Wed, 07 Aug 2019

Package webTRISr updated to version 0.2.0 with previous version 0.1.1 dated 2018-10-19

Title: A Wrapper Around 'WebTRIS' Traffic Flow API from Highways England
Description: Provides functions to query data from the 'WebTRIS' Traffic Flow API (from Highways England) into tidy data frames. The API documentation is available here: <http://webtris.highwaysengland.co.uk/api/swagger/ui/index>.
Author: Ivo Wengraf [cre], Will Bowditch [aut]
Maintainer: Ivo Wengraf <Ivo.Wengraf@RACFoundation.org>

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Package SimJoint updated to version 0.2.2 with previous version 0.2.1 dated 2019-06-18

Title: Simulate Joint Distribution
Description: Simulate multivariate correlated data given nonparametric marginals and their covariance structure characterized by a Pearson or Spearman correlation matrix. The simulator engages the problem from a purely computational perspective. It assumes no statistical models such as copulas or parametric distributions, and can approximate the target correlations regardless of theoretical feasibility. The algorithm integrates and advances the Iman-Conover (1982) approach <doi:10.1080/03610918208812265> and the Ruscio-Kaczetow iteration (2008) <doi:10.1080/00273170802285693>. Package functions are carefully implemented in C++ for squeezing computing speed, suitable for large input in a manycore environment. Precision of the approximation and computing speed both outperform various CRAN packages to date by substantial margins. Benchmarks are detailed in function examples. A simple heuristic algorithm is additionally designed to optimize the joint distribution in the post-simulation stage. This heuristic demonstrated not only strong capability of cost reduction, but also good potential of achieving the same level of precision of approximation without the enhanced Iman-Conover-Ruscio-Kaczetow.
Author: Charlie Wusuo Liu
Maintainer: Charlie Wusuo Liu <liuwusuo@gmail.com>

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Package opencpu updated to version 2.1.3 with previous version 2.1.2 dated 2019-05-12

Title: Producing and Reproducing Results
Description: A system for embedded scientific computing and reproducible research with R. The OpenCPU server exposes a simple but powerful HTTP api for RPC and data interchange with R. This provides a reliable and scalable foundation for statistical services or building R web applications. The OpenCPU server runs either as a single-user development server within the interactive R session, or as a multi-user Linux stack based on Apache2. The entire system is fully open source and permissively licensed. The OpenCPU website has detailed documentation and example apps.
Author: Jeroen Ooms [aut, cre] (<https://orcid.org/0000-0002-4035-0289>)
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

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Package MWright updated to version 0.3.2 with previous version 0.3.0 dated 2019-08-05

Title: Mainardi-Wright Family of Distributions
Description: Implements random number generation, plotting, and estimation algorithms for the two-parameter one-sided and two-sided M-Wright (Mainardi-Wright) family. The M-Wright distributions naturally generalize the widely used one-sided (Airy and half-normal or half-Gaussian) and symmetric (Airy and Gaussian or normal) models. These are widely studied in time-fractional differential equations. References: Cahoy and Minkabo (2017) <doi:10.3233/MAS-170388>; Cahoy (2012) <doi:10.1007/s00180-011-0269-x>; Cahoy (2012) <doi:10.1080/03610926.2010.543299>; Cahoy (2011); Mainardi, Mura, and Pagnini (2010) <doi:10.1155/2010/104505>.
Author: Dexter Cahoy
Maintainer: Dexter Cahoy <cahoyd@uhd.edu>

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Package mlrCPO updated to version 0.3.4-4 with previous version 0.3.4-3 dated 2019-05-11

Title: Composable Preprocessing Operators and Pipelines for Machine Learning
Description: Toolset that enriches 'mlr' with a diverse set of preprocessing operators. Composable Preprocessing Operators ("CPO"s) are first-class R objects that can be applied to data.frames and 'mlr' "Task"s to modify data, can be attached to 'mlr' "Learner"s to add preprocessing to machine learning algorithms, and can be composed to form preprocessing pipelines.
Author: Martin Binder [aut, cre], Bernd Bischl [ctb], Michel Lang [ctb], Lars Kotthoff [ctb]
Maintainer: Martin Binder <developer.mb706@doublecaret.com>

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Package cder updated to version 0.2-0 with previous version 0.1-0 dated 2019-08-03

Title: Interface to the California Data Exchange Center
Description: Connect to the California Data Exchange Center (CDEC) Web Service <http://cdec.water.ca.gov/>. 'CDEC' provides a centralized database to store, process, and exchange real-time hydrologic information gathered by various cooperators throughout California. The 'CDEC' Web Service <http://cdec.water.ca.gov/dynamicapp/wsSensorData> provides a data download service for accessing historical records.
Author: Michael Koohafkan [aut, cre]
Maintainer: Michael Koohafkan <michael.koohafkan@gmail.com>

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Package sindyr updated to version 0.2.2 with previous version 0.2.1 dated 2018-09-10

Title: Sparse Identification of Nonlinear Dynamics
Description: This implements the Brunton et al (2016; PNAS <doi:10.1073/pnas.1517384113>) sparse identification algorithm for finding ordinary differential equations for a measured system from raw data (SINDy). The package includes a set of additional tools for working with raw data, with an emphasis on cognitive science applications (Dale and Bhat, in press <doi:10.1016/j.cogsys.2018.06.020>).
Author: Rick Dale and Harish S. Bhat
Maintainer: Rick Dale <racdale@gmail.com>

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Package mlr3misc updated to version 0.1.2 with previous version 0.1.1 dated 2019-07-23

Title: Helper Functions for 'mlr3'
Description: Frequently used helper functions and assertions used in 'mlr3' and its companion packages. Comes with helper functions for functional programming, for printing, to work with 'data.table', as well as some generally useful 'R6' classes. This package also supersedes the package 'BBmisc'.
Author: Michel Lang [cre, aut] (<https://orcid.org/0000-0001-9754-0393>)
Maintainer: Michel Lang <michellang@gmail.com>

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Package compstatr updated to version 0.2.0 with previous version 0.1.1 dated 2019-04-24

Title: Tools for St. Louis Crime Data
Description: Provides a set of tools for creating yearly data sets of St. Louis Metropolitan Police Department (SLMPD) crime data, which are available from January 2008 onward as monthly CSV releases on their website (<http:www.slmpd.org/Crimereports.shtml>). Once data are validated and created (monthly data releases have varying numbers of columns as well as different column names and formats), 'compstatr' also provides functions for categorizing and mapping crimes in St. Louis. The categorization tools that are provided will also work with any police department that uses 5 and 6 digit numeric codes to identify specific crimes. These data provide researchers and policy makers detailed data for St. Louis, which in the last several years has had some of the highest or the highest violent crime rates in the United States.
Author: Christopher Prener [aut, cre], Cree Foeller [aut], Taylor Braswell [com]
Maintainer: Christopher Prener <chris.prener@slu.edu>

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Package geojsonR updated to version 1.0.7 with previous version 1.0.6 dated 2018-09-23

Title: A GeoJson Processing Toolkit
Description: Includes functions for processing GeoJson objects <https://en.wikipedia.org/wiki/GeoJSON> relying on 'RFC 7946' <https://tools.ietf.org/pdf/rfc7946.pdf>. The geojson encoding is based on 'json11', a tiny JSON library for 'C++11' <https://github.com/dropbox/json11>. Furthermore, the source code is exported in R through the 'Rcpp' and 'RcppArmadillo' packages.
Author: Lampros Mouselimis <mouselimislampros@gmail.com>
Maintainer: Lampros Mouselimis <mouselimislampros@gmail.com>

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Package ShortForm updated to version 0.4.3 with previous version 0.4.2 dated 2018-10-17

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

Diff between ShortForm versions 0.4.2 dated 2018-10-17 and 0.4.3 dated 2019-08-07

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Package quantreg updated to version 5.51 with previous version 5.42.1 dated 2019-07-27

Title: Quantile Regression
Description: Estimation and inference methods for models of conditional quantiles: Linear and nonlinear parametric and non-parametric (total variation penalized) models for conditional quantiles of a univariate response and several methods for handling censored survival data. Portfolio selection methods based on expected shortfall risk are also included.
Author: Roger Koenker [cre, aut], Stephen Portnoy [ctb] (Contributions to Censored QR code), Pin Tian Ng [ctb] (Contributions to Sparse QR code), Achim Zeileis [ctb] (Contributions to dynrq code essentially identical to his dynlm code), Philip Grosjean [ctb] (Contributions to nlrq code), Brian D Ripley [trl, ctb] (Initial (2001) R port from S (to my everlasting shame -- how could I have been so slow to adopt R!) and for numerous other suggestions and useful advice)
Maintainer: Roger Koenker <rkoenker@illinois.edu>

