Mon, 05 Feb 2018

Package pubh updated to version 0.1.7 with previous version 0.1.6 dated 2018-01-19

Title: A Toolbox for Public Health and Epidemiology
Description: A toolbox for making R functions and capabilities more accessible to students and professionals from Epidemiology and Public Health related disciplines. Includes a function to report coefficients and confidence intervals from models using robust standard errors (when available), functions that expand lattice plots and functions relevant for introductory papers in Epidemiology or Public Health. Please note that use of the provided data sets is for educational purposes only.
Author: Josie Athens [aut, cre], Deepayan Sarkar [ctb], Mark Stevenson [ctb], Simon Firestone [ctb], Cord Heuer [ctb], Jim Robison-Cox [ctb], Frank Harell [ctb], John Fox [ctb], Kazuki Yoshida [ctb], Tomas Aragon [ctb], R-Core [ctb]
Maintainer: Josie Athens <josie.athens@otago.ac.nz>

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More information about pubh at CRAN
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Package brainGraph updated to version 2.0.0 with previous version 1.0.0 dated 2017-04-10

Title: Graph Theory Analysis of Brain MRI Data
Description: A set of tools for performing graph theory analysis of brain MRI data. It works with data from a Freesurfer analysis (cortical thickness, volumes, local gyrification index, surface area), diffusion tensor tractography data (e.g., from FSL) and resting-state fMRI data (e.g., from DPABI). It contains a graphical user interface for graph visualization and data exploration, along with several functions for generating useful figures.
Author: Christopher G. Watson <cgwatson@bu.edu>
Maintainer: Christopher G. Watson <cgwatson@bu.edu>

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Package ADMM updated to version 0.2.1 with previous version 0.2.0 dated 2018-01-26

Title: Algorithms using Alternating Direction Method of Multipliers
Description: Provides algorithms to solve popular optimization problems in statistics such as regression or denoising based on Alternating Direction Method of Multipliers (ADMM). See Boyd et al (2010) <doi:10.1561/2200000016> for complete introduction to the method.
Author: Kisung You [aut, cre] (<https://orcid.org/0000-0002-8584-459X>)
Maintainer: Kisung You <kyou@nd.edu>

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Package seriation updated to version 1.2-3 with previous version 1.2-2 dated 2017-05-09

Title: Infrastructure for Ordering Objects Using Seriation
Description: Infrastructure for seriation with an implementation of several seriation/sequencing techniques to reorder matrices, dissimilarity matrices, and dendrograms. Also provides (optimally) reordered heatmaps, color images and clustering visualizations like dissimilarity plots, and visual assessment of cluster tendency plots (VAT and iVAT).
Author: Michael Hahsler [aut, cre, cph], Christian Buchta [aut, cph], Kurt Hornik [aut, cph], Fionn Murtagh [ctb, cph], Michael Brusco [ctb, cph], Stephanie Stahl [ctb, cph], Hans-Friedrich Koehn [ctb, cph]
Maintainer: Michael Hahsler <mhahsler@lyle.smu.edu>

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Package PAFit updated to version 1.0.0.3 with previous version 1.0.0.1 dated 2017-06-30

Title: Generative Mechanism Estimation in Temporal Complex Networks
Description: Statistical methods for estimating preferential attachment and node fitness generative mechanisms in temporal complex networks are provided.
Author: Thong Pham, Paul Sheridan, Hidetoshi Shimodaira
Maintainer: Thong Pham <thongpham@thongpham.net>

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Package NeuralNetTools updated to version 1.5.1 with previous version 1.5.0 dated 2016-11-24

Title: Visualization and Analysis Tools for Neural Networks
Description: Visualization and analysis tools to aid in the interpretation of neural network models. Functions are available for plotting, quantifying variable importance, conducting a sensitivity analysis, and obtaining a simple list of model weights.
Author: Marcus W. Beck [aut, cre]
Maintainer: Marcus W. Beck <marcusb@sccwrp.org>

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Package lmodel2 updated to version 1.7-3 with previous version 1.7-2 dated 2014-02-24

Title: Model II Regression
Description: Computes model II simple linear regression using ordinary least squares (OLS), major axis (MA), standard major axis (SMA), and ranged major axis (RMA).
Author: Pierre Legendre
Maintainer: Jari Oksanen <jari.oksanen@oulu.fi>

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Package qualtRics updated to version 3.0 with previous version 2.2 dated 2017-10-27

Title: Download Qualtrics Survey Data Directly into R
Description: Qualtrics <https://www.qualtrics.com/about/> allows users to collect online data through surveys. This package contains convenience functions to pull survey results straight into R using the Qualtrics API. See <https://api.qualtrics.com/> for more information about the Qualtrics API. This package is community-maintained and is not officially supported by Qualtrics.
Author: Jasper Ginn
Maintainer: Jasper Ginn <jasperginn@gmail.com>

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Package PET updated to version 0.5.0 with previous version 0.4.9 dated 2010-08-23

Title: Simulation and Reconstruction of PET Images
Description: Implementation of different analytic/direct and iterative reconstruction methods of radon transformed data such as PET data. It also offer the possibility to simulate PET data.
Author: Joern Schulz <jschulz78@web.de> Peter Toft <pto@imm.dtu.dk> Jesper James Jensen <jjj@oedan.dk> Peter Philipsen <pap@imm.dtu.dk>
Maintainer: Joern Schulz <jschulz78@web.de>

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Package lolR updated to version 1.0.1 with previous version 1.0 dated 2018-02-05

