Wed, 24 Feb 2021

Package sociome updated to version 2.0.0 with previous version 1.4.2 dated 2020-08-03

Title: Operationalizing Social Determinants of Health Data for Researchers
Description: Accesses raw data via API and calculates social determinants of health measures for user-specified locations in the US, returning them in tidyverse- and sf-compatible data frames.
Author: Nik Krieger [aut, cre], Jarrod Dalton [aut], Cindy Wang [aut], Adam Perzynski [aut], National Institutes of Health/National Institute on Aging [fnd] (The development of this software package was supported by a research grant from the National Institutes of Health/National Institute on Aging, (Principal Investigators: Jarrod E. Dalton, PhD and Adam T. Perzynski, PhD; Grant Number: 5R01AG055480-02). All of its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIH.)
Maintainer: Nik Krieger <nk@case.edu>

Diff between sociome versions 1.4.2 dated 2020-08-03 and 2.0.0 dated 2021-02-24

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Package RAthena updated to version 2.0.1 with previous version 2.0.0 dated 2021-02-22

Title: Connect to 'AWS Athena' using 'Boto3' ('DBI' Interface)
Description: Designed to be compatible with the R package 'DBI' (Database Interface) when connecting to Amazon Web Service ('AWS') Athena <https://aws.amazon.com/athena/>. To do this 'Python' 'Boto3' Software Development Kit ('SDK') <https://boto3.amazonaws.com/v1/documentation/api/latest/index.html> is used as a driver.
Author: Dyfan Jones [aut, cre]
Maintainer: Dyfan Jones <dyfan.r.jones@gmail.com>

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Package noctua updated to version 2.0.1 with previous version 2.0.0 dated 2021-02-22

Title: Connect to 'AWS Athena' using R 'AWS SDK' 'paws' ('DBI' Interface)
Description: Designed to be compatible with the 'R' package 'DBI' (Database Interface) when connecting to Amazon Web Service ('AWS') Athena <https://aws.amazon.com/athena/>. To do this the 'R' 'AWS' Software Development Kit ('SDK') 'paws' <https://github.com/paws-r/paws> is used as a driver.
Author: Dyfan Jones [aut, cre]
Maintainer: Dyfan Jones <dyfan.r.jones@gmail.com>

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Package stringfish updated to version 0.15.0 with previous version 0.14.2 dated 2020-09-05

Title: Alt String Implementation
Description: Provides an extendable, performant and multithreaded 'alt-string' implementation backed by 'C++' vectors and strings.
Author: Travers Ching [aut, cre, cph], Phillip Hazel [ctb] (Bundled PCRE2 code), Zoltan Herczeg [ctb, cph] (Bundled PCRE2 code), University of Cambridge [cph] (Bundled PCRE2 code), Tilera Corporation [cph] (Stack-less Just-In-Time compiler bundled with PCRE2), Yann Collet [ctb, cph] (Yann Collet is the author of the bundled xxHash code)
Maintainer: Travers Ching <traversc@gmail.com>

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Package rBDAT updated to version 0.9.7 with previous version 0.9.6 dated 2021-02-18

Title: Implementation of BDAT Tree Taper Fortran Functions
Description: Implementing the BDAT tree taper Fortran routines, which were developed for the German National Forest Inventory (NFI), to calculate diameters, volume, assortments, double bark thickness and biomass for different tree species based on tree characteristics and sorting information. See Kublin (2003) <doi:10.1046/j.1439-0337.2003.00183.x> for details.
Author: Christian Vonderach [aut, cre], Edgar Kublin [aut], Bernhard Bösch [aut], Gerald Kändler [aut], Dominik Cullmann [ctb]
Maintainer: Christian Vonderach <christian.vonderach@forst.bwl.de>

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Package pxweb updated to version 0.10.4 with previous version 0.9.1 dated 2019-01-07