Diff between quantreg versions 5.42.1 dated 2019-07-27 and 5.51 dated 2019-08-07

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Package markdown updated to version 1.1 with previous version 1.0 dated 2019-06-07

Title: Render Markdown with the C Library 'Sundown'
Description: Provides R bindings to the 'Sundown' Markdown rendering library (<https://github.com/vmg/sundown>). Markdown is a plain-text formatting syntax that can be converted to 'XHTML' or other formats. See <http://en.wikipedia.org/wiki/Markdown> for more information about Markdown.
Author: JJ Allaire [aut], Jeffrey Horner [aut], Yihui Xie [aut, cre] (<https://orcid.org/0000-0003-0645-5666>), Henrik Bengtsson [ctb], Jim Hester [ctb], Yixuan Qiu [ctb], Kohske Takahashi [ctb], Adam November [ctb], Nacho Caballero [ctb], Jeroen Ooms [ctb], Thomas Leeper [ctb], Joe Cheng [ctb], Andrzej Oles [ctb], Vicent Marti [aut, cph] (The Sundown library), Natacha Porte [aut, cph] (The Sundown library), RStudio [cph]
Maintainer: Yihui Xie <xie@yihui.name>

Diff between markdown versions 1.0 dated 2019-06-07 and 1.1 dated 2019-08-07

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New package DistributionTest with initial version 1.0
Package: DistributionTest
Type: Package
Title: Powerful Goodness-of-Fit Tests Based on the Likelihood Ratio
Version: 1.0
Date: 2019-08-02
Author: Ning Cui [aut, cre], Maoyuan Zhou [ctb]
Maintainer: Ning Cui <2433971953@qq.com>
Description: Provides new types of omnibus tests which are generally much more powerful than traditional tests (including the Kolmogorov-Smirnov, Cramer-von Mises and Anderson-Darling tests),see Zhang (2002) <doi:10.1111/1467-9868.00337>.
License: GPL (>= 3)
Imports: stats, MASS
Repository: CRAN
NeedsCompilation: no
Packaged: 2019-08-07 03:44:52 UTC; Lenovo
Date/Publication: 2019-08-07 15:20:03 UTC

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New package ClimMobTools with initial version 0.2-6
Package: ClimMobTools
Type: Package
Title: Tools for Crowdsourcing Citizen Science in Agriculture
Version: 0.2-6
Authors@R: c(person("Kaue", "de Sousa", email = "kaue.desousa@inn.no", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-7571-7845")), person("Jacob", "van Etten", role = c("aut", "ctb"), comment = c(ORCID = "0000-0001-7554-2558")), person("Sam", "Dumble", role = c("aut", "ctb")), person("Brandon", "Madriz", role = c("aut","ctb")), person("Carlos", "Quiros", role = c("aut","ctb")))
Maintainer: Kaue de Sousa <kaue.desousa@inn.no>
URL: https://agrobioinfoservices.github.io/ClimMobTools/
BugReports: https://github.com/agrobioinfoservices/ClimMobTools/issues
Description: Toolkit for the 'ClimMob' platform in R. 'ClimMob' is an open source software for crowdsourcing citizen science in agriculture <https://climmob.net/climmob3/>. Developed by van Etten et al. (2019) <doi:10.1017/S0014479716000739>, it turns the research paradigm on its head; instead of a few researchers designing complicated trials to compare several technologies in search of the best solutions, it enables many farmers to carry out reasonably simple experiments that taken together can offer even more information. 'ClimMobTools' enables project managers to deep explore and analyse their 'ClimMob' data in R.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10)
Imports: httr, jsonlite, Matrix, methods, nasapower, PlackettLuce, raster, RSpectra, tibble, tidyr, utils
Suggests: psychotree, psychotools, qvcalc, knitr, rmarkdown, testthat (>= 2.1.0)
Language: en-GB
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-08-07 10:09:54 UTC; kaued
Author: Kaue de Sousa [aut, cre] (<https://orcid.org/0000-0002-7571-7845>), Jacob van Etten [aut, ctb] (<https://orcid.org/0000-0001-7554-2558>), Sam Dumble [aut, ctb], Brandon Madriz [aut, ctb], Carlos Quiros [aut, ctb]
Repository: CRAN
Date/Publication: 2019-08-07 16:00:02 UTC

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Package shrinkTVP updated to version 1.0.2 with previous version 1.0.1 dated 2019-07-15

Title: Efficient Bayesian Inference for Time-Varying Parameter Models with Shrinkage
Description: Efficient Markov chain Monte Carlo (MCMC) algorithms for fully Bayesian estimation of time-varying parameter models with shrinkage priors. Details on the algorithms used are provided in Bitto and Frühwirth-Schnatter (2019) <doi:10.1016/j.jeconom.2018.11.006>.
Author: Peter Knaus [aut, cre] (<https://orcid.org/0000-0001-6498-7084>), Angela Bitto-Nemling [aut], Annalisa Cadonna [aut] (<https://orcid.org/0000-0003-0360-7628>), Sylvia Frühwirth-Schnatter [aut] (<https://orcid.org/0000-0003-0516-5552>), Daniel Winkler [ctb], Kemal Dingic [ctb]
Maintainer: Peter Knaus <peter.knaus@wu.ac.at>

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Package bioOED updated to version 0.2.1 with previous version 0.1.4 dated 2018-04-17

Title: Sensitivity Analysis and Optimum Experiment Design for Microbial Inactivation
Description: Extends the bioinactivation package with functions for Sensitivity Analysis and Optimum Experiment Design.
Author: Alberto Garre [aut, cre], Jose Lucas Penalver-Soto [aut], Pablo S. Fernandez [aut], Jose A. Egea [aut]
Maintainer: Alberto Garre <garre.alberto@gmail.com>

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Package OpenML updated to version 1.9 with previous version 1.8 dated 2018-03-02

Title: Open Machine Learning and Open Data Platform
Description: We provide an R interface to 'OpenML.org' which is an online machine learning platform where researchers can access open data, download and upload data sets, share their machine learning tasks and experiments and organize them online to work and collaborate with other researchers. The R interface allows to query for data sets with specific properties, and allows the downloading and uploading of data sets, tasks, flows and runs. See <https://www.openml.org/guide/api> for more information.
Author: Giuseppe Casalicchio <giuseppe.casalicchio@stat.uni-muenchen.de>, Bernd Bischl <bernd_bischl@gmx.net>, Dominik Kirchhoff <dom.kirchhoff@gmail.com>, Michel Lang <michellang@gmail.com>, Benjamin Hofner <benjamin.hofner@fau.de>, Jakob Bossek <j.bossek@gmail.com>, Pascal Kerschke <kerschke@uni-muenster.de>, Joaquin Vanschoren <joaquin.vanschoren@gmail.com>
Maintainer: Giuseppe Casalicchio <giuseppe.casalicchio@stat.uni-muenchen.de>

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Package onelogin updated to version 0.2.0 with previous version 0.1.0 dated 2019-07-30

Title: Interact with the 'OneLogin' API
Description: The identity provider ['OneLogin']<http://onelogin.com> is used for authentication via Single Sign On (SSO). This package provides an R interface to their API.
Author: Alex Gold [aut, cre], Cole Arendt [ctb]
Maintainer: Alex Gold <alexkgold@gmail.com>

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Package ClinReport updated to version 0.9.1.13.1 with previous version 0.9.1.12 dated 2019-04-02

Title: Statistical Reporting for Scientific Publications, Epidemiological Studies and Clinical Trials
Description: Export to 'Microsoft Word' or R markdown documents nicely formatted tables of descriptive or inferential statistics. Can be used within the scope of clinical trials, or for any scientific publications. Descriptive tables for quantitative statistics (mean, median, max etc..) and/or qualitative statistics (frequencies and percentages) are available along with formatted tables of Least Square Means of Linear Models, Linear Mixed Models, Cox Models and Generalized Linear Mixed Models. It works mainly with 'emmeans' 'officer' and 'flextable' packages.
Author: Jean-Francois Collin
Maintainer: Jean-Francois Collin <jfcollin@live.fr>

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Package RQuantLib updated to version 0.4.10 with previous version 0.4.9 dated 2019-05-19

