Mon, 18 Feb 2019

Package windfarmGA updated to version 2.2.1 with previous version 1.2.1 dated 2018-03-24

Title: Genetic Algorithm for Wind Farm Layout Optimization
Description: The genetic algorithm is designed to optimize small wind farms with irregular shapes. The algorithm works with a fixed amount of turbines, a fixed rotor radius and a mean wind speed value for every incoming wind direction. If required, it can include a terrain effect model which downloads an 'SRTM' elevation model automatically and loads a Corine Land Cover raster, which has to be downloaded previously. Further information can be found in the description of the function 'windfarmGA'. To start an optimization run, either the function 'windfarmGA' or 'genAlgo' can be used. The function 'windfarmGA' checks the user inputs interactively and then runs the function 'genAlgo'. If the input parameters are already known, an optimization can be run directly via the function 'genAlgo'. Their output is identical.
Author: Sebastian Gatscha
Maintainer: Sebastian Gatscha <sebastian_gatscha@gmx.at>

Diff between windfarmGA versions 1.2.1 dated 2018-03-24 and 2.2.1 dated 2019-02-18

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More information about windfarmGA at CRAN
Permanent link

New package interactions with initial version 1.0.0
Package: interactions
Type: Package
Title: Comprehensive, User-Friendly Toolkit for Probing Interactions
Version: 1.0.0
Authors@R: person(c("Jacob","A."), "Long", email = "long.1377@osu.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-1582-6214"))
Description: A suite of functions for conducting and interpreting analysis of statistical interaction in regression models that was formerly part of the 'jtools' package. Functionality includes visualization of two- and three-way interactions among continuous and/or categorical variables as well as calculation of "simple slopes" and Johnson-Neyman intervals. These capabilities are implemented for generalized linear models in addition to the standard linear regression context.
URL: https://interactions.jacob-long.com
BugReports: https://github.com/jacob-long/interactions/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: ggplot2, crayon, cli, jtools (>= 2.0.0), rlang
Suggests: brms, broom, cowplot, ggstance, glue, huxtable (>= 3.0.0), lme4, rstanarm, sandwich, survey, knitr, rmarkdown, rmdformats, testthat
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-02-09 14:06:52 UTC; jlong
Author: Jacob A. Long [aut, cre] (<https://orcid.org/0000-0002-1582-6214>)
Maintainer: Jacob A. Long <long.1377@osu.edu>
Repository: CRAN
Date/Publication: 2019-02-18 23:20:03 UTC

More information about interactions at CRAN
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Package tidygraph updated to version 1.1.2 with previous version 1.1.1 dated 2018-11-20

Title: A Tidy API for Graph Manipulation
Description: A graph, while not "tidy" in itself, can be thought of as two tidy data frames describing node and edge data respectively. 'tidygraph' provides an approach to manipulate these two virtual data frames using the API defined in the 'dplyr' package, as well as provides tidy interfaces to a lot of common graph algorithms.
Author: Thomas Lin Pedersen [cre, aut]
Maintainer: Thomas Lin Pedersen <thomasp85@gmail.com>

Diff between tidygraph versions 1.1.1 dated 2018-11-20 and 1.1.2 dated 2019-02-18

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More information about tidygraph at CRAN
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Package shinyWidgets updated to version 0.4.5 with previous version 0.4.4 dated 2018-11-05

Title: Custom Inputs Widgets for Shiny
Description: Some custom inputs widgets to use in Shiny applications, like a toggle switch to replace checkboxes. And other components to pimp your apps.
Author: Victor Perrier [aut, cre], Fanny Meyer [aut], David Granjon [aut] (jQuery Knob shiny interface & sliders appearance), Ian Fellows [ctb] (Methods for mutating vertical tabs & updateMultiInput), Wil Davis [ctb] (numericRangeInput function), SnapAppointments [cph] (bootstrap-select), Mattia Larentis [ctb, cph] (Bootstrap Switch), Emanuele Marchi [ctb, cph] (Bootstrap Switch), Mark Otto [ctb] (Bootstrap library), Jacob Thornton [ctb] (Bootstrap library), Bootstrap contributors [ctb] (Bootstrap library), Twitter, Inc [cph] (Bootstrap library), Flatlogic [cph] (Awesome Bootstrap Checkbox), mouse0270 [ctb, cph] (Material Design Switch), Tristan Edwards [ctb, cph] (SweetAlert), Fabian Lindfors [ctb, cph] (multi.js), Anthony Terrien [ctb, cph] (jQuery Knob), Daniel Eden [ctb, cph] (animate.css), Ganapati V S [ctb, cph] (bttn.css), Brian Grinstead [ctb, cph] (Spectrum), Lokesh Rajendran [ctb, cph] (pretty-checkbox), Leon Gersen [ctb, cph] (wnumb & noUiSlider), Timofey Marochkin [ctb, cph] (air-datepicker), Tobias Ahlin [ctb, cph] (CSS spin)
Maintainer: Victor Perrier <victor.perrier@dreamrs.fr>

Diff between shinyWidgets versions 0.4.4 dated 2018-11-05 and 0.4.5 dated 2019-02-18

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More information about shinyWidgets at CRAN
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New package segmenTier with initial version 0.1.2
Package: segmenTier
Type: Package
Title: Similarity-Based Segmentation of Multidimensional Signals
Version: 0.1.2
Author: Rainer Machne, Douglas B. Murray, Peter F. Stadler
URL: https://github.com/raim/segmenTier
BugReports: https://github.com/raim/segmenTier/issues
Maintainer: Rainer Machne <raim@tbi.univie.ac.at>
Description: A dynamic programming solution to segmentation based on maximization of arbitrary similarity measures within segments. The general idea, theory and this implementation are described in Machne, Murray & Stadler (2017) <doi:10.1038/s41598-017-12401-8>. In addition to the core algorithm, the package provides time-series processing and clustering functions as described in the publication. These are generally applicable where a `k-means` clustering yields meaningful results, and have been specifically developed for clustering of the Discrete Fourier Transform of periodic gene expression data (`circadian' or `yeast metabolic oscillations'). This clustering approach is outlined in the supplemental material of Machne & Murray (2012) <doi:10.1371/journal.pone.0037906>), and here is used as a basis of segment similarity measures. Notably, the time-series processing and clustering functions can also be used as stand-alone tools, independent of segmentation, e.g., for transcriptome data already mapped to genes.
License: GPL (>= 2)
Imports: Rcpp (>= 0.12.7)
Suggests: flowMerge, flowClust, flowCore, knitr, rmarkdown
LinkingTo: Rcpp
Encoding: UTF-8
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-02-09 13:04:24 UTC; raim
Repository: CRAN
Date/Publication: 2019-02-18 23:00:03 UTC

More information about segmenTier at CRAN
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Package nonmem2R updated to version 0.2.1 with previous version 0.1.10 dated 2018-09-26

Title: Loading NONMEM Output Files with Functions for Visual Predictive Checks (VPC) and Goodness of Fit (GOF) Plots
Description: Loading NONMEM (NONlinear Mixed-Effect Modeling, <http://www.iconplc.com/innovation/solutions/nonmem/>) and PSN (Perl-speaks-NONMEM, <https://uupharmacometrics.github.io/PsN/>) output files to extract parameter estimates, provide visual predictive check (VPC) and goodness of fit (GOF) plots, and simulate with parameter uncertainty.
Author: Magnus Astrand
Maintainer: Magnus Astrand <magnus.astrand@astrazeneca.com>