Title: R Interface to PXWEB APIs
Description: Generic interface for the PX-Web/PC-Axis API. The PX-Web/PC-Axis API is used by organizations such as Statistics Sweden and Statistics Finland to disseminate data. The R package can interact with all PX-Web/PC-Axis APIs to fetch information about the data hierarchy, extract metadata and extract and parse statistics to R data.frame format. PX-Web is a solution to disseminate PC-Axis data files in dynamic tables on the web. Since 2013 PX-Web contains an API to disseminate PC-Axis files.
Author: Mans Magnusson [aut, cre], Markus Kainu [aut], Janne Huovari [aut], Leo Lahti [aut] (<https://orcid.org/0000-0001-5537-637X>), Jan Bruusgaard [ctb], Øyvind Langsrud [ctb], Love Hansson [ctb], Eydun Nielsen [ctb], Bo Werth [ctb], Thomas Runarsson [ctb], Torbjörn Lindquist [ctb], Palmar Thorsteinsson [ctb], Pyry Kantanen [ctb]
Maintainer: Mans Magnusson <mons.magnusson@gmail.com>

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Package mlrCPO updated to version 0.3.7-2 with previous version 0.3.7-1 dated 2021-01-11

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 LWFBrook90R updated to version 0.4.4 with previous version 0.4.3 dated 2021-02-09

Title: Simulate Evapotranspiration and Soil Moisture with the SVAT Model LWF-Brook90
Description: Provides a flexible and easy-to use interface for the soil vegetation atmosphere transport (SVAT) model LWF-BROOK90, written in Fortran. The model simulates daily transpiration, interception, soil and snow evaporation, streamflow and soil water fluxes through a soil profile covered with vegetation, as described in Hammel & Kennel (2001, ISBN:978-3-933506-16-0) and Federer et al. (2003) <doi:10.1175/1525-7541(2003)004%3C1276:SOAETS%3E2.0.CO;2>. A set of high-level functions for model set up, execution and parallelization provides easy access to plot-level SVAT simulations, as well as multi-run and large-scale applications.
Author: Paul Schmidt-Walter [aut, cre] (<https://orcid.org/0000-0003-2699-0893>), Volodymyr Trotsiuk [aut] (<https://orcid.org/0000-0002-8363-656X>), Klaus Hammel [aut], Martin Kennel [aut], Anthony Federer [aut], Robert Nuske [ctb] (<https://orcid.org/0000-0001-9773-2061>), Bavarian State Institute of Forestry (LWF) [cph, fnd], Northwest German Forest Research Institute (NW-FVA) [cph, fnd]
Maintainer: Paul Schmidt-Walter <paulsw@posteo.de>

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Package localScore updated to version 1.0.6 with previous version 1.0.4 dated 2021-02-23

Title: Package for Sequence Analysis by Local Score
Description: Functionalities for calculating the local score and calculating statistical relevance (p-value) to find a local Score in a sequence of given distribution (S. Mercier and J.-J. Daudin (2001) <https://hal.archives-ouvertes.fr/hal-00714174> ; S. Karlin and S. Altschul (1990) <https://www.pnas.org/content/87/6/2264> ; S. Mercier, D. Cellier and F. Charlot (2003) <https://hal.archives-ouvertes.fr/hal-00937529v1> ; A. Lagnoux, S. Mercier and P. Valois (2017) <doi:10.1093/bioinformatics/btw699> ).
Author: Sebastian Simon [aut], David Robelin [aut, cre], Sabine Mercier [aut], Sebastien Dejean [aut], The authors of Eigen the library for the included version of Eigen [cph]
Maintainer: David Robelin <david.robelin@inrae.fr>

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Package activity updated to version 1.3.1 with previous version 1.3 dated 2019-09-09

Title: Animal Activity Statistics
Description: Provides functions to express clock time data relative to anchor points (typically solar); fit kernel density functions to animal activity time data; plot activity distributions; quantify overall levels of activity; statistically compare activity metrics through bootstrapping; evaluate variation in linear variables with time (or other circular variables).
Author: Marcus Rowcliffe
Maintainer: Marcus Rowcliffe <marcus.rowcliffe@ioz.ac.uk>