Title: R Interface to the 'QuantLib' Library
Description: The 'RQuantLib' package makes parts of 'QuantLib' accessible from R The 'QuantLib' project aims to provide a comprehensive software framework for quantitative finance. The goal is to provide a standard open source library for quantitative analysis, modeling, trading, and risk management of financial assets.
Author: Dirk Eddelbuettel, Khanh Nguyen (2009-2010), Terry Leitch (since 2016)
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package hmm.discnp updated to version 2.1-11 with previous version 2.1-5 dated 2018-11-26

Title: Hidden Markov Models with Discrete Non-Parametric Observation Distributions
Description: Fits hidden Markov models with discrete non-parametric observation distributions to data sets. The observations may be univariate or bivariate. Simulates data from such models. Finds most probable underlying hidden states, the most probable sequences of such states, and the log likelihood of a collection of observations given the parameters of the model. Auxiliary predictors are accommodated in the univariate setting.
Author: Rolf Turner
Maintainer: Rolf Turner <r.turner@auckland.ac.nz>

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Package tikzDevice updated to version 0.12.3 with previous version 0.12 dated 2018-07-02

Title: R Graphics Output in LaTeX Format
Description: Provides a graphics output device for R that records plots in a LaTeX-friendly format. The device transforms plotting commands issued by R functions into LaTeX code blocks. When included in a LaTeX document, these blocks are interpreted with the help of 'TikZ'---a graphics package for TeX and friends written by Till Tantau. Using the 'tikzDevice', the text of R plots can contain LaTeX commands such as mathematical formula. The device also allows arbitrary LaTeX code to be inserted into the output stream.
Author: Charlie Sharpsteen [aut], Cameron Bracken [aut], Kirill Müller [ctb], Yihui Xie [ctb], Ralf Stubner [cre], Nico Bellack [ctb]
Maintainer: Ralf Stubner <ralf.stubner@gmail.com>

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Package SCORPIUS updated to version 1.0.4.1 with previous version 1.0.4 dated 2019-08-05

Title: Inferring Developmental Chronologies from Single-Cell RNA Sequencing Data
Description: An accurate and easy tool for performing linear trajectory inference on single cells using single-cell RNA sequencing data. In addition, SCORPIUS provides functions for discovering the most important genes with respect to the reconstructed trajectory, as well as nice visualisation tools. Cannoodt et al. (2016) <doi:10.1101/079509>.
Author: Robrecht Cannoodt [aut, cre] (<https://orcid.org/0000-0003-3641-729X>, rcannood), Wouter Saelens [ctb] (<https://orcid.org/0000-0002-7114-6248>, zouter)
Maintainer: Robrecht Cannoodt <rcannood@gmail.com>

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Package Epi updated to version 2.38 with previous version 2.37 dated 2019-05-23

Title: A Package for Statistical Analysis in Epidemiology
Description: Functions for demographic and epidemiological analysis in the Lexis diagram, i.e. register and cohort follow-up data, in particular representation, manipulation and simulation of multistate data - the Lexis suite of functions, which includes interfaces to 'mstate', 'etm' and 'cmprsk' packages. Also contains functions for Age-Period-Cohort and Lee-Carter modeling and a function for interval censored data and some useful functions for tabulation and plotting, as well as a number of epidemiological data sets.
Author: Bendix Carstensen [aut, cre], Martyn Plummer [aut], Esa Laara [ctb], Michael Hills [ctb]
Maintainer: Bendix Carstensen <b@bxc.dk>

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Package dyndimred updated to version 1.0.2 with previous version 1.0.1 dated 2019-05-24

Title: Dimensionality Reduction Methods in a Common Format
Description: Provides a common interface for applying dimensionality reduction methods, such as Principal Component Analysis ('PCA'), Independent Component Analysis ('ICA'), diffusion maps, Locally-Linear Embedding ('LLE'), t-distributed Stochastic Neighbor Embedding ('t-SNE'), and Uniform Manifold Approximation and Projection ('UMAP'). Has built-in support for sparse matrices.
Author: Robrecht Cannoodt [aut] (<https://orcid.org/0000-0003-3641-729X>, rcannood), Wouter Saelens [aut, cre] (<https://orcid.org/0000-0002-7114-6248>, zouter)
Maintainer: Wouter Saelens <wouter.saelens@gmail.com>

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Package qrng updated to version 0.0-6 with previous version 0.0-5 dated 2018-06-21

Title: (Randomized) Quasi-Random Number Generators
Description: Functionality for generating (randomized) quasi-random numbers in high dimensions.
Author: Marius Hofert [aut, cre], Christiane Lemieux [aut]
Maintainer: Marius Hofert <marius.hofert@uwaterloo.ca>

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Package nngeo updated to version 0.2.9 with previous version 0.2.8 dated 2019-05-12

Title: k-Nearest Neighbor Join for Spatial Data
Description: K-nearest neighbor search for projected and non-projected 'sf' spatial layers. Nearest neighbor search uses (1) C code from 'GeographicLib' for lon-lat point layers, (2) function nn2() from package 'RANN' for projected point layers, or (3) function st_distance() from package 'sf' for line or polygon layers.
Author: Michael Dorman [aut, cre], Johnathan Rush [ctb], Ian Hough [ctb], Charles F.F Karney [ctb, cph] (Author of included C code from 'GeographicLib' for geodesic distance)
Maintainer: Michael Dorman <dorman@post.bgu.ac.il>

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Package netmeta updated to version 1.1-0 with previous version 1.0-1 dated 2019-01-02

Title: Network Meta-Analysis using Frequentist Methods
Description: A comprehensive set of functions providing frequentist methods for network meta-analysis and supporting Schwarzer et al. (2015) <DOI:10.1007/978-3-319-21416-0>, Chapter 8 "Network Meta-Analysis": - frequentist network meta-analysis following Rücker (2012) <DOI:10.1002/jrsm.1058>; - net heat plot and design-based decomposition of Cochran's Q according to Krahn et al. (2013) <DOI:10.1186/1471-2288-13-35>; - measures characterizing the flow of evidence between two treatments by König et al. (2013) <DOI:10.1002/sim.6001>; - ranking of treatments (frequentist analogue of SUCRA) according to Rücker & Schwarzer (2015) <DOI:10.1186/s12874-015-0060-8>; - partial order of treatment rankings ('poset') and Hasse diagram for 'poset' (Carlsen & Bruggemann, 2014) <DOI:10.1002/cem.2569>; (Rücker & Schwarzer, 2017) <DOI:10.1002/jrsm.1270>; - split direct and indirect evidence to check consistency (Dias et al., 2010) <DOI:10.1002/sim.3767>, (Efthimiou et al., 2019) <DOI:10.1002/sim.8158>; - league table with network meta-analysis results; - additive network meta-analysis for combinations of treatments (Rücker et al., 2019) <DOI:10.1002/bimj.201800167>; - network meta-analysis of binary data using the Mantel-Haenszel or non-central hypergeometric distribution method (Efthimiou et al., 2019) <DOI:10.1002/sim.8158>; - 'comparison-adjusted' funnel plot (Chaimani & Salanti, 2012) <DOI:10.1002/jrsm.57>; - automated drawing of network graphs described in Rücker & Schwarzer (2016) <DOI:10.1002/jrsm.1143>.
Author: Gerta Rücker [aut] (<https://orcid.org/0000-0002-2192-2560>), Ulrike Krahn [aut], Jochem König [aut] (<https://orcid.org/0000-0003-4683-0360>), Orestis Efthimiou [aut] (<https://orcid.org/0000-0002-0955-7572>), Guido Schwarzer [aut, cre] (<https://orcid.org/0000-0001-6214-9087>)
Maintainer: Guido Schwarzer <sc@imbi.uni-freiburg.de>

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Package landscapemetrics updated to version 1.2.1 with previous version 1.2 dated 2019-07-02

Title: Landscape Metrics for Categorical Map Patterns
Description: Calculates landscape metrics for categorical landscape patterns in a tidy workflow. 'landscapemetrics' reimplements the most common metrics from 'FRAGSTATS' (<https://www.umass.edu/landeco/research/fragstats/fragstats.html>) and new ones from the current literature on landscape metrics. This package supports 'raster' spatial objects and takes RasterLayer, RasterStacks, RasterBricks or lists of RasterLayer from the 'raster' package as input arguments. It further provides utility functions to visualize patches, select metrics and building blocks to develop new metrics.
Author: Maximillian H.K. Hesselbarth [aut, cre] (<https://orcid.org/0000-0003-1125-9918>), Marco Sciaini [aut] (<https://orcid.org/0000-0002-3042-5435>), Jakub Nowosad [aut] (<https://orcid.org/0000-0002-1057-3721>), Sebastian Hanss [aut] (<https://orcid.org/0000-0002-3990-4897>), Laura J. Graham [ctb] (Input on package structure), Jeffrey Hollister [ctb] (Input on package structure), Kimberly A. With [ctb] (Input on package structure), Florian Privé [ctb] (Original author of underlying C++ code for get_nearestneighbour() function), Jeremy VanDerWal [ctb] (Original author of underlying C code for get_patches() function), Matt Strimas-Mackey [ctb] (Bugfix in sample_metrics())
Maintainer: Maximillian H.K. Hesselbarth <maximilian.hesselbarth@uni-goettingen.de>