Diff between nonmem2R versions 0.1.10 dated 2018-09-26 and 0.2.1 dated 2019-02-18

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Package ggsn updated to version 0.5.0 with previous version 0.4.0 dated 2017-03-20

Title: North Symbols and Scale Bars for Maps Created with 'ggplot2' or 'ggmap'
Description: Adds north symbols (18 options) and scale bars in kilometers, meters, nautical miles, or statue miles, to maps in geographic or metric coordinates created with 'ggplot2' or 'ggmap'.
Author: Oswaldo Santos Baquero [aut, cre]
Maintainer: Oswaldo Santos Baquero <baquero@usp.br>

Diff between ggsn versions 0.4.0 dated 2017-03-20 and 0.5.0 dated 2019-02-18

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Package modelr updated to version 0.1.4 with previous version 0.1.3 dated 2019-02-05

Title: Modelling Functions that Work with the Pipe
Description: Functions for modelling that help you seamlessly integrate modelling into a pipeline of data manipulation and visualisation.
Author: Hadley Wickham [aut, cre], RStudio [cph]
Maintainer: Hadley Wickham <hadley@rstudio.com>

Diff between modelr versions 0.1.3 dated 2019-02-05 and 0.1.4 dated 2019-02-18

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Package flexmix updated to version 2.3-15 with previous version 2.3-14 dated 2017-04-28

Title: Flexible Mixture Modeling
Description: A general framework for finite mixtures of regression models using the EM algorithm is implemented. The E-step and all data handling are provided, while the M-step can be supplied by the user to easily define new models. Existing drivers implement mixtures of standard linear models, generalized linear models and model-based clustering.
Author: Bettina Gruen [aut, cre] (<https://orcid.org/0000-0001-7265-4773>), Friedrich Leisch [aut] (<https://orcid.org/0000-0001-7278-1983>), Deepayan Sarkar [ctb] (<https://orcid.org/0000-0003-4107-1553>), Frederic Mortier [ctb], Nicolas Picard [ctb] (<https://orcid.org/0000-0001-5548-9171>)
Maintainer: Bettina Gruen <Bettina.Gruen@jku.at>

Diff between flexmix versions 2.3-14 dated 2017-04-28 and 2.3-15 dated 2019-02-18

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More information about flexmix at CRAN
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Package nonneg.cg updated to version 0.1.1 with previous version 0.1 dated 2019-01-27

Title: Non-Negative Conjugate-Gradient Minimizer
Description: Minimize a differentiable function subject to all the variables being non-negative (i.e. >= 0), using a Conjugate-Gradient algorithm based on a modified Polak-Ribiere-Polyak formula as described in (Li, Can, 2013, <https://www.hindawi.com/journals/jam/2013/986317/abs/>).
Author: David Cortes
Maintainer: David Cortes <david.cortes.rivera@gmail.com>

Diff between nonneg.cg versions 0.1 dated 2019-01-27 and 0.1.1 dated 2019-02-18

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Package libcoin updated to version 1.0-3 with previous version 1.0-2 dated 2018-12-13

Title: Linear Test Statistics for Permutation Inference
Description: Basic infrastructure for linear test statistics and permutation inference in the framework of Strasser and Weber (1999) <http://epub.wu.ac.at/102/>. This package must not be used by end-users. CRAN package 'coin' implements all user interfaces and is ready to be used by anyone.
Author: Torsten Hothorn [aut, cre]
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

Diff between libcoin versions 1.0-2 dated 2018-12-13 and 1.0-3 dated 2019-02-18

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Package poplite updated to version 0.99.21 with previous version 0.99.19 dated 2017-10-12

Title: Tools for Simplifying the Population and Querying of SQLite Databases
Description: Provides objects and accompanying methods which facilitates populating and querying SQLite databases.
Author: Daniel Bottomly [cre, aut], Shannon McWeeney [aut], Beth Wilmot [aut]
Maintainer: Daniel Bottomly <bottomly@ohsu.edu>

Diff between poplite versions 0.99.19 dated 2017-10-12 and 0.99.21 dated 2019-02-18

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Package rayshader updated to version 0.10.0 with previous version 0.5.1 dated 2018-09-11

Title: Create and Visualize Hillshaded Maps from Elevation Matrices
Description: Uses a combination of raytracing, spherical texture mapping, lambertian reflectance, and ambient occlusion to produce hillshades of elevation matrices. Includes water detection and layering functions, programmable color palette generation, several built-in textures, 2D and 3D plotting options, and the ability to export 3D maps to a 3D printable format.
Author: Tyler Morgan-Wall
Maintainer: Tyler Morgan-Wall <tylermw@gmail.com>

Diff between rayshader versions 0.5.1 dated 2018-09-11 and 0.10.0 dated 2019-02-18

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More information about rayshader at CRAN
Permanent link

Package lwgeom updated to version 0.1-6 with previous version 0.1-5 dated 2018-12-07

Title: Bindings to Selected 'liblwgeom' Functions for Simple Features
Description: Access to selected functions found in 'liblwgeom' <https://github.com/postgis/postgis/tree/svn-trunk/liblwgeom>, the light-weight geometry library used by 'PostGIS' <http://postgis.net/>.
Author: Edzer Pebesma [aut, cre] (<https://orcid.org/0000-0001-8049-7069>), Colin Rundel [ctb], Andy Teucher [ctb], liblwgeom developers [cph]
Maintainer: Edzer Pebesma <edzer.pebesma@uni-muenster.de>

Diff between lwgeom versions 0.1-5 dated 2018-12-07 and 0.1-6 dated 2019-02-18

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Package SAM updated to version 1.1.0 with previous version 1.0.5 dated 2014-02-12

Title: Sparse Additive Modelling
Description: Computationally efficient tools for high dimensional predictive modeling (regression and classification). SAM is short for sparse additive modeling, and adopts the computationally efficient basis spline technique. We solve the optimization problems by various computational algorithms including the block coordinate descent algorithm, fast iterative soft-thresholding algorithm, and newton method. The computation is further accelerated by warm-start and active-set tricks.
Author: Haoming Jiang, Yukun Ma, Xinyu Fei, Tuo Zhao, Xingguo Li, Han Liu, and Kathryn Roeder
Maintainer: Haoming Jiang <jianghm.ustc@gmail.com>

Diff between SAM versions 1.0.5 dated 2014-02-12 and 1.1.0 dated 2019-02-18

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More information about SAM at CRAN
Permanent link

Package dkanr updated to version 0.1.3 with previous version 0.1.2 dated 2018-07-12

Title: Client for the 'DKAN' API
Description: Provides functions to facilitate access to the 'DKAN' API (<https://dkan.readthedocs.io/en/latest/apis/index.html>), including the 'DKAN' REST API (metadata), and the 'DKAN' datastore API (data). Includes functions to list, create, retrieve, update, and delete datasets and resources nodes. It also includes functions to search and retrieve data from the 'DKAN' datastore.
Author: Tony Fujs [aut, cre], Meera Desai [aut], Karthik Ramanathan [aut]
Maintainer: Tony Fujs <tonyfujs@gmail.com>

