysis of Multi-Allelic Loci
Description: Data sets and functions for chi-squared Hardy-Weinberg and case-control association tests of highly polymorphic genetic data [e.g., human leukocyte antigen (HLA) data]. Performs association tests at multiple levels of polymorphism (haplotype, locus and HLA amino-acids) as described in Pappas DJ, Marin W, Hollenbach JA, Mack SJ (2016) <doi:10.1016/j.humimm.2015.12.006>. Combines rare variants to a common class to account for sparse cells in tables as described by Hollenbach JA, Mack SJ, Thomson G, Gourraud PA (2012) <doi:10.1007/978-1-61779-842-9_14>.
Author: Derek Pappas <dpappas@chori.org>, Steve Mack <sjmack@chori.org>, Jill Hollenbach <Jill.Hollenbach@ucsf.edu>
Maintainer: Steve Mack <sjmack@chori.org>

Diff between BIGDAWG versions 1.14.2 dated 2017-07-19 and 1.16 dated 2017-09-06

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More information about BIGDAWG at CRAN
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