Diff between landscapemetrics versions 1.2 dated 2019-07-02 and 1.2.1 dated 2019-08-07

 DESCRIPTION                                       |    6 
 MD5                                               |  744 ++--
 NAMESPACE                                         | 1874 +++++-----
 NEWS.md                                           |  229 -
 R/RcppExports.R                                   |  202 -
 R/calculate_correlation.R                         |  364 +-
 R/calculate_lsm.R                                 |  936 ++---
 R/construct_buffer.R                              |  360 +-
 R/data.R                                          |  250 -
 R/data_info.R                                     |   86 
 R/extract_lsm.R                                   |  870 ++--
 R/get_patches.R                                   |  668 +--
 R/landscapemetrics-package.R                      |  106 
 R/list_lsm.R                                      |  410 +-
 R/lsm_l_condent.R                                 |  354 +-
 R/lsm_l_ent.R                                     |  308 -
 R/lsm_l_joinent.R                                 |  336 -
 R/lsm_l_mutinf.R                                  |  352 -
 R/matrix_to_raster.R                              |  164 
 R/onUnload.R                                      |   16 
 R/options_landscapemetrics.R                      |   64 
 R/pad_raster.R                                    |  546 +--
 R/proj_info.R                                     |  104 
 R/sample_lsm.R                                    |  994 ++---
 R/scale_sample.R                                  |  802 ++--
 R/scale_window.R                                  |  780 ++--
 R/show_correlation.R                              |  588 +--
 R/spatialize_lsm.R                                |  592 +--
 R/window_lsm.R                                    |  982 ++---
 build/vignette.rds                                |binary
 inst/CITATION                                     |   28 
 inst/doc/getstarted.R                             |  190 -
 inst/doc/getstarted.Rmd                           |  364 +-
 inst/doc/getstarted.html                          | 1192 +++---
 man/augusta_nlcd.Rd                               |   42 
 man/calculate_correlation.Rd                      |   68 
 man/calculate_lsm.Rd                              |  248 -
 man/check_landscape.Rd                            |   96 
 man/construct_buffer.Rd                           |  120 
 man/data_info.Rd                                  |   54 
 man/extract_lsm.Rd                                |  196 -
 man/figures/README-unnamed-chunk-1-1.png          |binary
 man/fragstats_class_augusta_nlcd.Rd               |   32 
 man/fragstats_class_landscape.Rd                  |   32 
 man/fragstats_class_podlasie.Rd                   |   32 
 man/fragstats_landscape_augusta_nlcd.Rd           |   32 
 man/fragstats_landscape_landscape.Rd              |   32 
 man/fragstats_landscape_podlasie.Rd               |   32 
 man/fragstats_patch_augusta_nlcd.Rd               |   32 
 man/fragstats_patch_landscape.Rd                  |   32 
 man/fragstats_patch_podlasie.Rd                   |   32 
 man/get_adjacencies.Rd                            |  156 
 man/get_boundaries.Rd                             |  126 
 man/get_circumscribingcircle.Rd                   |  122 
 man/get_nearestneighbour.Rd                       |  104 
 man/get_patches.Rd                                |  194 -
 man/get_unique_values.Rd                          |  126 
 man/landscape.Rd                                  |   36 
 man/landscapemetrics.Rd                           |   92 
 man/list_lsm.Rd                                   |  112 
 man/lsm_abbreviations_names.Rd                    |   50 
 man/lsm_c_ai.Rd                                   |  126 
 man/lsm_c_area_cv.Rd                              |  134 
 man/lsm_c_area_mn.Rd                              |  136 
 man/lsm_c_area_sd.Rd                              |  142 
 man/lsm_c_ca.Rd                                   |  134 
 man/lsm_c_cai_cv.Rd                               |  166 
 man/lsm_c_cai_mn.Rd                               |  160 
 man/lsm_c_cai_sd.Rd                               |  164 
 man/lsm_c_circle_cv.Rd                            |  150 
 man/lsm_c_circle_mn.Rd                            |  146 
 man/lsm_c_circle_sd.Rd                            |  146 
 man/lsm_c_clumpy.Rd                               |  122 
 man/lsm_c_cohesion.Rd                             |  136 
 man/lsm_c_contig_cv.Rd                            |  156 
 man/lsm_c_contig_mn.Rd                            |  154 
 man/lsm_c_contig_sd.Rd                            |  156 
 man/lsm_c_core_cv.Rd                              |  158 
 man/lsm_c_core_mn.Rd                              |  154 
 man/lsm_c_core_sd.Rd                              |  156 
 man/lsm_c_cpland.Rd                               |  150 
 man/lsm_c_dcad.Rd                                 |  156 
 man/lsm_c_dcore_cv.Rd                             |  164 
 man/lsm_c_dcore_mn.Rd                             |  158 
 man/lsm_c_dcore_sd.Rd                             |  164 
 man/lsm_c_division.Rd                             |  128 
 man/lsm_c_ed.Rd                                   |  148 
 man/lsm_c_enn_cv.Rd                               |  158 
 man/lsm_c_enn_mn.Rd                               |  158 
 man/lsm_c_enn_sd.Rd                               |  158 
 man/lsm_c_frac_cv.Rd                              |  146 
 man/lsm_c_frac_mn.Rd                              |  138 
 man/lsm_c_frac_sd.Rd                              |  144 
 man/lsm_c_gyrate_cv.Rd                            |  148 
 man/lsm_c_gyrate_mn.Rd                            |  146 
 man/lsm_c_gyrate_sd.Rd                            |  146 
 man/lsm_c_iji.Rd                                  |  132 
 man/lsm_c_lpi.Rd                                  |  128 
 man/lsm_c_lsi.Rd                                  |  134 
 man/lsm_c_mesh.Rd                                 |  138 
 man/lsm_c_ndca.Rd                                 |  158 
 man/lsm_c_nlsi.Rd                                 |  132 
 man/lsm_c_np.Rd                                   |  120 
 man/lsm_c_pafrac.Rd                               |  152 
 man/lsm_c_para_cv.Rd                              |  140 
 man/lsm_c_para_mn.Rd                              |  140 
 man/lsm_c_para_sd.Rd                              |  140 
 man/lsm_c_pd.Rd                                   |  130 
 man/lsm_c_pladj.Rd                                |  114 
 man/lsm_c_pland.Rd                                |  126 
 man/lsm_c_shape_cv.Rd                             |  142 
 man/lsm_c_shape_mn.Rd                             |  142 
 man/lsm_c_shape_sd.Rd                             |  142 
 man/lsm_c_split.Rd                                |  134 
 man/lsm_c_tca.Rd                                  |  156 
 man/lsm_c_te.Rd                                   |  140 
 man/lsm_l_ai.Rd                                   |  130 
 man/lsm_l_area_cv.Rd                              |  134 
 man/lsm_l_area_mn.Rd                              |  136 
 man/lsm_l_area_sd.Rd                              |  132 
 man/lsm_l_cai_cv.Rd                               |  166 
 man/lsm_l_cai_mn.Rd                               |  160 
 man/lsm_l_cai_sd.Rd                               |  164 
 man/lsm_l_circle_cv.Rd                            |  146 
 man/lsm_l_circle_mn.Rd                            |  144 
 man/lsm_l_circle_sd.Rd                            |  148 
 man/lsm_l_cohesion.Rd                             |  126 
 man/lsm_l_condent.Rd                              |  134 
 man/lsm_l_contag.Rd                               |  136 
 man/lsm_l_contig_cv.Rd                            |  156 
 man/lsm_l_contig_mn.Rd                            |  154 
 man/lsm_l_contig_sd.Rd                            |  156 
 man/lsm_l_core_cv.Rd                              |  160 
 man/lsm_l_core_mn.Rd                              |  156 
 man/lsm_l_core_sd.Rd                              |  158 
 man/lsm_l_dcad.Rd                                 |  156 
 man/lsm_l_dcore_cv.Rd                             |  164 
 man/lsm_l_dcore_mn.Rd                             |  158 
 man/lsm_l_dcore_sd.Rd                             |  162 
 man/lsm_l_division.Rd                             |  134 
 man/lsm_l_ed.Rd                                   |  148 
 man/lsm_l_enn_cv.Rd                               |  158 
 man/lsm_l_enn_mn.Rd                               |  158 
 man/lsm_l_enn_sd.Rd                               |  158 
 man/lsm_l_ent.Rd                                  |  116 
 man/lsm_l_frac_cv.Rd                              |  146 
 man/lsm_l_frac_mn.Rd                              |  144 
 man/lsm_l_frac_sd.Rd                              |  144 
 man/lsm_l_gyrate_cv.Rd                            |  148 
 man/lsm_l_gyrate_mn.Rd                            |  146 
 man/lsm_l_gyrate_sd.Rd                            |  146 
 man/lsm_l_iji.Rd                                  |  134 
 man/lsm_l_joinent.Rd                              |  128 
 man/lsm_l_lpi.Rd                                  |  128 
 man/lsm_l_lsi.Rd                                  |  134 
 man/lsm_l_mesh.Rd                                 |  138 
 man/lsm_l_msidi.Rd                                |  132 
 man/lsm_l_msiei.Rd                                |  122 
 man/lsm_l_mutinf.Rd                               |  130 
 man/lsm_l_ndca.Rd                                 |  158 
 man/lsm_l_np.Rd                                   |  122 
 man/lsm_l_pafrac.Rd                               |  152 
 man/lsm_l_para_cv.Rd                              |  140 
 man/lsm_l_para_mn.Rd                              |  140 
 man/lsm_l_para_sd.Rd                              |  140 
 man/lsm_l_pd.Rd                                   |  130 
 man/lsm_l_pladj.Rd                                |  114 
 man/lsm_l_pr.Rd                                   |  110 
 man/lsm_l_prd.Rd                                  |  120 
 man/lsm_l_rpr.Rd                                  |  136 
 man/lsm_l_shape_cv.Rd                             |  142 
 man/lsm_l_shape_mn.Rd                             |  142 
 man/lsm_l_shape_sd.Rd                             |  142 
 man/lsm_l_shdi.Rd                                 |  122 
 man/lsm_l_shei.Rd                                 |  126 
 man/lsm_l_sidi.Rd                                 |  132 
 man/lsm_l_siei.Rd                                 |  132 
 man/lsm_l_split.Rd                                |  134 
 man/lsm_l_ta.Rd                                   |  124 
 man/lsm_l_tca.Rd                                  |  154 
 man/lsm_l_te.Rd                                   |  124 
 man/lsm_p_area.Rd                                 |  138 
 man/lsm_p_cai.Rd                                  |  166 
 man/lsm_p_circle.Rd                               |  148 
 man/lsm_p_contig.Rd                               |  158 
 man/lsm_p_core.Rd                                 |  164 