Diff between dkanr versions 0.1.2 dated 2018-07-12 and 0.1.3 dated 2019-02-18

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Permanent link

New package swephR with initial version 0.1.5
Package: swephR
Type: Package
Title: High Precision Swiss Ephemeris
Version: 0.1.5
Authors@R: c( person("Ralf", "Stubner", email = "ralf.stubner@gmail.com", role = c("aut", "cre")), person("Victor", "Reijs", role = "aut"), person("Authors and copyright holder of the Swiss Ephemeris", role = c("aut", "cph"), comment = "see LICENSE for details"))
Description: The Swiss Ephemeris is a high precision ephemeris based upon the DE431 ephemerides from NASA's JPL. It covers the time range 13201 BC to AD 17191. This package uses the semi-analytic theory by Steve Moshier. For faster and more accurate calculations, the compressed Swiss Ephemeris data is available in the 'swephRdata' package. To access this data package, run 'install.packages("swephRdata", repos = "https://rstub.github.io/drat/", type = "source")'. The size of the 'swephRdata' package is approximately 115 MB. The user can also use the original JPL DE431 data.
License: AGPL | file LICENSE
Imports: Rcpp (>= 0.12.18)
LinkingTo: Rcpp
RoxygenNote: 6.1.1
Suggests: testthat, swephRdata, knitr, rmarkdown
Encoding: UTF-8
URL: https://github.com/rstub/swephR/, http://www.astro.com/swisseph/
BugReports: https://github.com/rstub/swephR/issues/
Additional_repositories: https://rstub.github.io/drat
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-02-09 11:50:37 UTC; ralf
Author: Ralf Stubner [aut, cre], Victor Reijs [aut], Authors and copyright holder of the Swiss Ephemeris [aut, cph] (see LICENSE for details)
Maintainer: Ralf Stubner <ralf.stubner@gmail.com>
Repository: CRAN
Date/Publication: 2019-02-18 15:00:03 UTC

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New package pcgen with initial version 0.2.0
Package: pcgen
Type: Package
Title: Reconstruction of Causal Networks for Data with Random Genetic Effects
Version: 0.2.0
Author: Willem Kruijer, Pariya Behrouzi, Maria Xose Rodriguez-Alvarez
Maintainer: Pariya Behrouzi <pariya.behrouzi@gmail.com>
Depends: R (>= 3.1.0)
Imports: pcalg, graph, Matrix, stats, MASS, utils, Hmisc, methods, lme4, sommer, ggm
Description: Implements the pcgen algorithm, which is a modified version of the standard pc-algorithm, with specific conditional independence tests and modified orientation rules. pcgen extends the approach of Valente et al. (2010) <doi:10.1534/genetics.109.112979> with reconstruction of direct genetic effects.
License: GPL-3
Date: 2019-02-18
NeedsCompilation: no
Packaged: 2019-02-18 13:27:37 UTC; behro001
Repository: CRAN
Date/Publication: 2019-02-18 14:50:03 UTC

More information about pcgen at CRAN
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New package LongMemoryTS with initial version 0.1.0
Package: LongMemoryTS
Type: Package
Title: Long Memory Time Series
Version: 0.1.0
Date: 2019-01-18
Authors@R: c(person("Christian", "Leschinski", email="christian_leschinski@gmx.de", role=c("aut", "cre")), person("Michelle", "Voges", email="voges@statistik.uni-hannover.de", role="ctb"), person("Kai", "Wenger", email="wenger@statistik.uni-hannover.de", role="ctb"))
Description: Long Memory Time Series is a collection of functions for estimation, simulation and testing of long memory processes, spurious long memory processes and fractionally cointegrated systems.
License: GPL-2
LinkingTo: Rcpp, RcppArmadillo
Imports: Rcpp, stats, longmemo, partitions, fracdiff, mvtnorm
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-02-09 13:31:27 UTC; Christian
Author: Christian Leschinski [aut, cre], Michelle Voges [ctb], Kai Wenger [ctb]
Maintainer: Christian Leschinski <christian_leschinski@gmx.de>
Repository: CRAN
Date/Publication: 2019-02-18 14:40:03 UTC

More information about LongMemoryTS at CRAN
Permanent link

New package imageviewer with initial version 0.1.0
Package: imageviewer
Title: Simple 'htmlwidgets' Image Viewer with WebGL Brightness/Contrast
Version: 0.1.0
Author: Iakov Pustilnik [aut, cre], Denis Rastegaev [aut]
Maintainer: Iakov Pustilnik <xyapus@gmail.com>
URL: https://github.com/yapus/imageviewer
BugReports: https://github.com/yapus/imageviewer/issues
Authors@R: c( person("Iakov", "Pustilnik", email = "xyapus@gmail.com", role = c("aut", "cre")), person("Denis", "Rastegaev", email = "leda82@gmail.com", role = "aut") )
Description: Display a 2D-matrix data as a interactive zoomable gray-scale image viewer, providing tools for manual data inspection. The viewer window shows cursor guiding lines and a corresponding data slices for both axes at the current cursor position. A tool-bar allows adjusting image display brightness/contrast through WebGL filters and performing basic high-pass/low-pass filtering.
Depends: R (>= 3.4), htmlwidgets
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-02-09 07:19:14 UTC; 2can
Repository: CRAN
Date/Publication: 2019-02-18 14:50:40 UTC

More information about imageviewer at CRAN
Permanent link

New package DTAT with initial version 0.3-0
Package: DTAT
Type: Package
Title: Dose Titration Algorithm Tuning
Version: 0.3-0
Date: 2019-02-08
Authors@R: person("David C.", "Norris" , role = c("aut", "cre") , email = "david@precisionmethods.guru" )
Maintainer: David C. Norris <david@precisionmethods.guru>
Depends: R (>= 3.4.0), survival
Imports: km.ci, pomp, Hmisc, data.table, dplyr, r2d3, shiny, jsonlite, methods
Suggests: knitr, rmarkdown, lattice, latticeExtra, widgetframe, tidyr, RColorBrewer
Description: DTAT is a methodologic framework allowing dose individualization to be conceived as a continuous learning process that begins in early-phase clinical trials and continues throughout drug development, on into clinical practice. This package includes code that researchers may use to reproduce or extend key results of the DTAT research programme, plus tools for trialists to design and simulate a '3+3/PC' dose-finding study. Please see Norris (2017) <doi:10.12688/f1000research.10624.3> and Norris (2017) <doi:10.1101/240846>.
URL: https://osf.io/5479p/
License: MIT + file LICENSE
RoxygenNote: 6.1.1
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-02-08 12:05:34 UTC; david
Author: David C. Norris [aut, cre]
Repository: CRAN
Date/Publication: 2019-02-18 14:40:10 UTC