Title: Linear Optimal Low-Rank Projection (LOL)
Description: Supervised learning techniques designed for the situation when the dimensionality exceeds the sample size have a tendency to overfit as the dimensionality of the data increases. To remedy this High dimensionality; low sample size (HDLSS) situation, we attempt to learn a lower-dimensional representation of the data before learning a classifier. That is, we project the data to a situation where the dimensionality is more manageable, and then are able to better apply standard classification or clustering techniques since we will have fewer dimensions to overfit. A number of previous works have focused on how to strategically reduce dimensionality in the unsupervised case, yet in the supervised HDLSS regime, few works have attempted to devise dimensionality reduction techniques that leverage the labels associated with the data. In this package, we provide several methods for feature extraction, some utilizing labels and some not, along with easily extensible utilities to simplify cross-validative efforts to identify the best feature extraction method. Additionally, we include a series of adaptable benchmark simulations to serve as a standard for future investigative efforts into supervised HDLSS. Finally, we produce a comprehensive comparison of the included algorithms across a range of benchmark simulations and real data applications.
Author: Eric Bridgeford [aut, cre], Minh Tang [ctb], Jason Yim [ctb], Joshua Vogelstein [ths]
Maintainer: Eric Bridgeford <ericwb95@gmail.com>

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Package GetTDData updated to version 1.3.1 with previous version 1.3 dated 2017-09-14

Title: Get Data for Brazilian Bonds (Tesouro Direto)
Description: Downloads and aggregates data for Brazilian government issued bonds directly from the website of Tesouro Direto <http://www.tesouro.fazenda.gov.br/tesouro-direto-balanco-e-estatisticas>.
Author: Marcelo Perlin [aut, cre]
Maintainer: Marcelo Perlin <marceloperlin@gmail.com>

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Package eulerr updated to version 4.0.0 with previous version 3.1.0 dated 2018-01-02

Title: Area-Proportional Euler and Venn Diagrams with Circles or Ellipses
Description: Generate area-proportional Euler diagrams using numerical optimization. An Euler diagram is a generalization of a Venn diagram, relaxing the criterion that all interactions need to be represented. Diagrams may be fit with ellipses and circles via a wide range of inputs and can be visualized in numerous ways.
Author: Johan Larsson [aut, cre], A. Jonathan R. Godfrey [ctb], Tim Kelley [ctb] (original Nelder-Mead code), David H. Eberly [ctb] (geometric algorithms), Peter Gustafsson [ctb], Emanuel Huber [ctb] (root solver code)
Maintainer: Johan Larsson <johanlarsson@outlook.com>

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Package entropart updated to version 1.5-3 with previous version 1.4-8 dated 2017-11-22

Title: Entropy Partitioning to Measure Diversity
Description: Measurement and partitioning of diversity, based on Tsallis entropy, following Marcon and Herault (2015) <doi:10.18637/jss.v067.i08>. entropart provides functions to calculate alpha, beta and gamma diversity of communities, including phylogenetic and functional diversity. Estimation-bias corrections are available.
Author: Eric Marcon [aut, cre], Bruno Herault [aut]
Maintainer: Eric Marcon <eric.marcon@ecofog.gf>

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New package dvmisc with initial version 1.1.2
Package: dvmisc
Type: Package
Title: Faster Computation of Common Statistics and Miscellaneous Functions
Version: 1.1.2
Date: 2018-02-05
Author: Dane R. Van Domelen
Maintainer: Dane R. Van Domelen <vandomed@gmail.com>
Description: Faster versions of base R functions (e.g. mean, standard deviation, covariance, weighted mean), mostly written in C++, along with miscellaneous functions for various purposes (e.g. create histogram with fitted probability density function or probability mass function curve, create body mass index groups, assess linearity assumption in logistic regression).
License: GPL-2
Depends: rbenchmark
Imports: graphics, MASS, Rcpp (>= 0.12.15), stats, utils
LinkingTo: Rcpp
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2018-02-05 15:27:45 UTC; Dane
Repository: CRAN
Date/Publication: 2018-02-05 22:19:18 UTC

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Package ChannelAttribution updated to version 1.12 with previous version 1.11 dated 2018-02-02

Title: Markov Model for the Online Multi-Channel Attribution Problem
Description: Advertisers use a variety of online marketing channels to reach consumers and they want to know the degree each channel contributes to their marketing success. This is called the online multi-channel attribution problem. This package contains a probabilistic algorithm for the attribution problem. The model uses a k-order Markov representation to identify structural correlations in the customer journey data. The package also contains three heuristic algorithms (first-touch, last-touch and linear-touch approach) for the same problem. The algorithms are implemented in C++.
Author: Davide Altomare, David Loris
Maintainer: Davide Altomare <davide.altomare@gmail.com>

Diff between ChannelAttribution versions 1.11 dated 2018-02-02 and 1.12 dated 2018-02-05

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Package irtDemo updated to version 0.1.3 with previous version 0.1.2 dated 2016-08-21

Title: Item Response Theory Demo Collection
Description: Includes a collection of shiny applications to demonstrate or to explore fundamental item response theory (IRT) concepts such as estimation, scoring, and multidimensional IRT models.
Author: Metin Bulus [aut,cre] Wes Bonifay [aut,cre]
Maintainer: Metin Bulus <bulusmetin@gmail.com>

Diff between irtDemo versions 0.1.2 dated 2016-08-21 and 0.1.3 dated 2018-02-05

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Package frailtyEM updated to version 0.8.3 with previous version 0.8.1 dated 2018-01-25

Title: Fitting Frailty Models with the EM Algorithm
Description: Contains functions for fitting shared frailty models with a semi-parametric baseline hazard with the Expectation-Maximization algorithm. Supported data formats include clustered failures with left truncation and recurrent events in gap-time or Andersen-Gill format. Several frailty distributions, such as the the gamma, positive stable and the Power Variance Family are supported.
Author: Theodor Adrian Balan, Hein Putter
Maintainer: Theodor Adrian Balan <t.a.balan@lumc.nl>

Diff between frailtyEM versions 0.8.1 dated 2018-01-25 and 0.8.3 dated 2018-02-05

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Package sim1000G updated to version 1.37 with previous version 1.33 dated 2017-12-15