 man/lsm_p_enn.Rd                                  |  158 
 man/lsm_p_frac.Rd                                 |  146 
 man/lsm_p_gyrate.Rd                               |  142 
 man/lsm_p_ncore.Rd                                |  166 
 man/lsm_p_para.Rd                                 |  140 
 man/lsm_p_perim.Rd                                |  118 
 man/lsm_p_shape.Rd                                |  144 
 man/matrix_to_raster.Rd                           |   82 
 man/options_landscapemetrics.Rd                   |   56 
 man/pad_raster.Rd                                 |  136 
 man/podlasie_ccilc.Rd                             |   36 
 man/proj_info.Rd                                  |   54 
 man/raster_to_points.Rd                           |   86 
 man/rcpp_cell_from_xy.Rd                          |   38 
 man/rcpp_create_neighborhood.Rd                   |   38 
 man/rcpp_get_nearest_neighbor.Rd                  |   44 
 man/rcpp_xy_from_matrix.Rd                        |   36 
 man/sample_lsm.Rd                                 |  234 -
 man/scale_sample.Rd                               |  170 
 man/scale_window.Rd                               |  178 -
 man/show_cores.Rd                                 |  148 
 man/show_correlation.Rd                           |   90 
 man/show_lsm.Rd                                   |  140 
 man/show_patches.Rd                               |  112 
 man/spatialize_lsm.Rd                             |  144 
 man/window_lsm.Rd                                 |  172 
 tests/testthat.R                                  |   10 
 tests/testthat/helper-brick.R                     |    8 
 tests/testthat/helper-landscapes.R                |   34 
 tests/testthat/helper-points.R                    |   36 
 tests/testthat/test-calculate-lsm.R               |  238 -
 tests/testthat/test-calculate_correlation.R       |  140 
 tests/testthat/test-check-landscape.R             |  138 
 tests/testthat/test-construct-buffer.R            |   62 
 tests/testthat/test-extract-lsm.R                 |  272 -
 tests/testthat/test-get-circumscribungcircle.R    |  146 
 tests/testthat/test-get-patches.R                 |   46 
 tests/testthat/test-get-unique-values.R           |  182 -
 tests/testthat/test-list-lsm.R                    |  182 -
 tests/testthat/test-lsm-c-area-cv.R               |   48 
 tests/testthat/test-lsm-c-area-mn.R               |   50 
 tests/testthat/test-lsm-c-area-sd.R               |   48 
 tests/testthat/test-lsm-c-ca.R                    |   52 
 tests/testthat/test-lsm-c-cai-cv.R                |   50 
 tests/testthat/test-lsm-c-cai-mn.R                |   50 
 tests/testthat/test-lsm-c-cai-sd.R                |   46 
 tests/testthat/test-lsm-c-circle-cv.R             |   52 
 tests/testthat/test-lsm-c-circle-mn.R             |   48 
 tests/testthat/test-lsm-c-circle-sd.R             |   48 
 tests/testthat/test-lsm-c-clumpy.R                |   48 
 tests/testthat/test-lsm-c-cohesion.R              |   50 
 tests/testthat/test-lsm-c-contig-cv.R             |   50 
 tests/testthat/test-lsm-c-contig-mn.R             |   50 
 tests/testthat/test-lsm-c-contig-sd.R             |   50 
 tests/testthat/test-lsm-c-core-cv.R               |   46 
 tests/testthat/test-lsm-c-core-mn.R               |   46 
 tests/testthat/test-lsm-c-core-sd.R               |   46 
 tests/testthat/test-lsm-c-cpland.R                |   48 
 tests/testthat/test-lsm-c-dcad.R                  |   48 
 tests/testthat/test-lsm-c-dcore_cv.R              |   46 
 tests/testthat/test-lsm-c-dcore_mn.R              |   46 
 tests/testthat/test-lsm-c-dcore_sd.R              |   46 
 tests/testthat/test-lsm-c-division.R              |   48 
 tests/testthat/test-lsm-c-ed.R                    |   48 
 tests/testthat/test-lsm-c-enn-cv.R                |   46 
 tests/testthat/test-lsm-c-enn-mn.R                |   46 
 tests/testthat/test-lsm-c-enn-sd.R                |   46 
 tests/testthat/test-lsm-c-frac-cv.R               |   46 
 tests/testthat/test-lsm-c-frac-mn.R               |   46 
 tests/testthat/test-lsm-c-frac-sd.R               |   46 
 tests/testthat/test-lsm-c-gyrate-cv.R             |   46 
 tests/testthat/test-lsm-c-gyrate-mn.R             |   46 
 tests/testthat/test-lsm-c-gyrate-sd.R             |   46 
 tests/testthat/test-lsm-c-iji.R                   |   68 
 tests/testthat/test-lsm-c-lpi.R                   |   48 
 tests/testthat/test-lsm-c-lsi.R                   |   48 
 tests/testthat/test-lsm-c-mesh.R                  |   48 
 tests/testthat/test-lsm-c-ndca.R                  |   48 
 tests/testthat/test-lsm-c-nlsi.R                  |   48 
 tests/testthat/test-lsm-c-np.R                    |   48 
 tests/testthat/test-lsm-c-pafrac.R                |   76 
 tests/testthat/test-lsm-c-para-cv.R               |   46 
 tests/testthat/test-lsm-c-para-mn.R               |   46 
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 tests/testthat/test-lsm-c-pd.R                    |   48 
 tests/testthat/test-lsm-c-pladj.R                 |   48 
 tests/testthat/test-lsm-c-pland.R                 |   48 
 tests/testthat/test-lsm-c-shape-cv.R              |   46 
 tests/testthat/test-lsm-c-shape-mn.R              |   46 
 tests/testthat/test-lsm-c-shape-sd.R              |   46 
 tests/testthat/test-lsm-c-split.R                 |   48 
 tests/testthat/test-lsm-c-tca.R                   |   48 
 tests/testthat/test-lsm-c-te.R                    |   64 
 tests/testthat/test-lsm-l-ai.R                    |   48 
 tests/testthat/test-lsm-l-area-cv.R               |   46 
 tests/testthat/test-lsm-l-area-mn.R               |   50 
 tests/testthat/test-lsm-l-area-sd.R               |   50 
 tests/testthat/test-lsm-l-cai-cv.R                |   50 
 tests/testthat/test-lsm-l-cai-mn.R                |   50 
 tests/testthat/test-lsm-l-cai-sd.R                |   50 
 tests/testthat/test-lsm-l-circle-cv.R             |   50 
 tests/testthat/test-lsm-l-circle-mn.R             |   50 
 tests/testthat/test-lsm-l-circle-sd.R             |   50 
 tests/testthat/test-lsm-l-cohesion.R              |   48 
 tests/testthat/test-lsm-l-condent.R               |   48 
 tests/testthat/test-lsm-l-contag.R                |   66 
 tests/testthat/test-lsm-l-contig-cv.R             |   46 
 tests/testthat/test-lsm-l-contig-mn.R             |   46 
 tests/testthat/test-lsm-l-contig-sd.R             |   46 
 tests/testthat/test-lsm-l-core-cv.R               |   50 
 tests/testthat/test-lsm-l-core-mn.R               |   50 
 tests/testthat/test-lsm-l-core-sd.R               |   50 
 tests/testthat/test-lsm-l-dcad.R                  |   48 
 tests/testthat/test-lsm-l-dcore-cv.R              |   50 
 tests/testthat/test-lsm-l-dcore-mn.R              |   50 
 tests/testthat/test-lsm-l-dcore-sd.R              |   50 
 tests/testthat/test-lsm-l-division.R              |   48 
 tests/testthat/test-lsm-l-ed.R                    |   48 
 tests/testthat/test-lsm-l-enn-cv.R                |   50 
 tests/testthat/test-lsm-l-enn-mn.R                |   50 
 tests/testthat/test-lsm-l-enn-sd.R                |   50 
 tests/testthat/test-lsm-l-ent.R                   |   48 
 tests/testthat/test-lsm-l-frac-cv.R               |   46 
 tests/testthat/test-lsm-l-frac-mn.R               |   46 
 tests/testthat/test-lsm-l-frac-sd.R               |   46 
 tests/testthat/test-lsm-l-gyrate-cv.R             |   46 
 tests/testthat/test-lsm-l-gyrate-mn.R             |   46 
 tests/testthat/test-lsm-l-gyrate-sd.R             |   48 
 tests/testthat/test-lsm-l-iji.R                   |   68 
 tests/testthat/test-lsm-l-joinent.R               |   48 
 tests/testthat/test-lsm-l-lpi.R                   |   48 
 tests/testthat/test-lsm-l-lsi.R                   |   48 
 tests/testthat/test-lsm-l-mesh.R                  |   48 
 tests/testthat/test-lsm-l-msidi.R                 |   48 
 tests/testthat/test-lsm-l-msiei.R                 |   48 
 tests/testthat/test-lsm-l-mutinf.R                |   48 
 tests/testthat/test-lsm-l-ndca.R                  |   48 
 tests/testthat/test-lsm-l-np.R                    |   48 
 tests/testthat/test-lsm-l-pafrac.R                |   66 
 tests/testthat/test-lsm-l-para-cv.R               |   46 
 tests/testthat/test-lsm-l-para-mn.R               |   46 
 tests/testthat/test-lsm-l-para-sd.R               |   46 
 tests/testthat/test-lsm-l-pd.R                    |   48 
 tests/testthat/test-lsm-l-pladj.R                 |   48 
 tests/testthat/test-lsm-l-pr.R                    |   48 
 tests/testthat/test-lsm-l-prd.R                   |   48 
 tests/testthat/test-lsm-l-rpr.R                   |   48 
 tests/testthat/test-lsm-l-shape-cv.R              |   46 
 tests/testthat/test-lsm-l-shape-mn.R              |   46 
 tests/testthat/test-lsm-l-shape-sd.R              |   46 
 tests/testthat/test-lsm-l-shdi.R                  |   48 
 tests/testthat/test-lsm-l-shei.R                  |   48 
 tests/testthat/test-lsm-l-sidi.R                  |   48 
 tests/testthat/test-lsm-l-siei.R                  |   48 
 tests/testthat/test-lsm-l-split.R                 |   48 
 tests/testthat/test-lsm-l-ta.R                    |   48 
 tests/testthat/test-lsm-l-tca.R                   |   48 
 tests/testthat/test-lsm-l-te.R                    |   66 
 tests/testthat/test-lsm-p-area.R                  |   50 
 tests/testthat/test-lsm-p-cai.R                   |   46 
 tests/testthat/test-lsm-p-circle.R                |   54 
 tests/testthat/test-lsm-p-contig.R                |   50 
 tests/testthat/test-lsm-p-core.R                  |   68 
 tests/testthat/test-lsm-p-enn.R                   |   50 
 tests/testthat/test-lsm-p-frac.R                  |   50 
 tests/testthat/test-lsm-p-gyrate.R                |   50 
 tests/testthat/test-lsm-p-nca.R                   |   50 
 tests/testthat/test-lsm-p-para.R                  |   50 
 tests/testthat/test-lsm-p-perim.R                 |   54 
 tests/testthat/test-lsm-p-shape.R                 |   48 
 tests/testthat/test-matrix-to-raster.R            |   96 
 tests/testthat/test-options-landscapemetrics.R    |   24 
 tests/testthat/test-pad-raster.R                  |   84 
 tests/testthat/test-rcpp-get-coocurrence-matrix.R |  204 -
 tests/testthat/test-rcpp-get-entropy.R            |   46 
 tests/testthat/test-sample-lsm.R                  |  428 +-
 tests/testthat/test-scale-sample.R                |  200 -
 tests/testthat/test-scale-window.R                |  164 
 tests/testthat/test-show-cores.R                  |  106 
 tests/testthat/test-show-correlation.R            |  116 
 tests/testthat/test-show-lsm.R                    |   96 
 tests/testthat/test-show-patches.R                |   74 
 tests/testthat/test-spatialize-lsm.R              |  152 
 tests/testthat/test-unique-values.R               |   26 
 tests/testthat/test-window-lsm.R                  |   84 
 tests/testthat/test_fragstats.R                   | 3884 +++++++++++-----------
 vignettes/getstarted.Rmd                          |  364 +-
 373 files changed, 26580 insertions(+), 26497 deletions(-)