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New package Cascade with initial version 1.7
Package: Cascade
Type: Package
Title: Selection, Reverse-Engineering and Prediction in Cascade Networks
Version: 1.7
Date: 2019-02-09
Depends: R (>= 2.10)
Imports: abind, animation, cluster, grid, igraph, lars, lattice, limma, magic, methods, nnls, splines, stats4, survival, tnet, VGAM
Suggests: R.rsp, CascadeData, knitr
Authors@R: c( person(given = "Frederic", family= "Bertrand", role = c("cre", "aut"), email = "frederic.bertrand@math.unistra.fr", comment = c(ORCID = "0000-0002-0837-8281")), person(given = "Myriam", family= "Maumy-Bertrand", role = c("aut"), email = "myriam.maumy-bertrand@math.unistra.fr", comment = c(ORCID = "0000-0002-4615-1512")), person(given = "Laurent", family= "Vallat", role = c("ctb"), email = "vallat@unistra.fr"), person(given = "Nicolas", family= "Jung", role = c("ctb"), email = "nicolas.jung@unistra.fr"))
Author: Frederic Bertrand [cre, aut] (<https://orcid.org/0000-0002-0837-8281>), Myriam Maumy-Bertrand [aut] (<https://orcid.org/0000-0002-4615-1512>), Laurent Vallat [ctb], Nicolas Jung [ctb]
Maintainer: Frederic Bertrand <frederic.bertrand@math.unistra.fr>
Description: A modeling tool allowing gene selection, reverse engineering, and prediction in cascade networks. Jung, N., Bertrand, F., Bahram, S., Vallat, L., and Maumy-Bertrand, M. (2014) <doi:10.1093/bioinformatics/btt705>.
License: GPL (>= 2)
Encoding: UTF-8
Collate: global.R micro_array.R network.R micro_array-network.R micropredict.R
Classification/MSC: 62J05, 62J07, 62J99, 92C42
VignetteBuilder: R.rsp
RoxygenNote: 6.1.1
URL: http://www-irma.u-strasbg.fr/~fbertran/, https://github.com/fbertran/Cascade
BugReports: https://github.com/fbertran/Cascade/issues
NeedsCompilation: no
Packaged: 2019-02-09 02:24:24 UTC; fbertran
Repository: CRAN
Date/Publication: 2019-02-18 14:50:52 UTC

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New package bdchecks with initial version 0.1.7
Package: bdchecks
Title: Biodiversity Data Checks
Description: Supplies a Shiny app and a set of functions to perform and managing data checks for biodiversity data.
Version: 0.1.7
Date: 2019-02-07
License: GPL-3 | file LICENSE
URL: https://github.com/bd-R/bdchecks
BugReports: https://github.com/bd-R/bdchecks/issues
Authors@R: c( person( "Povilas", "Gibas", email = "povilasgibas@gmail.com", role = c("aut", "cre"), comment = c(ORCID = '0000-0001-5311-6021')), person( "Tomer", "Gueta", email = "tomer.gu@gmail.com", role = c("aut"), comment = c(ORCID = '0000-0003-1557-8596')), person( "Vijay", "Barve", , email = "vijay.barve@gmail.com", role = c("aut"), comment = c(ORCID = '0000-0002-4852-2567')), person( "Thiloshon", "Nagarajah", email = "thiloshon@gmail.com", role = c("aut")), person( "Yohay", "Carmel", email = "yohay@cv.technion.ac.il", role = c("aut"), comment = c(ORCID = '0000-0002-5883-0184')) )
Depends: R (>= 2.10)
Imports: bdDwC, DT, data.table, finch, methods, knitr, rgbif, shiny, shinyBS, shinydashboard, shinyjs, spocc, yaml
LazyData: true
RoxygenNote: 6.1.1
Encoding: UTF-8
Suggests: testthat, covr
NeedsCompilation: no
Packaged: 2019-02-09 09:38:55 UTC; pogibas
Author: Povilas Gibas [aut, cre] (<https://orcid.org/0000-0001-5311-6021>), Tomer Gueta [aut] (<https://orcid.org/0000-0003-1557-8596>), Vijay Barve [aut] (<https://orcid.org/0000-0002-4852-2567>), Thiloshon Nagarajah [aut], Yohay Carmel [aut] (<https://orcid.org/0000-0002-5883-0184>)
Maintainer: Povilas Gibas <povilasgibas@gmail.com>
Repository: CRAN
Date/Publication: 2019-02-18 15:00:07 UTC

More information about bdchecks at CRAN
Permanent link

Package RandomFields updated to version 3.3.1 with previous version 3.3 dated 2019-02-14

Title: Simulation and Analysis of Random Fields
Description: Methods for the inference on and the simulation of Gaussian fields are provided, as well as methods for the simulation of extreme value random fields.
Author: Martin Schlather [aut, cre], Alexander Malinowski [aut], Marco Oesting [aut], Daphne Boecker [aut], Kirstin Strokorb [aut], Sebastian Engelke [aut], Johannes Martini [aut], Felix Ballani [aut], Olga Moreva [aut], Jonas Auel[ctr], Peter Menck [ctr], Sebastian Gross [ctr], Ulrike Ober [ctb], Paulo Ribeiro [ctb], Richard Singleton [ctb], Ben Pfaff [ctb], R Core Team [ctb]
Maintainer: Martin Schlather <schlather@math.uni-mannheim.de>

Diff between RandomFields versions 3.3 dated 2019-02-14 and 3.3.1 dated 2019-02-18

 DESCRIPTION |    8 +++++---
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Permanent link

Package geometry updated to version 0.4.0 with previous version 0.3-6 dated 2015-09-09

Title: Mesh Generation and Surface Tessellation
Description: Makes the 'Qhull' library <http://www.qhull.org> available in R, in a similar manner as in Octave and MATLAB. Qhull computes convex hulls, Delaunay triangulations, halfspace intersections about a point, Voronoi diagrams, furthest-site Delaunay triangulations, and furthest-site Voronoi diagrams. It runs in 2D, 3D, 4D, and higher dimensions. It implements the Quickhull algorithm for computing the convex hull. Qhull does not support constrained Delaunay triangulations, or mesh generation of non-convex objects, but the package does include some R functions that allow for this.
Author: Jean-Romain Roussel [cph, ctb] (wrote tsearch function with QuadTrees), C. B. Barber [cph], Kai Habel [cph, aut], Raoul Grasman [cph, aut], Robert B. Gramacy [cph, aut], Pavlo Mozharovskyi [cph, aut], David C. Sterratt [cph, aut, cre]
Maintainer: David C. Sterratt <david.c.sterratt@ed.ac.uk>

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Package zCompositions updated to version 1.2.0 with previous version 1.1.2 dated 2018-11-06

Title: Treatment of Zeros, Left-Censored and Missing Values in Compositional Data Sets
Description: Principled methods for the imputation of zeros, left-censored and missing data in compositional data sets.
Author: Javier Palarea-Albaladejo and Josep Antoni Martin-Fernandez
Maintainer: Javier Palarea-Albaladejo <javier.palarea@bioss.ac.uk>

Diff between zCompositions versions 1.1.2 dated 2018-11-06 and 1.2.0 dated 2019-02-18

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New package phenofit with initial version 0.2.0
Package: phenofit
Type: Package
Title: Extract Remote Sensing Vegetation Phenology
Version: 0.2.0
Authors@R: c( person("Dongdong", "Kong", role = c("aut", "cre"), email = "kongdd.sysu@gmail.com"), person("Mingzhong", "Xiao", role = c("aut"), email = "xmingzh@mail2.sysu.edu.cn"), person("Yongqiang", "Zhang", role = c("aut"), email = "yongqiang.zhang2014@gmail.com"), person("Xihui", "Gu", role = c("aut"), email = "guxh@cug.edu.cn"), person("Jianjian", "Cui", role = c("aut"), email = "cuijj6@mail2.sysu.edu.cn"))
Description: The merits of 'TIMESAT' and 'phenopix' are adopted. Besides, a simple and growing season dividing method and a practical snow elimination method based on Whittaker were proposed. 7 curve fitting methods and 4 phenology extraction methods were provided. Parameters boundary are considered for every curve fitting methods according to their ecological meaning. And 'optimx' is used to select best optimization method for different curve fitting methods.
License: GPL-2 | file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
LinkingTo: Rcpp, RcppArmadillo
Depends: R (>= 3.1)
Imports: Rcpp, tibble, dplyr, purrr, stringr, tidyr, ggplot2, lubridate, data.table, spam, grid, gridExtra, magrittr, plyr, reshape2, zoo, optimx, ucminf, numDeriv, grDevices, utils, stats, DT
Suggests: knitr, rmarkdown, testthat
URL: https://github.com/kongdd/phenofit
BugReports: https://github.com/kongdd/phenofit/issues
NeedsCompilation: yes
Packaged: 2019-02-08 23:37:39 UTC; kongdd
Author: Dongdong Kong [aut, cre], Mingzhong Xiao [aut], Yongqiang Zhang [aut], Xihui Gu [aut], Jianjian Cui [aut]
Maintainer: Dongdong Kong <kongdd.sysu@gmail.com>
Repository: CRAN
Date/Publication: 2019-02-18 11:50:04 UTC