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New package bcv with initial version 1.0.1.2
Package: bcv
Version: 1.0.1.2
Date: 2021-02-06
Title: Cross-Validation for the SVD (Bi-Cross-Validation)
Author: Patrick O. Perry
Maintainer: Seyed Morteza Najibi <mor.najibi@gmail.com>
Description: Methods for choosing the rank of an SVD approximation via cross validation. The package provides both Gabriel-style "block" holdouts and Wold-style "speckled" holdouts. It also includes an implementation of the SVDImpute algorithm. For more information about Bi-cross-validation, see Owen & Perry's 2009 AoAS article (at <arXiv:0908.2062>) and Perry's 2009 PhD thesis (at <arXiv:0909.3052>).
License: BSD_3_clause + file LICENSE
Encoding: UTF-8
NeedsCompilation: yes
RoxygenNote: 7.1.0
Packaged: 2021-02-24 10:23:33 UTC; morteza
Repository: CRAN
Date/Publication: 2021-02-24 22:40:26 UTC

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Package LTRCforests updated to version 0.5.5 with previous version 0.5.2 dated 2020-10-29

Title: Ensemble Methods for Survival Data with Time-Varying Covariates
Description: Implements the conditional inference forest and relative risk forest algorithm to modeling left-truncated right-censored data with time-invariant covariates, and (left-truncated) right-censored survival data with time-varying covariates. It also provides functions to tune the parameters and evaluate the model fit. See Yao et al. (2020) <arXiv:2006.00567>.
Author: Weichi Yao [aut, cre], Halina Frydman [aut], Denis Larocque [aut], Jeffrey S. Simonoff [aut]
Maintainer: Weichi Yao <wy635@stern.nyu.edu>

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Package renv updated to version 0.13.0 with previous version 0.12.5 dated 2021-01-09

Title: Project Environments
Description: A dependency management toolkit for R. Using 'renv', you can create and manage project-local R libraries, save the state of these libraries to a 'lockfile', and later restore your library as required. Together, these tools can help make your projects more isolated, portable, and reproducible.
Author: Kevin Ushey [aut, cre], RStudio [cph]
Maintainer: Kevin Ushey <kevin@rstudio.com>

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Package vinereg updated to version 0.7.3 with previous version 0.7.2 dated 2020-11-17

Title: D-Vine Quantile Regression
Description: Implements D-vine quantile regression models with parametric or nonparametric pair-copulas. See Kraus and Czado (2017) <doi:10.1016/j.csda.2016.12.009> and Schallhorn et al. (2017) <arXiv:1705.08310>.
Author: Thomas Nagler [aut, cre], Dani Kraus [ctb]
Maintainer: Thomas Nagler <mail@tnagler.com>

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Package survidm updated to version 1.3.1 with previous version 1.3.0 dated 2021-02-16

Title: Inference and Prediction in an Illness-Death Model
Description: Newly developed methods for the estimation of several probabilities in an illness-death model. The package can be used to obtain nonparametric and semiparametric estimates for: transition probabilities, occupation probabilities, cumulative incidence function and the sojourn time distributions. Additionally, it is possible to fit proportional hazards regression models in each transition of the Illness-Death Model. Several auxiliary functions are also provided which can be used for marginal estimation of the survival functions.
Author: Luis Meira-Machado, Marta Sestelo and Gustavo Soutinho
Maintainer: Marta Sestelo <sestelo@uvigo.es>

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Package SSDforR updated to version 1.5.21 with previous version 1.5.20 dated 2020-11-15

Title: Functions to Analyze Single System Data
Description: Functions to visually and statistically analyze single system data.
Author: Charles Auerbach [aut, cre], Wendy Zeitlin [aut]
Maintainer: Charles Auerbach <auerbach@yu.edu>

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Package medrxivr updated to version 0.0.5 with previous version 0.0.4 dated 2020-12-11