More information about landscapemetrics at CRAN
Permanent link

New package featuretoolsR with initial version 0.4.3
Package: featuretoolsR
Type: Package
Title: Interact with the 'Python' Module 'Featuretools'
Version: 0.4.3
Authors@R: person("Magnus", "Furugård", email = "magnus.furugard@gmail.com", role = c("aut", "cre"))
Maintainer: Magnus Furugård <magnus.furugard@gmail.com>
Description: A 'reticulate'-based interface to the 'Python' module 'Featuretools'. The package grants functionality to interact with 'Pythons' 'Featuretools' module, which allows for automated feature engineering on any data frame. Valid features and new data sets can, after feature synthesis, easily be extracted.
License: MIT + file LICENSE
URL: https://github.com/magnusfurugard/featuretoolsR
BugReports: https://github.com/magnusfurugard/featuretoolsR/issues
Depends: R (>= 3.4.2)
Imports: reticulate, caret, dplyr, purrr, stringr, tibble, magrittr, cli, testthat
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-08-06 15:48:38 UTC; Magnus
Author: Magnus Furugård [aut, cre]
Repository: CRAN
Date/Publication: 2019-08-07 08:40:02 UTC

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Package exactextractr updated to version 0.1.1 with previous version 0.1.0 dated 2019-08-01

Title: Fast Extraction from Raster Datasets using Polygons
Description: Provides a replacement for the 'extract' function from the 'raster' package that is suitable for extracting raster values using 'sf' polygons.
Author: Daniel Baston [aut, cre], ISciences, LLC [cph]
Maintainer: Daniel Baston <dbaston@isciences.com>

Diff between exactextractr versions 0.1.0 dated 2019-08-01 and 0.1.1 dated 2019-08-07