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Package catlearn updated to version 0.6.1 with previous version 0.6 dated 2018-07-17

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

Diff between catlearn versions 0.6 dated 2018-07-17 and 0.6.1 dated 2019-02-18

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Package VGAM updated to version 1.1-1 with previous version 1.0-6 dated 2018-08-18

Title: Vector Generalized Linear and Additive Models
Description: An implementation of about 6 major classes of statistical regression models. The central algorithm is Fisher scoring and iterative reweighted least squares. At the heart of this package are the vector generalized linear and additive model (VGLM/VGAM) classes. VGLMs can be loosely thought of as multivariate GLMs. VGAMs are data-driven VGLMs that use smoothing. The book "Vector Generalized Linear and Additive Models: With an Implementation in R" (Yee, 2015) <DOI:10.1007/978-1-4939-2818-7> gives details of the statistical framework and the package. Currently only fixed-effects models are implemented. Many (150+) models and distributions are estimated by maximum likelihood estimation (MLE) or penalized MLE. The other classes are RR-VGLMs (reduced-rank VGLMs), quadratic RR-VGLMs, reduced-rank VGAMs, RCIMs (row-column interaction models)---these classes perform constrained and unconstrained quadratic ordination (CQO/UQO) models in ecology, as well as constrained additive ordination (CAO). Note that these functions are subject to change; see the NEWS and ChangeLog files for latest changes.
Author: Thomas W. Yee <t.yee@auckland.ac.nz>
Maintainer: Thomas Yee <t.yee@auckland.ac.nz>

Diff between VGAM versions 1.0-6 dated 2018-08-18 and 1.1-1 dated 2019-02-18

 VGAM-1.0-6/VGAM/R/family.math.R              |only
 VGAM-1.0-6/VGAM/man/cauchit.Rd               |only
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 VGAM-1.1-1/VGAM/MD5                          |  771 +++++++++++++--------------
 VGAM-1.1-1/VGAM/NAMESPACE                    |   28 
 VGAM-1.1-1/VGAM/NEWS                         |   84 +-
 VGAM-1.1-1/VGAM/R/Links.R                    |    2 
 VGAM-1.1-1/VGAM/R/aamethods.q                |    2 
 VGAM-1.1-1/VGAM/R/anova.vglm.q               |    4 
 VGAM-1.1-1/VGAM/R/attrassign.R               |    2 
 VGAM-1.1-1/VGAM/R/bAIC.q                     |    2 
 VGAM-1.1-1/VGAM/R/build.terms.vlm.q          |    2 
 VGAM-1.1-1/VGAM/R/calibrate.R                |   32 -
 VGAM-1.1-1/VGAM/R/cao.R                      |    2 
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 VGAM-1.1-1/VGAM/R/cqo.R                      |    2 
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 VGAM-1.1-1/VGAM/R/deviance.vlm.q             |    6 
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 VGAM-1.1-1/VGAM/R/family.actuary.R           |  137 ++--
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 VGAM-1.1-1/VGAM/R/family.aunivariate.R       |  157 +++--
 VGAM-1.1-1/VGAM/R/family.basics.R            |   43 +
 VGAM-1.1-1/VGAM/R/family.binomial.R          |   54 -
 VGAM-1.1-1/VGAM/R/family.bivariate.R         |   70 +-
 VGAM-1.1-1/VGAM/R/family.categorical.R       |  105 +--
 VGAM-1.1-1/VGAM/R/family.censored.R          |   16 
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 VGAM-1.1-1/VGAM/R/family.extremes.R          |   54 -
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 VGAM-1.1-1/VGAM/R/family.mixture.R           |   10 
 VGAM-1.1-1/VGAM/R/family.nbd.R               |   84 +-
 VGAM-1.1-1/VGAM/R/family.nonlinear.R         |    2 
 VGAM-1.1-1/VGAM/R/family.normal.R            |  205 ++++---
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 VGAM-1.1-1/VGAM/R/family.rcim.R              |   18 
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 VGAM-1.1-1/VGAM/R/family.robust.R            |   12 
 VGAM-1.1-1/VGAM/R/family.rrr.R               |   40 -
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 VGAM-1.1-1/VGAM/R/family.ts.R                |   42 -
 VGAM-1.1-1/VGAM/R/family.univariate.R        |  566 +++++++++++++++----
 VGAM-1.1-1/VGAM/R/family.vglm.R              |    2 
 VGAM-1.1-1/VGAM/R/family.zeroinf.R           |  103 +--
 VGAM-1.1-1/VGAM/R/fittedvlm.R                |    2 
 VGAM-1.1-1/VGAM/R/formula.vlm.q              |    2 
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 VGAM-1.1-1/VGAM/R/getxvlmaug.R               |    2 
 VGAM-1.1-1/VGAM/R/hdeff.R                    |  166 +++++
 VGAM-1.1-1/VGAM/R/links.q                    |  283 +++++++--
 VGAM-1.1-1/VGAM/R/logLik.vlm.q               |    2 
 VGAM-1.1-1/VGAM/R/lrp.R                      |    2 
 VGAM-1.1-1/VGAM/R/lrwaldtest.R               |    2 
 VGAM-1.1-1/VGAM/R/model.matrix.vglm.q        |    2 
 VGAM-1.1-1/VGAM/R/mux.q                      |    2 
 VGAM-1.1-1/VGAM/R/nobs.R                     |    2 
 VGAM-1.1-1/VGAM/R/plot.vgam.R                |    2 
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 VGAM-1.1-1/VGAM/R/psv2magic.R                |    2 
 VGAM-1.1-1/VGAM/R/qrrvglm.control.q          |    6 
 VGAM-1.1-1/VGAM/R/qtplot.q                   |    2 
 VGAM-1.1-1/VGAM/R/residuals.vlm.q            |    2 
 VGAM-1.1-1/VGAM/R/rrvglm.R                   |    2 
 VGAM-1.1-1/VGAM/R/rrvglm.control.q           |    2 
 VGAM-1.1-1/VGAM/R/rrvglm.fit.q               |   12 
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 VGAM-1.1-1/VGAM/R/simulate.vglm.R            |    2 
 VGAM-1.1-1/VGAM/R/sm.os.R                    |    2 
 VGAM-1.1-1/VGAM/R/sm.ps.R                    |    2 
 VGAM-1.1-1/VGAM/R/smart.R                    |    2 
 VGAM-1.1-1/VGAM/R/summary.vgam.q             |   21 
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 VGAM-1.1-1/VGAM/man/A1A2A3.Rd                |    9 
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New package telefit with initial version 1.0.1
Package: telefit
Type: Package
Title: Estimation and Prediction for Remote Effects Spatial Process Models
Version: 1.0.1
Date: 2019-02-15
Author: Joshua Hewitt
Maintainer: Joshua Hewitt <joshua.hewitt@colostate.edu>
Description: Implementation of the remote effects spatial process (RESP) model for teleconnection. The RESP model is a geostatistical model that allows a spatially-referenced variable (like average precipitation) to be influenced by covariates defined on a remote domain (like sea surface temperatures). The RESP model is introduced in Hewitt et al. (2018) <doi:10.1002/env.2523>. Sample code for working with the RESP model is available at <https://jmhewitt.github.io/research/resp_example>. This material is based upon work supported by the National Science Foundation under grant number AGS 1419558. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
License: GPL-3
Depends: R (>= 3.0.2)
Imports: abind, coda, cowplot, doRNG, dplyr, fields, itertools, mvtnorm, raster, scoringRules, stringr, foreach, ggplot2, gtable, reshape2, scales, sp, SDMTools
LinkingTo: Rcpp (>= 0.12.4), RcppArmadillo, RcppEigen (>= 0.3.3.3.1)
RoxygenNote: 6.1.1
Suggests: testthat
LazyData: true
SystemRequirements: A system with a recent-enough C++11 compiler (such as g++-4.8 or later).
NeedsCompilation: yes
Encoding: UTF-8
Packaged: 2019-02-15 22:34:18 UTC; pointdex
Repository: CRAN
Date/Publication: 2019-02-18 10:50:03 UTC