Title: Genotype Simulations for Rare or Common Variants Using Haplotypes from 1000 Genomes
Description: Generates realistic simulated genetic data in families or unrelated individuals.
Author: Apostolos Dimitromanolakis <apostolis@live.ca>, Jingxiong Xu <jingxiong.xu@mail.utoronto.ca>, Agnieszka Krol <krol@lunenfeld.ca>, Laurent Briollais <laurent@lunenfeld.ca>
Maintainer: Apostolos Dimitromanolakis <apostolis@live.ca>

Diff between sim1000G versions 1.33 dated 2017-12-15 and 1.37 dated 2018-02-05

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Package SOMbrero updated to version 1.2-3 with previous version 1.2-2 dated 2017-09-20

Title: SOM Bound to Realize Euclidean and Relational Outputs
Description: The stochastic (also called on-line) version of the Self-Organising Map (SOM) algorithm is provided. Different versions of the algorithm are implemented, for numeric and relational data and for contingency tables as described, respectively, in Kohonen (2001) <isbn:3-540-67921-9>, Olteanu & Villa-Vialaneix (2005) <doi:10.1016/j.neucom.2013.11.047> and Cottrell et al (2004) <doi:10.1016/j.neunet.2004.07.010>. The package also contains many plotting features (to help the user interpret the results) and a graphical user interface based on 'shiny'.
Author: Nathalie Villa-Vialaneix [aut, cre], Jerome Mariette [aut], Madalina Olteanu [aut], Fabrice Rossi [aut], Laura Bendhaiba [ctb], Julien Boelaert [ctb]
Maintainer: Nathalie Villa-Vialaneix <nathalie.villa-vialaneix@inra.fr>

Diff between SOMbrero versions 1.2-2 dated 2017-09-20 and 1.2-3 dated 2018-02-05

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New package RaPKod with initial version 0.9
Package: RaPKod
Type: Package
Title: Random Projection Kernel Outlier Detector
Version: 0.9
Date: 2018-01-30
Author: Jeremie Kellner
Maintainer: Jeremie Kellner <jeremie.kellner@ed.univ-lille1.fr>
Description: Kernel method that performs online outlier detection through random low-dimensional projections in a kernel space. Controls the probability of false alarm error. See Kellner J., "Gaussian models and kernel methods" (2016), PhD thesis for reference <https://ori-nuxeo.univ-lille1.fr/nuxeo/site/esupversions/789d119a-6763-4205-972f-b318cd4fdb27>.
License: GPL (>= 2.0)
Imports: Rcpp (>= 0.12.15)
LinkingTo: Rcpp, RcppArmadillo
Depends: proxy, kernlab, MASS
NeedsCompilation: yes
Packaged: 2018-02-05 16:08:39 UTC; CompteZero
Repository: CRAN
Date/Publication: 2018-02-05 18:18:21 UTC

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Package MBC updated to version 0.10-4 with previous version 0.10-3 dated 2017-12-04

Title: Multivariate Bias Correction of Climate Model Outputs
Description: Calibrate and apply multivariate bias correction algorithms for climate model simulations of multiple climate variables. Three methods described by Cannon (2016) <doi:10.1175/JCLI-D-15-0679.1> and Cannon (2018) <doi:10.1007/s00382-017-3580-6> are implemented: (i) MBC Pearson correlation (MBCp), (ii) MBC rank correlation (MBCr), and (iii) MBC N-dimensional PDF transform (MBCn).
Author: Alex J. Cannon
Maintainer: Alex J. Cannon <alex.cannon@canada.ca>

Diff between MBC versions 0.10-3 dated 2017-12-04 and 0.10-4 dated 2018-02-05

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Package kofdata updated to version 0.1.3 with previous version 0.1.1 dated 2018-01-04

Title: Get Data from the 'KOF Datenservice' API
Description: Read Swiss time series data from the 'KOF Datenservice' API, <https://datenservice.kof.ethz.ch>. The API provides macroeconomic survey data, business cycle and further macro economic time series about Switzerland. The package itself is a set of wrappers around the 'KOF Datenservice' API. The 'kofdata' package is able to consume public information as well as data that requires an API token.
Author: Matthias Bannert [aut, cre], Severin Thoeni [aut]
Maintainer: Matthias Bannert <bannert@kof.ethz.ch>

Diff between kofdata versions 0.1.1 dated 2018-01-04 and 0.1.3 dated 2018-02-05

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New package ggbuildr with initial version 0.1.0
Package: ggbuildr
Type: Package
Title: Save Incremental Builds of Plots
Version: 0.1.0
Author: Jongbin Jung
Maintainer: Jongbin Jung <me@jongbin.com>
Description: Saves a 'ggplot' object into multiple files, each with a layer added incrementally. Generally to be used in presentation slides. Flexible enough to allow different file types for the final complete plot, and intermediate builds.
License: GPL-3 | file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Suggests: testthat
Depends: ggplot2
Imports: purrr, readr, tools
NeedsCompilation: no
Packaged: 2018-02-05 18:09:51 UTC; jongbin
Repository: CRAN
Date/Publication: 2018-02-05 18:45:42 UTC

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New package drtmle with initial version 1.0.2
Package: drtmle
Title: Doubly-Robust Nonparametric Estimation and Inference
Version: 1.0.2
Authors@R: c( person("David", "Benkeser", email = "benkeser@emory.edu", role = c("aut", "cre","cph"), comment = c(ORCID = "0000-0002-1019-8343")), person("Nima", "Hejazi", email = "nhejazi@berkeley.edu", role = "ctb", comment = c(ORCID = "0000-0002-7127-2789")))
Description: Targeted minimum loss-based estimators of counterfactual means and causal effects that are doubly-robust with respect both to consistency and asymptotic normality (Benkeser et al (2017), <doi:10.1093/biomet/asx053>; MJ van der Laan (2014), <doi:10.1515/ijb-2012-0038>).
Depends: R (>= 3.2.0)
Imports: SuperLearner, plyr, np, future, doFuture, future.batchtools
Suggests: testthat, knitr, rmarkdown, gam, quadprog, nloptr, parallel, snow
License: MIT + file LICENSE
URL: https://github.com/benkeser/drtmle
BugReports: https://github.com/benkeser/drtmle/issues
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-02-05 16:44:33 UTC; benkeser
Author: David Benkeser [aut, cre, cph] (<https://orcid.org/0000-0002-1019-8343>), Nima Hejazi [ctb] (<https://orcid.org/0000-0002-7127-2789>)
Maintainer: David Benkeser <benkeser@emory.edu>
Repository: CRAN
Date/Publication: 2018-02-05 18:59:00 UTC