 DESCRIPTION              |    7 +++--
 MD5                      |   11 ++++----
 NEWS.md                  |only
 configure                |   59 +++++++++++++++++++++++++++++++++++------------
 configure.ac             |   36 ++++++++++++++++++++--------
 man/coverage_fraction.Rd |    6 ++++
 src/exact_extract.cpp    |    4 +--
 7 files changed, 89 insertions(+), 34 deletions(-)

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Package EBPRS updated to version 1.1.5 with previous version 1.1.2 dated 2019-02-14

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

Diff between EBPRS versions 1.1.2 dated 2019-02-14 and 1.1.5 dated 2019-08-07

 DESCRIPTION          |   10 +++++-----
 MD5                  |   12 ++++++------
 R/extractInfo.R      |    2 +-
 R/findPara.R         |   17 +++++++++++------
 R/getEffectSize.R    |   16 ++++++++++------
 man/extractInfo.Rd   |    2 +-
 man/getEffectSize.Rd |    2 +-
 7 files changed, 35 insertions(+), 26 deletions(-)

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New package rapbase with initial version 1.10.0
Package: rapbase
Type: Package
Title: Base Functions and Resources for Rapporteket
Version: 1.10.0
Date: 2019-07-23
Authors@R: c( person(given = "Are", family = "Edvardsen", role = c("aut", "cre"), email = "biorakel@gmail.com", comment = c(ORCID = "0000-0002-5210-3656")), person(given = "Kevin Otto", family = "Thon", role = c("aut"), email = "kevin.thon@helse-nord.no"))
Maintainer: Are Edvardsen <biorakel@gmail.com>
Description: Provide common functions and resources for registry specific R-packages at Rapporteket <https://rapporteket.github.io/rapporteket/articles/short_introduction.html>. This package is relevant for developers of packages/registries at Rapporteket.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
Imports: DBI, devtools, digest, gistr, httr, knitr, magrittr, readr, RJDBC, RMariaDB, sendmailR, shiny, utils, yaml
RoxygenNote: 6.1.1
URL: http://github.com/Rapporteket/rapbase
BugReports: http://github.com/Rapporteket/rapbase/issues
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-08-06 08:56:24 UTC; rstudio
Author: Are Edvardsen [aut, cre] (<https://orcid.org/0000-0002-5210-3656>), Kevin Otto Thon [aut]
Repository: CRAN
Date/Publication: 2019-08-07 07:30:02 UTC

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New package planets with initial version 0.1.0
Package: planets
Title: Simple and Accessible Data from all Known Planets
Version: 0.1.0
Authors@R: person(given = "Alejandro", family = "Jiménez Rico", role = c("aut", "cre"), email = "aljrico@gmail.com")
Description: The goal of 'planets' is to provide of very simple and accessible data containing basic information from all known planets.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2019-08-06 11:29:40 UTC; alejandro
Author: Alejandro Jiménez Rico [aut, cre]
Maintainer: Alejandro Jiménez Rico <aljrico@gmail.com>
Repository: CRAN
Date/Publication: 2019-08-07 07:40:02 UTC

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Package tinytex updated to version 0.15 with previous version 0.14 dated 2019-06-25

Title: Helper Functions to Install and Maintain 'TeX Live', and Compile 'LaTeX' Documents
Description: Helper functions to install and maintain the 'LaTeX' distribution named 'TinyTeX' (<https://yihui.name/tinytex/>), a lightweight, cross-platform, portable, and easy-to-maintain version of 'TeX Live'. This package also contains helper functions to compile 'LaTeX' documents, and install missing 'LaTeX' packages automatically.
Author: Yihui Xie [aut, cre, cph] (<https://orcid.org/0000-0003-0645-5666>), RStudio, Inc. [cph], Fernando Cagua [ctb], Ethan Heinzen [ctb]
Maintainer: Yihui Xie <xie@yihui.name>

Diff between tinytex versions 0.14 dated 2019-06-25 and 0.15 dated 2019-08-07

 DESCRIPTION |    6 +++---
 MD5         |    4 ++--
 R/latex.R   |   24 ++++++++++++++----------
 3 files changed, 19 insertions(+), 15 deletions(-)

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Package servr updated to version 0.15 with previous version 0.14 dated 2019-06-11

Title: A Simple HTTP Server to Serve Static Files or Dynamic Documents
Description: Start an HTTP server in R to serve static files, or dynamic documents that can be converted to HTML files (e.g., R Markdown) under a given directory.
Author: Yihui Xie [aut, cre] (<https://orcid.org/0000-0003-0645-5666>), Carson Sievert [ctb], Jesse Anderson [ctb], Ramnath Vaidyanathan [ctb]
Maintainer: Yihui Xie <xie@yihui.name>

Diff between servr versions 0.14 dated 2019-06-11 and 0.15 dated 2019-08-07

 DESCRIPTION |    6 +++---
 MD5         |    6 +++---
 NEWS        |    6 ++++++
 R/static.R  |    3 ++-
 4 files changed, 14 insertions(+), 7 deletions(-)

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Package ggpubr updated to version 0.2.2 with previous version 0.2.1 dated 2019-06-23

Title: 'ggplot2' Based Publication Ready Plots
Description: The 'ggplot2' package is excellent and flexible for elegant data visualization in R. However the default generated plots requires some formatting before we can send them for publication. Furthermore, to customize a 'ggplot', the syntax is opaque and this raises the level of difficulty for researchers with no advanced R programming skills. 'ggpubr' provides some easy-to-use functions for creating and customizing 'ggplot2'- based publication ready plots.
Author: Alboukadel Kassambara [aut, cre]
Maintainer: Alboukadel Kassambara <alboukadel.kassambara@gmail.com>

Diff between ggpubr versions 0.2.1 dated 2019-06-23 and 0.2.2 dated 2019-08-07

 DESCRIPTION               |   17 ++--
 MD5                       |   28 +++----
 NAMESPACE                 |    6 +
 NEWS.md                   |   20 +++++
 R/add_summary.R           |   25 ++++--
 R/compare_means.R         |   10 +-
 R/geom_bracket.R          |only
 R/geom_exec.R             |   14 +++
 R/ggadd.R                 |   13 ++-
 R/ggline.R                |    1 
 R/stat_pvalue_manual.R    |  176 +++++++++++++++++++++++++++++++++-------------
 R/utilities.R             |   11 ++
 man/add_summary.Rd        |   22 +++--
 man/geom_bracket.Rd       |only
 man/ggadd.Rd              |   18 +++-
 man/stat_pvalue_manual.Rd |   41 +++++++---
 16 files changed, 290 insertions(+), 112 deletions(-)

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Package DT updated to version 0.8 with previous version 0.7 dated 2019-06-11

Title: A Wrapper of the JavaScript Library 'DataTables'
Description: Data objects in R can be rendered as HTML tables using the JavaScript library 'DataTables' (typically via R Markdown or Shiny). The 'DataTables' library has been included in this R package. The package name 'DT' is an abbreviation of 'DataTables'.
Author: Yihui Xie [aut, cre], Joe Cheng [aut], Xianying Tan [aut], JJ Allaire [ctb], Maximilian Girlich [ctb], Greg Freedman Ellis [ctb], Johannes Rauh [ctb], jQuery contributors [ctb, cph] (jQuery in htmlwidgets/lib), SpryMedia Limited [ctb, cph] (DataTables in htmlwidgets/lib), Brian Reavis [ctb, cph] (selectize.js in htmlwidgets/lib), Leon Gersen [ctb, cph] (noUiSlider in htmlwidgets/lib), Bartek Szopka [ctb, cph] (jquery.highlight.js in htmlwidgets/lib), RStudio Inc [cph]
Maintainer: Yihui Xie <xie@yihui.name>

Diff between DT versions 0.7 dated 2019-06-11 and 0.8 dated 2019-08-07

 DESCRIPTION            |   13 ++++++-------
 MD5                    |   16 ++++++++--------
 R/datatables.R         |   17 +++++++++++++----
 R/format.R             |   48 ++++++++++++++++++++++++------------------------
 R/shiny.R              |    2 +-
 build/vignette.rds     |binary
 inst/doc/DT.html       |   14 +++++++++-----
 man/dataTableOutput.Rd |    2 +-
 man/datatable.Rd       |    4 +++-
 9 files changed, 65 insertions(+), 51 deletions(-)