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New package orders with initial version 0.1.0
Package: orders
Type: Package
Title: Sampling from Order Statistics of New Families of Distributions
Version: 0.1.0
Author: Carlos Alberto Cardozo Delgado
Maintainer: Carlos Alberto Cardozo Delgado <cardozorpackages@gmail.com>
Description: Set of tools to generate samples of order statistics from new families of distributions. The main references for this package are: Gentle, J. (2009), Computational Statistics, Springer-Verlag and Naradajah, S. and Rocha, R. (2016), Newdistns: An R Package for New Families of Distributions, Journal of Statistical Software. The families of distributions are: Marshall Olkin G distributions, exponentiated G distributions, beta G distributions, gamma G distributions, Kumaraswamy G distributions, generalized beta G distributions, beta extended G distributions, gamma G distributions, gamma uniform G distributions, beta exponential G distributions, Weibull G distributions, log gamma G I distributions, log gamma G II distributions, exponentiated generalized G distributions, exponentiated Kumaraswamy G distributions, geometric exponential Poisson G distributions, truncated-exponential skew-symmetric G distributions, modi???ed beta G distributions, and exponentiated exponential Poisson G distributions.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Imports: Newdistns
NeedsCompilation: no
Packaged: 2019-02-08 23:26:30 UTC; Carlos
Repository: CRAN
Date/Publication: 2019-02-18 10:30:03 UTC

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Package maptools updated to version 0.9-5 with previous version 0.9-4 dated 2018-09-19

Title: Tools for Handling Spatial Objects
Description: Set of tools for manipulating geographic data. It includes binary access to 'GSHHG' shoreline files. The package also provides interface wrappers for exchanging spatial objects with packages such as 'PBSmapping', 'spatstat', 'maps', 'RArcInfo', and others.
Author: Roger Bivand [cre, aut] (<https://orcid.org/0000-0003-2392-6140>), Nicholas Lewin-Koh [aut], Edzer Pebesma [ctb], Eric Archer [ctb], Adrian Baddeley [ctb], Nick Bearman [ctb], Hans-Jörg Bibiko [ctb], Steven Brey [ctb], Jonathan Callahan [ctb], German Carrillo [ctb], Stéphane Dray [ctb], David Forrest [ctb], Michael Friendly [ctb], Patrick Giraudoux [ctb], Duncan Golicher [ctb], Virgilio Gómez Rubio [ctb], Patrick Hausmann [ctb], Karl Ove Hufthammer [ctb], Thomas Jagger [ctb], Kent Johnson [ctb], Sebastian Luque [ctb], Don MacQueen [ctb], Andrew Niccolai [ctb], Edzer Pebesma [ctb], Oscar Perpiñán Lamigueiro [ctb], Ethan Plunkett [ctb], Tom Short [ctb], Greg Snow [ctb], Ben Stabler [ctb], Murray Stokely [ctb], Rolf Turner [ctb]
Maintainer: Roger Bivand <Roger.Bivand@nhh.no>

Diff between maptools versions 0.9-4 dated 2018-09-19 and 0.9-5 dated 2019-02-18

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New package fiberLD with initial version 0.1-6
Encoding: UTF-8
Package: fiberLD
Version: 0.1-6
Author: Natalya Pya Arnqvist[aut, cre], Sara Sjöstedt de Luna [aut] Konrad Abramowicz [aut]
Maintainer: Natalya Pya Arnqvist <nat.pya@gmail.com>
Title: Fiber Length Determination
Date: 2019-02-08
Description: Routines for estimating tree fiber (tracheid) length distributions in the standing tree based on increment core samples. Two types of data can be used with the package, increment core data measured by means of an optical fiber analyzer (OFA), e.g. such as the Kajaani Fiber Lab, or measured by microscopy. Increment core data analyzed by OFAs consist of the cell lengths of both cut and uncut fibres (tracheids) and fines (such as ray parenchyma cells) without being able to identify which cells are cut or if they are fines or fibres. The microscopy measured data consist of the observed lengths of the uncut fibres in the increment core. A censored version of a mixture of the fine and fiber length distributions is proposed to fit the OFA data, under distributional assumptions (Svensson et al., 2006) <doi:10.1111/j.1467-9469.2006.00501.x>. The package offers two choices for the assumptions of the underlying density functions of the true fiber (fine) lenghts of those fibers (fines) that at least partially appear in the increment core, being the generalized gamma and the log normal densities.
Depends: R (>= 2.15.0)
Imports: stats, graphics, Matrix, VGAM, parallel, foreach, doParallel
Suggests: MASS
License: GPL (>= 2)
LazyLoad: yes
NeedsCompilation: no
Packaged: 2019-02-08 21:07:16 UTC; natalya
Repository: CRAN
Date/Publication: 2019-02-18 10:30:10 UTC

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Package tsibble updated to version 0.7.0 with previous version 0.6.2 dated 2018-12-12

Title: Tidy Temporal Data Frames and Tools
Description: Provides a 'tbl_ts' class (the 'tsibble') to store and manage temporal data in a data-centric format, which is built on top of the 'tibble'. The 'tsibble' aims at easily manipulating and analysing temporal data, including counting and filling in time gaps, aggregate over calendar periods, performing rolling window calculations, and etc.
Author: Earo Wang [aut, cre] (<https://orcid.org/0000-0001-6448-5260>), Di Cook [aut, ths] (<https://orcid.org/0000-0002-3813-7155>), Rob Hyndman [aut, ths] (<https://orcid.org/0000-0002-2140-5352>), Mitchell O'Hara-Wild [ctb]
Maintainer: Earo Wang <earo.wang@gmail.com>

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Package Spectrum updated to version 0.3 with previous version 0.2 dated 2019-02-11