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New package cepreader with initial version 1.1-2
Package: cepreader
Title: Read 'CEP' and Legacy 'CANOCO' Files
Version: 1.1-2
Date: 2018-02-05
Authors@R: c(person("Jari", "Oksanen", role=c("aut","cre"), email="jhoksane@gmail.com"), person(given = c("Gavin", "L."), family = "Simpson", role = c("aut"), email = "ucfagls@gmail.com", comment = c(ORCID = "0000-0002-9084-8413")))
Description: Read Condensed Cornell Ecology Program ('CEP') and legacy 'CANOCO' files into R data frames.
License: MIT + file LICENCE
BugReports: https://github.com/vegandevs/cepreader/issues
URL: https://cran.r-project.org/, https://github.com/vegandevs/cepreader/
NeedsCompilation: yes
Packaged: 2018-02-05 17:29:26 UTC; jarioksa
Author: Jari Oksanen [aut, cre], Gavin L. Simpson [aut] (<https://orcid.org/0000-0002-9084-8413>)
Maintainer: Jari Oksanen <jhoksane@gmail.com>
Repository: CRAN
Date/Publication: 2018-02-05 18:43:20 UTC

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Package biogas updated to version 1.10.0 with previous version 1.9.0 dated 2018-01-03

Title: Process Biogas Data and Predict Biogas Production
Description: High- and low-level functions for processing biogas data and predicting biogas production. Molar mass and calculated oxygen demand (COD') can be determined from a chemical formula. Measured gas volume can be corrected for water vapor and to (possibly user-defined) standard temperature and pressure. Gas quantity can be converted between volume, mass, and moles. Gas composition, cumulative production, or other variables can be interpolated to a specified time. Cumulative biogas and methane production (and rates) can be calculated using volumetric, manometric, or gravimetric methods for any number of reactors. With cumulative methane production data and data on reactor contents, biochemical methane potential (BMP) can be calculated and summarized, including subtraction of the inoculum contribution and normalization by substrate mass. Cumulative production and production rates can be summarized in several different ways (e.g., omitting normalization) using the same function. Biogas quantity and composition can be predicted from substrate composition and additional, optional data. Lastly, inoculum and substrate mass can be determined for planning BMP experiments.
Author: Sasha D. Hafner [aut, cre], Charlotte Rennuit [aut], Jin Mi Triolo [ctb], Ali Heidarzadeh Vazifehkhoran [ctb]
Maintainer: Sasha D. Hafner <sasha.hafner@eng.au.dk>

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Package bestNormalize updated to version 1.0.1 with previous version 1.0.0 dated 2018-01-04

Title: Normalizing Transformation Functions
Description: Estimate a suite of normalizing transformations, including a new adaptation of a technique based on ranks which can guarantee normally distributed transformed data if there are no ties: ordered quantile normalization (ORQ). ORQ normalization combines a rank-mapping approach with a shifted logit approximation that allows the transformation to work on data outside the original domain. It is also able to handle new data within the original domain via linear interpolation. The package is built to estimate the best normalizing transformation for a vector consistently and accurately. It implements the Box-Cox transformation, the Yeo-Johnson transformation, three types of Lambert WxF transformations, and the ordered quantile normalization transformation.
Author: Ryan Andrew Peterson [aut, cre]
Maintainer: Ryan Andrew Peterson <ryan-peterson@uiowa.edu>

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Package migest updated to version 1.7.4 with previous version 1.7.3 dated 2016-10-26

Title: Methods for the Indirect Estimation of Bilateral Migration
Description: Indirect methods for estimating bilateral migration flows in the presence of partial or missing data. Methods might be relevant to other categorical data situations on non-migration data, where for example, marginal totals are known and only auxiliary bilateral data is available.
Author: Guy J. Abel
Maintainer: Guy J. Abel <g.j.abel@gmail.com>

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Package mapmisc updated to version 1.7.0 with previous version 1.6.3 dated 2017-08-29

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 JuniperKernel updated to version 1.2.3.0 with previous version 1.2.2.0 dated 2018-01-16

Title: Kernel for 'Jupyter'
Description: Provides a full implementation of the 'Jupyter' <http://jupyter.org/> messaging protocol in C++ by leveraging 'Rcpp' and 'Xeus' <https://github.com/QuantStack/xeus>. 'Jupyter' supplies an interactive computing environment and a messaging protocol defined over 'ZeroMQ' for multiple programming languages. This package implements the 'Jupyter' kernel interface so that 'R' is exposed to this interactive computing environment. 'ZeroMQ' functionality is provided by the 'pbdZMQ' package. 'Xeus' is a C++ library that facilitates the implementation of kernels for 'Jupyter'. Additionally, 'Xeus' provides an interface to libraries that exist in the 'Jupyter' ecosystem for building widgets, plotting, and more <https://blog.jupyter.org/interactive-workflows-for-c-with-jupyter-fe9b54227d92>. 'JuniperKernel' uses 'Xeus' as a library for the 'Jupyter' messaging protocol.
Author: Spencer Aiello [aut, cre, cph], Wei-Chen Chen [ctb], Stephan Brumme [cph], Jake Luciani [cph], Tony Plate [cph], Matthieu Decorde [cph], RStudio (Hadley Wickham) [cph], Sylvain Corlay [cph], Johan Mabille [cph], Niels Lohmann [cph]
Maintainer: Spencer Aiello <spnrpa@gmail.com>