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New package TrendSLR with initial version 1.0
Package: TrendSLR
Type: Package
Title: Estimating Trend, Velocity and Acceleration from Sea Level Records
Version: 1.0
Depends: R (>= 3.2.2)
Date: 2019-08-05
Description: Analysis of annual average ocean water level time series, providing improved estimates of trend (mean sea level) and associated real-time velocities and accelerations. Improved trend estimates are based on singular spectrum analysis methods. Various gap-filling options are included to accommodate incomplete time series records. The package also includes a range of diagnostic tools to inspect the components comprising the original time series which enables expert interpretation and selection of likely trend components. A wide range of screen and plot to file options are available in the package.
Author: Phil J Watson <philwatson.slr@gmail.com>
Maintainer: Phil J Watson <philwatson.slr@gmail.com>
License: GPL (>= 3)
LazyData: TRUE
Imports: changepoint (>= 2.1.1), forecast (>= 6.2), plyr (>= 1.8.3), Rssa (>= 0.13-1), tseries (>= 0.10-34), zoo (>= 1.7-12), imputeTS (>= 1.8)
Repository: CRAN
NeedsCompilation: no
RoxygenNote: 6.1.1
Packaged: 2019-08-06 01:16:31 UTC; tiara
Date/Publication: 2019-08-07 05:00:03 UTC

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Package groupedstats updated to version 0.0.8 with previous version 0.0.7 dated 2019-06-05

Title: Grouped Statistical Analyses in a Tidy Way
Description: Collection of functions to run statistical tests across all combinations of multiple grouping variables.
Author: Indrajeet Patil [aut, cre] (<https://orcid.org/0000-0003-1995-6531>)
Maintainer: Indrajeet Patil <patilindrajeet.science@gmail.com>

Diff between groupedstats versions 0.0.7 dated 2019-06-05 and 0.0.8 dated 2019-08-07

 groupedstats-0.0.7/groupedstats/man/compound.Rd                               |only
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 groupedstats-0.0.7/groupedstats/tests/testthat/test_lm_effsize_ci.R           |only
 groupedstats-0.0.7/groupedstats/tests/testthat/test_signif_column.R           |only
 groupedstats-0.0.7/groupedstats/tests/testthat/test_specify_decimal_p.R       |only
 groupedstats-0.0.8/groupedstats/DESCRIPTION                                   |   22 
 groupedstats-0.0.8/groupedstats/MD5                                           |   83 +-
 groupedstats-0.0.8/groupedstats/NAMESPACE                                     |   10 
 groupedstats-0.0.8/groupedstats/NEWS.md                                       |   14 
 groupedstats-0.0.8/groupedstats/R/global_vars.R                               |    8 
 groupedstats-0.0.8/groupedstats/R/grouped_aov.R                               |  126 +--
 groupedstats-0.0.8/groupedstats/R/grouped_lm.R                                |   15 
 groupedstats-0.0.8/groupedstats/R/grouped_lmer.R                              |    6 
 groupedstats-0.0.8/groupedstats/R/grouped_proptest.R                          |    6 
 groupedstats-0.0.8/groupedstats/R/grouped_robustslr.R                         |   21 
 groupedstats-0.0.8/groupedstats/R/grouped_slr.R                               |    7 
 groupedstats-0.0.8/groupedstats/R/grouped_summary.R                           |  337 ++------
 groupedstats-0.0.8/groupedstats/R/grouped_ttest.R                             |   24 
 groupedstats-0.0.8/groupedstats/R/grouped_wilcox.R                            |  124 +--
 groupedstats-0.0.8/groupedstats/R/lm_effsize_ci.R                             |   66 -
 groupedstats-0.0.8/groupedstats/R/reexports.R                                 |   14 
 groupedstats-0.0.8/groupedstats/R/signif_column.R                             |   94 --
 groupedstats-0.0.8/groupedstats/R/specify_decimal_p.R                         |   47 -
 groupedstats-0.0.8/groupedstats/R/utils-tidy.R                                |   24 
 groupedstats-0.0.8/groupedstats/README.md                                     |  388 +++++-----
 groupedstats-0.0.8/groupedstats/inst/WORDLIST                                 |    5 
 groupedstats-0.0.8/groupedstats/man/figures/README-grouped_summary3-1.png     |binary
 groupedstats-0.0.8/groupedstats/man/grouped_aov.Rd                            |   12 
 groupedstats-0.0.8/groupedstats/man/grouped_lm.Rd                             |    6 
 groupedstats-0.0.8/groupedstats/man/grouped_lmer.Rd                           |    4 
 groupedstats-0.0.8/groupedstats/man/grouped_proptest.Rd                       |    2 
 groupedstats-0.0.8/groupedstats/man/grouped_robustslr.Rd                      |    2 
 groupedstats-0.0.8/groupedstats/man/grouped_slr.Rd                            |    9 
 groupedstats-0.0.8/groupedstats/man/grouped_summary.Rd                        |   21 
 groupedstats-0.0.8/groupedstats/man/grouped_ttest.Rd                          |   22 
 groupedstats-0.0.8/groupedstats/man/grouped_wilcox.Rd                         |   10 
 groupedstats-0.0.8/groupedstats/man/lm_effsize_ci.Rd                          |    4 
 groupedstats-0.0.8/groupedstats/man/lm_effsize_standardizer.Rd                |    6 
 groupedstats-0.0.8/groupedstats/man/reexports.Rd                              |    5 
 groupedstats-0.0.8/groupedstats/man/signif_column.Rd                          |   24 
 groupedstats-0.0.8/groupedstats/man/specify_decimal_p.Rd                      |   20 
 groupedstats-0.0.8/groupedstats/tests/README.md                               |   75 +
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 groupedstats-0.0.8/groupedstats/tests/testthat/test-lm_effsize_ci.R           |only
 groupedstats-0.0.8/groupedstats/tests/testthat/test-lm_effsize_standardizer.R |only
 groupedstats-0.0.8/groupedstats/tests/testthat/test-signif_column.R           |only
 groupedstats-0.0.8/groupedstats/tests/testthat/test-specify_decimal_p.R       |only
 48 files changed, 747 insertions(+), 916 deletions(-)

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New package hwordcloud with initial version 0.1.0
Package: hwordcloud
Type: Package
Title: Rendering Word Clouds
Version: 0.1.0
Authors@R: person(given = "Zhenxing", family = "Cheng", email = "czxjnu@163.com", role = c("aut", "cre"))
Description: Provides a way to display word clouds in R. The word cloud is a html widget, so you can use it in interactive documents and 'shiny' applications.
License: MIT + file LICENSE
Date: 2019-08-05
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 3.0.0)
URL: https://github.com/czxa/hwordcloud
BugReports: https://github.com/czxa/hwordcloud/issues
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Imports: htmlwidgets, wordcloud2, shiny, colourpicker
NeedsCompilation: no
Packaged: 2019-08-05 23:28:24 UTC; czx
Author: Zhenxing Cheng [aut, cre]
Maintainer: Zhenxing Cheng <czxjnu@163.com>
Repository: CRAN
Date/Publication: 2019-08-07 04:50:02 UTC

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Package ADAPTS updated to version 0.9.21 with previous version 0.9.20 dated 2019-06-17

Title: Automated Deconvolution Augmentation of Profiles for Tissue Specific Cells
Description: Augments existing or de-novo cell-type signature matrices to deconvolve bulk gene expression data. Useful for building signature matrices from single cell RNAseq data, determine cell type deconvolution spillover, and hierarchical deconvolution to use spillover to increase deconvolution accuracy. Please cite: Danziger SA et al. (2019) ADAPTS: Automated Deconvolution Augmentation of Profiles for Tissue Specific cells <doi:10.1101/633958>. This package expands on the techniques outlined in Newman AM, Liu CL, Green MR, Gentles AJ, Feng W, Xu Y, Hoang CD, Diehn M, Alizadeh, AA (2015) <doi:10.1038/nmeth.3337>'s Nature Methods paper: 'Robust enumeration of cell subsets from tissue expression profiles' to allow a user to easily add their own cell types (e.g. a tumor specific cell type) to Newman's LM22 or other signature matrix.
Author: Samuel A Danziger
Maintainer: Samuel A Danziger <sam.danziger@gmail.com>

Diff between ADAPTS versions 0.9.20 dated 2019-06-17 and 0.9.21 dated 2019-08-07

 DESCRIPTION       |    6 ++---
 MD5               |    6 ++---
 R/MakeSigMatrix.R |   61 ++++++++++++++++++++++++++++++++++--------------------
 man/rankByT.Rd    |    8 ++++---
 4 files changed, 50 insertions(+), 31 deletions(-)

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