Title: Versatile Ultra-Fast Spectral Clustering for Single and Multi-View Data
Description: A versatile ultra-fast spectral clustering method for single or multi-view data. 'Spectrum' uses a new type of adaptive density aware kernel that strengthens local connections in dense regions in the graph. For integrating multi-view data and reducing noise we use a recently developed tensor product graph data integration and diffusion system. 'Spectrum' contains two techniques for finding the number of clusters (K); the classical eigengap method and a novel multimodality gap procedure. The multimodality gap analyses the distribution of the eigenvectors of the graph Laplacian to decide K and tune the kernel. 'Spectrum' is suited for clustering a wide range of complex data.
Author: Christopher R John, David Watson
Maintainer: Christopher R John <chris.r.john86@gmail.com>

Diff between Spectrum versions 0.2 dated 2019-02-11 and 0.3 dated 2019-02-18

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New package SPAS with initial version 2019.2
Package: SPAS
Type: Package
Title: Stratified-Petersen Analysis System
Version: 2019.2
Date: 2019-02-06
Author: Carl James Schwarz
Maintainer: Carl James Schwarz <cschwarz.stat.sfu.ca@gmail.com>
Depends:
Imports: BB, MASS, Matrix, msm, numDeriv, plyr
Description: The Stratified-Petersen Analysis System (SPAS) is designed to estimate abundance in two-sample capture-recapture experiments where the capture and recaptures are stratified. This is a generalization of the simple Lincoln-Petersen estimator. Strata may be defined in time or in space or both, and the s strata in which marking takes place may differ from the t strata in which recoveries take place. When s=t, SPAS reduces to the method described by Darroch (1961) <https://www.jstor.org/stable/2332748>. When s<t, SPAS implements the methods described in Plante, Rivest, and Tremblay (1988) <https://www.jstor.org/stable/2533994>. Schwarz and Taylor (1998) <doi:10.1139/f97-238> describe the use of SPAS in estimating return of salmon stratified by time and geography. A related package, BTSPAS, deals with temporal stratification where a spline is used to model the distribution of the population over time as it passes the second capture location. This is the R-version of the (now obsolete) standalone Windows program available at <http://www.cs.umanitoba.ca/~popan/spas/spas_home.html>.
License: GPL (>= 2)
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-02-07 06:25:06 UTC; carlschwarz
Repository: CRAN
Date/Publication: 2019-02-18 09:30:02 UTC

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New package SMITIDvisu with initial version 0.0.3
Package: SMITIDvisu
Type: Package
Title: Visualize Data for Host and Viral Population from 'SMITIDstruct' using HTMLwidgets
Version: 0.0.3
Authors@R: person("Jean-Francois", "Rey", email = "jean-francois.rey@inra.fr", role = c("aut", "cre"))
Description: Visualisation tools for 'SMITIDstruct' package. Allow to visualize host timeline, transmission tree, index diversities and variant graph using HTMLwidgets. It mainly using D3JS javascript framework.
Date: 2019-02-03
Depends: R (>= 3.4.0), utils
LinkingTo: Rcpp
NeedsCompilation: yes
SystemRequirements: C++11
Biarch: true
License: GPL (>= 3) | file LICENSE
URL: https://informatique-mia.inra.fr/biosp/anr-smitid-project, https://gitlab.paca.inra.fr/SMITID/visu
Encoding: UTF-8
LazyData: true
Imports: Rcpp (>= 0.11.0), htmlwidgets (>= 0.3.2), yaml (>= 2.1.16), jsonlite (>= 1.5.0), magrittr
Suggests: SMITIDstruct, knitr, shiny
RoxygenNote: 6.1.0
Packaged: 2019-02-08 13:24:25 UTC; jfrey
Author: Jean-Francois Rey [aut, cre]
Maintainer: Jean-Francois Rey <jean-francois.rey@inra.fr>
Repository: CRAN
Date/Publication: 2019-02-18 09:40:07 UTC

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New package PUPAIM with initial version 0.1.0
Package: PUPAIM
Type: Package
Title: 'A Collection of Physical and Chemical Adsorption Isotherm Models'
Version: 0.1.0
Author: John Ray V. Saroyda/Ranya Yyan S. Cruz/Roel Joseph C. Antonio/Chester C. Deocaris
Maintainer: Chester Deocaris <ccdeocaris@pup.edu.ph>
Description: Adsorption isotherm equations are linearized plots of different solid-liquid phase equilibria used in calculating different parameters related to the adsorption process. Isotherm equations deals with physical adsorption of gases and vapor and gives the most important characteristics of industrial adsorbents that include pore volume, pore size or energy distribution. PUPAIM has 28 documented adsorption isotherm models listed by Dabrowski (2001) <doi:10.1016/S0001-8686(00)00082-8> and Ayawei et al.(2017) <doi:10.1155/2017/3039817>. These models could be easily fitted in R using adsorption data (Ce and Qe) obtained from experiments.
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R(>= 3.4.0)
Imports: FSA, Metrics, minpack.lm, stats, graphics
NeedsCompilation: no
Packaged: 2019-02-08 12:46:18 UTC; Joseph
Repository: CRAN
Date/Publication: 2019-02-18 09:40:10 UTC

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New package optimos.prime with initial version 0.1.0
Package: optimos.prime
Type: Package
Title: Optimos Prime Helps Calculate Autoecological Data for Biological Species
Version: 0.1.0
Authors@R: c( person("María Belén", "Sathicq", email = "mbelen@ilpla.edu.ar", role = "aut"), person("María Mercedes", "Nicolosi Gelis", email = "mercedesnicolosi@ilpla.edu.ar", role = "aut"), person("Joaquín", "Cochero", email = "jcochero@ilpla.edu.ar", role = "cre"))
Maintainer: Joaquín Cochero <jcochero@ilpla.edu.ar>
Description: Calculates autoecological data (optima and tolerance ranges) of a biological species given an environmental matrix. The package calculates by weighted averaging, using the number of occurrences to adjust the tolerance assigned to each taxon to estimate optima and tolerance range in cases where taxa have unequal occurrences. See the detailed methodology by Birks et al. (1990) <doi:10.1098/rstb.1990.0062>, and a case example by Potapova and Charles (2003) <doi:10.1046/j.1365-2427.2003.01080.x>.
License: GNU General Public License
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1.9000
Depends: ggplot2, tidyverse, plotly
NeedsCompilation: no
Packaged: 2019-02-08 17:18:13 UTC; Juaco
Author: María Belén Sathicq [aut], María Mercedes Nicolosi Gelis [aut], Joaquín Cochero [cre]
Repository: CRAN
Date/Publication: 2019-02-18 09:50:03 UTC

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New package opalr with initial version 1.0.0
Package: opalr
Version: 1.0.0
Title: Opal R and Datashield Utils
Authors@R: c(person(given = "Yannick", family = "Marcon", role = c("aut", "cre"), email = "yannick.marcon@obiba.org", comment = c(ORCID = "0000-0003-0138-2023")), person(given = "Amadou", family = "Gaye", role = "ctb", comment = c(ORCID = "0000-0002-1180-2792")), person("OBiBa group", role="cph", email="info@obiba.org"))
Depends: R (>= 3.1), httr
Imports: xml2, jsonlite, mime
Suggests: e1071, knitr, knitrBootstrap, rmarkdown
Description: Data integration Web application for biobanks by OBiBa. Opal is OBiBa's core database application for biobanks. Participant data, once collected from any data source, must be integrated and stored in a central data repository under a uniform model. Opal is such a central repository. It can import, process, validate, query, analyze, report, and export data. Opal is typically used in a research center to analyze the data acquired at assessment centres. Its ultimate purpose is to achieve seamless data-sharing among biobanks.
License: GPL-3
URL: https://www.obiba.org/ https://www.obiba.org/pages/products/opal/ https://academic.oup.com/ije/article/46/5/1372/4102813
BugReports: https://github.com/obiba/opalr
RoxygenNote: 6.1.1
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-02-08 16:46:59 UTC; yannick
Author: Yannick Marcon [aut, cre] (<https://orcid.org/0000-0003-0138-2023>), Amadou Gaye [ctb] (<https://orcid.org/0000-0002-1180-2792>), OBiBa group [cph]
Maintainer: Yannick Marcon <yannick.marcon@obiba.org>
Repository: CRAN
Date/Publication: 2019-02-18 10:00:08 UTC