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Package sjPlot updated to version 2.4.1 with previous version 2.4.0 dated 2017-10-19

Title: Data Visualization for Statistics in Social Science
Description: Collection of plotting and table output functions for data visualization. Results of various statistical analyses (that are commonly used in social sciences) can be visualized using this package, including simple and cross tabulated frequencies, histograms, box plots, (generalized) linear models, mixed effects models, principal component analysis and correlation matrices, cluster analyses, scatter plots, stacked scales, effects plots of regression models (including interaction terms) and much more. This package supports labelled data.
Author: Daniel Lüdecke [aut, cre], Carsten Schwemmer [ctb]
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

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Package shinyKGode updated to version 1.0.3 with previous version 1.0.1 dated 2017-11-14

Title: An Interactive Application for ODE Parameter Inference Using Gradient Matching
Description: An interactive Shiny application to perform fast parameter inference on dynamical systems (described by ordinary differential equations) using gradient matching. Please see the project page for more details.
Author: Joe Wandy
Maintainer: Joe Wandy <joe.wandy@glasgow.ac.uk>

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Package networktools updated to version 1.1.1 with previous version 1.1.0 dated 2017-08-09

Title: Tools for Identifying Important Nodes in Networks
Description: Includes assorted tools for network analysis. Useful for calculating and plotting expected influence, bridge centrality, and impact statistics.
Author: Payton Jones [aut, cre]
Maintainer: Payton Jones <payton_jones@g.harvard.edu>

Diff between networktools versions 1.1.0 dated 2017-08-09 and 1.1.1 dated 2018-02-05

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New package zscorer with initial version 0.1.0
Package: zscorer
Type: Package
Title: Child Anthropometry z-Score Calculator
Version: 0.1.0
Authors@R: c( person("Mark", "Myatt", email = "mark@brixtonhealth.com", role = "aut"), person("Ernest", "Guevarra", email = "ernestgmd@gmail.com", role = c("aut", "cre")))
Description: A tool for calculating z-scores for weight-for- age, length/height-for-age, and weight-for-length/height, based on the WHO Child Growth Standards.
Depends: R (>= 2.10)
License: AGPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Suggests: testthat, knitr, rmarkdown, shiny, shinythemes
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-02-05 04:48:04 UTC; ernest
Author: Mark Myatt [aut], Ernest Guevarra [aut, cre]
Maintainer: Ernest Guevarra <ernestgmd@gmail.com>
Repository: CRAN
Date/Publication: 2018-02-05 15:24:00 UTC

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Package TreeBUGS updated to version 1.3.0 with previous version 1.2.0 dated 2018-01-19

Title: Hierarchical Multinomial Processing Tree Modeling
Description: User-friendly analysis of hierarchical multinomial processing tree (MPT) models that are often used in cognitive psychology. Implements the latent-trait MPT approach (Klauer, 2010) <DOI:10.1007/s11336-009-9141-0> and the beta-MPT approach (Smith & Batchelder, 2010) <DOI:10.1016/j.jmp.2009.06.007> to model heterogeneity of participants. MPT models are conveniently specified by an .eqn-file as used by other MPT software and data are provided by a .csv-file or directly in R. Models are either fitted by calling JAGS or by an MPT-tailored Gibbs sampler in C++ (only for nonhierarchical and beta MPT models). Provides tests of heterogeneity and MPT-tailored summaries and plotting functions.
Author: Daniel W. Heck [aut, cre], Nina R. Arnold [aut, dtc], Denis Arnold [aut], Alexander Ly [ctb]
Maintainer: Daniel W. Heck <heck@uni-mannheim.de>

Diff between TreeBUGS versions 1.2.0 dated 2018-01-19 and 1.3.0 dated 2018-02-05

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Package PLMIX updated to version 2.0 with previous version 1.0 dated 2016-12-21

Title: Bayesian Analysis of Finite Mixtures of Plackett-Luce Models for Partial Rankings/Orderings
Description: Fit finite mixtures of Plackett-Luce models for partial top rankings/orderings within the Bayesian framework. It provides MAP point estimates via EM algorithm and posterior MCMC simulations via Gibbs Sampling. It also fits MLE as a special case of the noninformative Bayesian analysis with vague priors. In addition to inferential techniques, the package assists other fundamental phases of a model-based analysis for partial rankings/orderings, by including functions for data manipulation, simulation, descriptive summary, model selection and goodness-of-fit evaluation.
Author: Cristina Mollica [aut, cre], Luca Tardella [aut]
Maintainer: Cristina Mollica <cristina.mollica@uniroma1.it>

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New package nord with initial version 0.0.1
Package: nord
Title: Arctic Ice Studio's Nord and Group of Seven Inspired Colour Palettes
Version: 0.0.1
Authors@R: person("Jake", "Kaupp", email = "jkaupp@gmail.com", role = c("cre", "aut"))
Description: Provides the Arctic Ice Studio's Nord and Group of Seven inspired colour palettes.
Depends: R (>= 3.4.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Imports: ggplot2
Suggests: testthat
NeedsCompilation: no
Packaged: 2018-02-05 04:03:04 UTC; rstudio
Author: Jake Kaupp [cre, aut]
Maintainer: Jake Kaupp <jkaupp@gmail.com>
Repository: CRAN
Date/Publication: 2018-02-05 15:17:00 UTC

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Package multiApply updated to version 1.0.0 with previous version 0.0.1 dated 2017-07-17

Title: Apply Functions to Multiple Multidimensional Arguments
Description: The base apply function and its variants, as well as the related functions in the 'plyr' package, typically apply user-defined functions to a single argument (or a list of vectorized arguments in the case of mapply). The 'multiApply' package extends this paradigm to functions taking a list of multiple unidimensional or multidimensional arguments (or combinations thereof) as input, which can have different numbers of dimensions as well as different dimension lengths.
Author: BSC-CNS [aut, cph], Alasdair Hunter [aut, cre], Nicolau Manubens [aut]
Maintainer: Alasdair Hunter <alasdair.hunter@bsc.es>

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Package fingertipsR updated to version 0.1.5 with previous version 0.1.4 dated 2018-02-02

Title: Fingertips Data for Public Health
Description: Fingertips (<http://fingertips.phe.org.uk/>) contains data for many indicators of public health in England. The underlying data is now more easily accessible by making use of the API.
Author: Sebastian Fox [aut, cre], Julian Flowers [aut, ctb], Crown Copyright 2018 [cph]
Maintainer: Sebastian Fox <sebastian.fox@phe.gov.uk>

Diff between fingertipsR versions 0.1.4 dated 2018-02-02 and 0.1.5 dated 2018-02-05

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Package OutliersO3 updated to version 0.5.1 with previous version 0.2.1 dated 2017-09-26

Title: Draws Overview of Outliers (O3) Plots
Description: Potential outliers are identified for all combinations of a dataset's variables. The available methods are HDoutliers() from the package 'HDoutliers', FastPCS() from the package 'FastPCS', mvBACON() from 'robustX', adjOutlyingness() from 'robustbase', DectectDeviatingCells() from 'cellWise', covMcd() from 'robustbase'.
Author: Antony Unwin
Maintainer: Antony Unwin <unwin@math.uni-augsburg.de>

Diff between OutliersO3 versions 0.2.1 dated 2017-09-26 and 0.5.1 dated 2018-02-05

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Package ROlogit updated to version 0.1.1 with previous version 0.1.0 dated 2018-01-29

Title: Fit Rank-Ordered Logit (RO-Logit) Model
Description: Implements the rank-ordered logit (RO-logit) model for stratified analysis of continuous outcomes introduced by Tan et al. (2017) <doi:10.1177/0962280217747309>. Model diagnostics based on the heuristic residuals and estimates in linear scales are available from the package, and outcomes with ties are supported.
Author: Tan Chuen Seng, Ning Yilin
Maintainer: Ning Yilin <ningyilinnyl@gmail.com>

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New package lolR with initial version 1.0
Package: lolR
Type: Package
Title: Linear Optimal Low-Rank Projection
Version: 1.0
Date: 2018-02-02
Authors@R: c(person("Eric", "Bridgeford", role = c("aut", "cre"), email = "ericwb95@gmail.com"), person("Minh", "Tang", role="ctb", email="minh@jhu.edu"), person("Jason", "Yim", role = "ctb", email = "jasonkyuyim@gmail.com"), person("Joshua", "Vogelstein", role = "ths", email = "jovo@jhu.edu"))
Maintainer: Eric Bridgeford <ericwb95@gmail.com>
Description: Supervised learning techniques designed for the situation when the dimensionality exceeds the sample size have a tendency to overfit as the dimensionality of the data increases. To remedy this High dimensionality; low sample size (HDLSS) situation, we attempt to learn a lower-dimensional representation of the data before learning a classifier. That is, we project the data to a situation where the dimensionality is more manageable, and then are able to better apply standard classification or clustering techniques since we will have fewer dimensions to overfit. A number of previous works have focused on how to strategically reduce dimensionality in the unsupervised case, yet in the supervised HDLSS regime, few works have attempted to devise dimensionality reduction techniques that leverage the labels associated with the data. In this package, we provide several methods for feature extraction, some utilizing labels and some not, along with easily extensible utilities to simplify cross-validative efforts to identify the best feature extraction method. Additionally, we include a series of adaptable benchmark simulations to serve as a standard for future investigative efforts into supervised HDLSS. Finally, we produce a comprehensive comparison of the included algorithms across a range of benchmark simulations and real data applications.
Depends: R (>= 3.4.0)
License: GPL-2
URL: https://github.com/neurodata/lol
Imports: ggplot2, abind, MASS, irlba
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown, parallel, randomForest, latex2exp
NeedsCompilation: no
Packaged: 2018-02-02 22:14:59 UTC; eric
Author: Eric Bridgeford [aut, cre], Minh Tang [ctb], Jason Yim [ctb], Joshua Vogelstein [ths]
Repository: CRAN
Date/Publication: 2018-02-05 12:46:30 UTC

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Package xtensor (with last version 0.4.0-0) was removed from CRAN

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

2017-12-18 0.4.0-0
2017-11-10 0.3.0-0
2017-10-23 0.2.0-0
2017-09-15 0.1.1-0
2017-09-11 0.1.0-0

Permanent link
Package ukbtools updated to version 0.10.1 with previous version 0.10.0 dated 2017-11-27

Title: Manipulate and Explore UK Biobank Data
Description: A set of tools to create a UK Biobank <http://www.ukbiobank.ac.uk/> dataset from a UKB fileset (.tab, .r, .html), visualize primary demographic data for a sample subset, query ICD diagnoses, retrieve genetic metadata, read and write standard file formats for genetic analyses.
Author: Ken Hanscombe [aut, cre]
Maintainer: Ken Hanscombe <ken.hanscombe@gmail.com>

Diff between ukbtools versions 0.10.0 dated 2017-11-27 and 0.10.1 dated 2018-02-05

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Package population updated to version 0.2 with previous version 0.1 dated 2015-12-23

Title: Models for Simulating Populations
Description: Run population simulations using an Individual-Based Model (IBM) compiled in C.
Author: Guillaume Chapron
Maintainer: Guillaume Chapron <gchapron@carnivoreconservation.org>