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New package nsga3 with initial version 0.0.3
Package: nsga3
Type: Package
Title: An Implementation of Non-Dominated Sorting Genetic Algorithm III for Feature Selection
Version: 0.0.3
Author: Artem Shramko
Maintainer: Artem Shramko <art.shramko@gmail.com>
Description: An adaptation of Non-dominated Sorting Genetic Algorithm III for multi objective feature selection tasks. Non-dominated Sorting Genetic Algorithm III is a genetic algorithm that solves multiple optimization problems simultaneously by applying a non-dominated sorting technique. It uses a reference points based selection operator to explore solution space and preserve diversity. See the original paper by K. Deb and H. Jain (2014) <DOI:10.1109/TEVC.2013.2281534> for a detailed description.
Depends: R (>= 2.10.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: mlr, parallelMap, rPref, xgboost
Suggests: testthat, knitr, rmarkdown
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-02-08 16:47:37 UTC; user
Repository: CRAN
Date/Publication: 2019-02-18 10:00:15 UTC

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New package mixsqp with initial version 0.1-97
Encoding: UTF-8
Type: Package
Package: mixsqp
Version: 0.1-97
Date: 2019-02-08
Title: Sequential Quadratic Programming for Fast Maximum-Likelihood Estimation of Mixture Proportions
Authors@R: c(person("Youngseok","Kim",role="aut", email="youngseok@uchicago.edu"), person("Peter","Carbonetto",role=c("aut","cre"), email="peter.carbonetto@gmail.com"), person("Mihai","Anitescu",role="aut"), person("Matthew","Stephens",role="aut"), person("Jason","Willwerscheid",role="ctb"), person("Jean","Morrison",role="ctb"))
URL: https://github.com/stephenslab/mixsqp
BugReports: https://github.com/stephenslab/mixsqp/issues
SystemRequirements: C++11
Depends: R (>= 3.3.0)
Description: Provides optimization algorithms based on sequential quadratic programming (SQP) for maximum likelihood estimation of the mixture proportions in a finite mixture model where the component densities are known. The algorithms are expected to obtain solutions that are at least as accurate as the state-of-the-art MOSEK interior-point solver (called by function "KWDual" in the 'REBayes' package), and they are expected to arrive at solutions more quickly in large data sets. The algorithms are described in Y. Kim, P. Carbonetto, M. Stephens & M. Anitescu (2012) <arXiv:1806.01412>.
License: MIT + file LICENSE
Imports: stats, Rcpp (>= 0.12.15)
Suggests: REBayes, Rmosek, testthat, knitr, rmarkdown
LinkingTo: Rcpp, RcppArmadillo
LazyData: true
NeedsCompilation: yes
VignetteBuilder: knitr
RoxygenNote: 6.1.1
Packaged: 2019-02-08 13:57:28 UTC; pcarbo
Author: Youngseok Kim [aut], Peter Carbonetto [aut, cre], Mihai Anitescu [aut], Matthew Stephens [aut], Jason Willwerscheid [ctb], Jean Morrison [ctb]
Maintainer: Peter Carbonetto <peter.carbonetto@gmail.com>
Repository: CRAN
Date/Publication: 2019-02-18 09:40:03 UTC

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Package SDLfilter updated to version 1.2.0 with previous version 1.1.1 dated 2018-06-20

Title: Filtering Satellite-Derived Locations
Description: Functions to filter GPS and/or Argos locations. The provided filters remove temporal and spatial duplicates, fixes located at a given height from estimated high tide line, and locations with high error as proposed in Shimada et al. (2012) <doi:10.3354/meps09747> and Shimada et al. (2016) <doi:10.1007/s00227-015-2771-0>.
Author: Takahiro Shimada
Maintainer: Takahiro Shimada <takahiro.shimada@my.jcu.edu.au>

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Package ggstatsplot updated to version 0.0.9 with previous version 0.0.8 dated 2019-01-07

Title: 'ggplot2' Based Plots with Statistical Details
Description: Extension of 'ggplot2', 'ggstatsplot' creates graphics with details from statistical tests included in the plots themselves. It is targeted primarily at behavioral sciences community to provide a one-line code to generate information-rich plots for statistical analysis. of continuous (violin plots, scatterplots, histograms) or categorical (pie and bar charts) data. Currently, it supports only the most common types of statistical tests: parametric, nonparametric, robust, and bayesian versions of t-test/anova, correlation analyses, contingency table analysis, and regression analyses.
Author: Indrajeet Patil [cre, aut, ctb] (<https://orcid.org/0000-0003-1995-6531>), Chuck Powell [aut, ctb] (<https://orcid.org/0000-0002-3606-2188>)
Maintainer: Indrajeet Patil <patilindrajeet.science@gmail.com>

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Package cchs updated to version 0.4.1 with previous version 0.4.0 dated 2017-08-26

Title: Cox Model for Case-Cohort Data with Stratified Subcohort-Selection
Description: Contains a function, also called 'cchs', that calculates Estimator III of Borgan et al (2000), <DOI:10.1023/A:1009661900674>. This estimator is for fitting a Cox proportional hazards model to data from a case-cohort study where the subcohort was selected by stratified simple random sampling.
Author: E. Jones
Maintainer: E. Jones <edmundjones79@gmail.com>

Diff between cchs versions 0.4.0 dated 2017-08-26 and 0.4.1 dated 2019-02-18

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Package openVA updated to version 1.0.8 with previous version 1.0.7 dated 2018-09-13

Title: Automated Method for Verbal Autopsy
Description: Implements multiple existing open-source algorithms for coding cause of death from verbal autopsies. It also provides tools for data manipulation tasks commonly used in Verbal Autopsy analysis and implements easy graphical visualization of individual and population level statistics.
Author: Zehang Li, Tyler McCormick, Sam Clark
Maintainer: Zehang Li <lizehang@gmail.com>

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Package JuliaCall updated to version 0.16.4 with previous version 0.16.2 dated 2019-01-02

Title: Seamless Integration Between R and 'Julia'
Description: Provides an R interface to 'Julia', which is a high-level, high-performance dynamic programming language for numerical computing, see <https://julialang.org/> for more information. It provides a high-level interface as well as a low-level interface. Using the high level interface, you could call any 'Julia' function just like any R function with automatic type conversion. Using the low level interface, you could deal with C-level SEXP directly while enjoying the convenience of using a high-level programming language like 'Julia'.
Author: Changcheng Li [aut, cre], Randy Lai [ctb], Dmitri Grominski [ctb], Nagi Teramo [ctb]
Maintainer: Changcheng Li <cxl508@psu.edu>

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