Diff between population versions 0.1 dated 2015-12-23 and 0.2 dated 2018-02-05

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New package rsimsum with initial version 0.1.0
Package: rsimsum
Version: 0.1.0
Title: Analysis of Simulation Studies Including Monte Carlo Error
Description: Summarise results from simulation studies and compute Monte Carlo standard errors of commonly used summary statistics. This package is modelled on the 'simsum' user-written command in 'Stata' (See White I.R., 2010 <http://www.stata-journal.com/article.html?article=st0200>).
Authors@R: c(person("Alessandro", "Gasparini", role = c("aut", "cre"), email = "ag475@leicester.ac.uk"), person("Ian R.", "White", role = "aut"))
License: GPL (>= 3)
Depends: R (>= 2.10)
Imports: checkmate, stats
Suggests: covr, devtools, eha, ggplot2, knitr, rmarkdown, rstpm2, survival, testthat, tidyverse
URL: https://github.com/ellessenne/rsimsum
BugReports: https://github.com/ellessenne/rsimsum/issues
VignetteBuilder: knitr
RoxygenNote: 6.0.1
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2018-02-01 10:40:19 UTC; ag475
Author: Alessandro Gasparini [aut, cre], Ian R. White [aut]
Maintainer: Alessandro Gasparini <ag475@leicester.ac.uk>
Repository: CRAN
Date/Publication: 2018-02-05 10:07:10 UTC

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Package pbdBASE updated to version 0.4-5.1 with previous version 0.4-5 dated 2016-10-12

Title: Programming with Big Data -- Base Wrappers for Distributed Matrices
Description: An interface to and extensions for the 'PBLAS' and 'ScaLAPACK' numerical libraries. This enables R to utilize distributed linear algebra for codes written in the 'SPMD' fashion. This interface is deliberately low-level and mimics the style of the native libraries it wraps. For a much higher level way of managing distributed matrices, see the 'pbdDMAT' package.
Author: Drew Schmidt [aut, cre], Wei-Chen Chen [aut], George Ostrouchov [aut], Pragneshkumar Patel [aut], Ewan Higgs [ctb]
Maintainer: ORPHANED

Diff between pbdBASE versions 0.4-5 dated 2016-10-12 and 0.4-5.1 dated 2018-02-05

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New package NetLogoR with initial version 0.3.1
Package: NetLogoR
Title: A Port of 'NetLogo' Functions and Language to R
Description: Easily create agent-based models in R following the 'NetLogo' framework (Wilensky, 1999; <http://ccl.northwestern.edu/netlogo/>). 'NetLogoR' provides classes to represent 'patches' (raster cells) and 'turtles' (individuals), the necessary 'NetLogo' primitives (<https://ccl.northwestern.edu/netlogo/docs/dictionary.html>), and complementary functions to easily build agent-based models or translate 'NetLogo' models in R. A programming guide derived from the 'NetLogo' Programming Guide (<https://ccl.northwestern.edu/netlogo/docs/programming.html>) and a dictionary of 'NetLogo' primitives (<https://ccl.northwestern.edu/netlogo/docs/dictionary.html>) equivalences are available. As examples, three 'NetLogo' models (Ants, <http://ccl.northwestern.edu/netlogo/models/Ants>; Butterfly, Railsback and Grimm, 2012; Wolf-Sheep-Predation, <http://ccl.northwestern.edu/netlogo/models/WolfSheepPredation>) were translated in R language using 'NetLogoR'. NOTE: To increment 'time', these functions can use a for loop or can be integrated with a discrete event simulator, such as 'SpaDES' (<https://cran.r-project.org/package=SpaDES>). The suggested package 'fastshp' can be installed with 'install.packages("fastshp", repos = "http://rforge.net", type = "source")'.
URL: http://netlogor.predictiveecology.org
Version: 0.3.1
Date: 2018-01-31
Authors@R: c( person("Sarah", "Bauduin", email = "sarahbauduin@hotmail.fr", role = c("aut", "cre")), person("Eliot J B", "McIntire", email = "eliot.mcintire@canada.ca", role = c("aut")), person("Alex M", "Chubaty", email = "alexander.chubaty@canada.ca", role = c("aut")), person("Her Majesty the Queen in Right of Canada, as represented by the Minister of Natural Resources Canada", role = "cph") )
Depends: R (>= 3.3.0), raster
Imports: abind, car, CircStats, data.table, grDevices, Hmisc, matrixStats, methods, plyr, quickPlot (>= 0.1.2), sp, SpaDES.tools, stats, rgeos
Suggests: fastshp, knitr, magrittr, microbenchmark, rmarkdown, SpaDES.core, testthat
License: GPL-3
VignetteBuilder: knitr, rmarkdown
BugReports: https://github.com/PredictiveEcology/NetLogoR/issues
ByteCompile: yes
LazyData: true
RoxygenNote: 6.0.1
Additional_repositories: https://rforge.net
Collate: 'Agent-classes.R' 'Classes.R' 'NetLogoR-package.R' 'worldNLR-classes-methods.R' 'agentMatrix-Class-methods.R' 'agentset-functions.R' 'function-arguments.R' 'patch-functions.R' 'plot.R' 'world-functions.R' 'quickPlot.R' 'spades-functions.R' 'turtle-functions.R'
NeedsCompilation: no
Packaged: 2018-02-01 05:46:39 UTC; emcintir
Author: Sarah Bauduin [aut, cre], Eliot J B McIntire [aut], Alex M Chubaty [aut], Her Majesty the Queen in Right of Canada, as represented by the Minister of Natural Resources Canada [cph]
Maintainer: Sarah Bauduin <sarahbauduin@hotmail.fr>
Repository: CRAN
Date/Publication: 2018-02-05 10:03:36 UTC

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New package RiverBuilder with initial version 0.1.0
Package: RiverBuilder
Type: Package
Title: River Generation for Given Data Sets
Version: 0.1.0
Author: Gregory Pasternack <gpast@ucdavis.edu>, Rafaeli Arroyo <rtoarroyo@gmail.com>
Maintainer: Gregory Pasternack <gpast@ucdavis.edu>
Description: Generates graphs, CSV files, and coordinates related to river valleys when calling the riverbuilder() function.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-01-31 23:18:31 UTC; Soronie
Repository: CRAN
Date/Publication: 2018-02-05 09:40:27 UTC

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New package essHist with initial version 1.0.1
Package: essHist
Type: Package
Title: The Essential Histogram
Version: 1.0.1
Date: 2018-01-30
Authors@R: c(person("Housen", "Li", role = c("aut", "cre"), email = "housen.li@outlook.com"), person("Hannes", "Sieling", role = "aut", email = "hsielin@uni-goettingen.de"))
Author: Housen Li [aut, cre], Hannes Sieling [aut]
Maintainer: Housen Li <housen.li@outlook.com>
Description: Provide an optimal histogram, in the sense of probability density estimation and features detection, by means of multiscale variational inference. For details see Li, Munk, Sieling and Walther (2016) <arXiv:1612.07216>.
Depends: R (>= 2.15.3)
License: GPL-3
LazyData: TRUE
Imports: Rcpp (>= 0.12.5)
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2018-01-31 13:11:32 UTC; hli
Repository: CRAN
Date/Publication: 2018-02-05 09:07:08 UTC

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Package psycho updated to version 0.1.0 with previous version 0.0.8 dated 2018-01-10

Title: Efficient and Publishing-Oriented Workflow for Psychological Science
Description: Toolbox for psychologists, neuropsychologists and neuroscientists. It implements methods to create report-ready outputs for statistical models, as well as various convenient statistical functions used in psychological science, such as correlation matrices and normalization.
Author: Dominique Makowski [aut, cre], Viliam Simko [ctb]
Maintainer: Dominique Makowski <dom.makowski@gmail.com>

Diff between psycho versions 0.0.8 dated 2018-01-10 and 0.1.0 dated 2018-02-05

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Package gibble updated to version 0.0.2 with previous version 0.0.1 dated 2017-09-08

Title: Geometry Decomposition
Description: Build a map of path-based geometry, this is a simple description of the number of parts in an object and their basic structure. Translation and restructuring operations for planar shapes and other hierarchical types require a data model with a record of the underlying relationships between elements. The gibble() function creates a geometry map, a simple record of the underlying structure in path-based hierarchical types. There are methods for the planar shape types in the 'sf' and 'sp' packages.
Author: Michael Sumner [aut, cre]
Maintainer: Michael Sumner <mdsumner@gmail.com>

Diff between gibble versions 0.0.1 dated 2017-09-08 and 0.0.2 dated 2018-02-05

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Package rtrie (with last version 0.1.1) was removed from CRAN

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

2017-01-06 0.1.1
2017-01-05 0.1.0

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Package biwavelet (with last version 0.20.11) was removed from CRAN

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2016-08-31 0.20.11
2016-08-28 0.20.10
2016-06-02 0.20.7
2016-05-10 0.20.3
2016-05-05 0.19.2
2016-05-01 0.19.1
2015-05-05 0.17.10
2014-11-07 0.17.5
2014-11-04 0.17.4
2014-03-27 0.17.3
2013-07-16 0.17.1
2013-07-12 0.17
2013-05-18 0.16
2013-04-23 0.15
2013-03-22 0.14
2013-01-11 0.13
2012-10-07 0.12
2012-05-17 0.11
2012-04-28 0.1

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Package dvmisc (with last version 1.1.1) was removed from CRAN

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2017-11-06 1.1.1

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Package matdist (with last version 0.1.1) was removed from CRAN

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2017-12-07 0.1.1
2017-10-16 0.1.0

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Package WeightedROC (with last version 2017.07.12) was removed from CRAN

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2017-07-12 2017.07.12
2017-07-11 2017.07.11
2017-06-19 2017.06.08

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Package Wmisc (with last version 0.3.4) was removed from CRAN

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2018-01-13 0.3.4
2017-10-03 0.3.3
2017-02-10 0.3.2
2016-12-09 0.3.1

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Package Rlinsolve (with last version 0.1.2) was removed from CRAN

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2017-12-07 0.1.2
2017-10-07 0.1.1
2017-09-28 0.1.0

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Package JacobiEigen (with last version 0.2-2) was removed from CRAN

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2015-12-06 0.2-2
2015-11-29 0.2-1
2015-08-09 0.1

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Package Kmisc (with last version 0.5.0) was removed from CRAN

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2013-12-13 0.5.0
2013-02-21 0.4.0
2013-02-21 0.4.0-1
2013-01-22 0.3.0
2012-12-24 0.2.0
2012-12-12 0.1.0

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Package Rdimtools (with last version 0.3.0) was removed from CRAN

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2018-01-30 0.3.0
2018-01-02 0.2.0
2017-11-24 0.1.3
2017-11-13 0.1.2
2017-09-24 0.1.1
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Package RNOmni (with last version 0.1.4) was removed from CRAN

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2017-11-16 0.1.4
2017-11-02 0.1.3
2017-10-29 0.1.2

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Package survivalsvm updated to version 0.0.5 with previous version 0.0.4 dated 2018-01-08

Title: Survival Support Vector Analysis
Description: Performs support vectors analysis for data sets with survival outcome. Three approaches are available in the package: The regression approach takes censoring into account when formulating the inequality constraints of the support vector problem. In the ranking approach, the inequality constraints set the objective to maximize the concordance index for comparable pairs of observations. The hybrid approach combines the regression and ranking constraints in the same model.
Author: Cesaire J. K. Fouodo
Maintainer: Cesaire Fouodo <fouodo@imbs.uni-luebeck.de>

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Package quantoptr updated to version 0.1.3 with previous version 0.1.2 dated 2017-03-12

Title: Algorithms for Quantile- And Mean-Optimal Treatment Regimes
Description: Estimation methods for optimal treatment regimes under three different criteria, namely marginal quantile, marginal mean, and mean absolute difference. For the first two criteria, both one-stage and two-stage estimation method are implemented. A doubly robust estimator for estimating the quantile-optimal treatment regime is also included.
Author: Yu Zhou [cre, aut], Lan Wang [ctb], Ben Sherwood [ctb], Rui Song [ctb]
Maintainer: Yu Zhou <zhou0269@umn.edu>

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