Title: Access and Search MedRxiv and BioRxiv Preprint Data
Description: An increasingly important source of health-related bibliographic content are preprints - preliminary versions of research articles that have yet to undergo peer review. The two preprint repositories most relevant to health-related sciences are medRxiv <https://www.medrxiv.org/> and bioRxiv <https://www.biorxiv.org/>, both of which are operated by the Cold Spring Harbor Laboratory. 'medrxivr' provides programmatic access to the 'Cold Spring Harbour Laboratory (CSHL)' API <https://api.biorxiv.org/>, allowing users to easily download medRxiv and bioRxiv preprint metadata (e.g. title, abstract, publication date, author list, etc) into R. 'medrxivr' also provides functions to search the downloaded preprint records using regular expressions and Boolean logic, as well as helper functions that allow users to export their search results to a .BIB file for easy import to a reference manager and to download the full-text PDFs of preprints matching their search criteria.
Author: Luke McGuinness [aut, cre] (<https://orcid.org/0000-0001-8730-9761>), Lena Schmidt [aut] (<https://orcid.org/0000-0003-0709-8226>), Tuija Sonkkila [rev], Najko Jahn [rev]
Maintainer: Luke McGuinness <luke.mcguinness@bristol.ac.uk>

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New package steps with initial version 1.2.0
Package: steps
Type: Package
Title: Spatially- and Temporally-Explicit Population Simulator
Version: 1.2.0
Date: 2021-02-15
Authors@R: c( person("Casey", "Visintin", email = "casey.visintin@unimelb.edu.au", role=c("aut", "cre")), person("Nick", "Golding", email = "nick.golding.research@gmail.com", role = "ctb"), person("Skipton", "Woolley", email = "skip.woolley@csiro.au", role = "ctb"), person("John", "Baumgartner", email = "john.baumgartner@mq.edu.au", role = "ctb") )
Maintainer: Casey Visintin <casey.visintin@unimelb.edu.au>
Description: Software to simulate population change across space and time.
Depends: R (>= 3.4.0)
License: GPL (>= 2)
Imports: Rcpp, raster, future, future.apply, rasterVis, viridisLite, memuse
LinkingTo: Rcpp
RoxygenNote: 7.1.1
Suggests: testthat, fields, knitr, rmarkdown, foreach
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
Packaged: 2021-02-17 02:28:35 UTC; casey
Author: Casey Visintin [aut, cre], Nick Golding [ctb], Skipton Woolley [ctb], John Baumgartner [ctb]
Repository: CRAN
Date/Publication: 2021-02-24 16:50:03 UTC

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Package shinyML updated to version 1.0.1 with previous version 1.0.0 dated 2020-10-03

Title: Compare Supervised Machine Learning Models Using Shiny App
Description: Implementation of a shiny app to easily compare supervised machine learning model performances. You provide the data and configure each model parameter directly on the shiny app. Different supervised learning algorithms can be tested either on Spark or H2O frameworks to suit your regression and classification tasks. Implementation of available machine learning models on R has been done by Lantz (2013, ISBN:9781782162148).
Author: Jean Bertin
Maintainer: Jean Bertin <jean.bertin@mines-paris.org>

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Package quantreg updated to version 5.85 with previous version 5.83 dated 2021-01-22

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 now included. See Koenker (2006) <doi:10.1017/CBO9780511754098> and Koenker et al (2017) <doi:10.1201/9781315120256>.
Author: Roger Koenker [cre, aut], Stephen Portnoy [ctb] (Contributions to Censored QR code), Pin Tian Ng [ctb] (Contributions to Sparse QR code), Blaise Melly [ctb] (Contributions to preprocessing code), Achim Zeileis [ctb] (Contributions to dynrq code essentially identical to his dynlm code), Philip Grosjean [ctb] (Contributions to nlrq code), Cleve Moler [ctb] (author of several linpack routines), Yousef Saad [ctb] (author of sparskit2), Victor Chernozhukov [ctb] (contributions to extreme value inference code), Ivan Fernandez-Val [ctb] (contributions to extreme value inference 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>

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Package Deriv updated to version 4.1.3 with previous version 4.1.2 dated 2020-12-10

Title: Symbolic Differentiation
Description: R-based solution for symbolic differentiation. It admits user-defined function as well as function substitution in arguments of functions to be differentiated. Some symbolic simplification is part of the work.
Author: Andrew Clausen [aut], Serguei Sokol [aut, cre] (<https://orcid.org/0000-0002-5674-3327>), Andreas Rappold [ctb]
Maintainer: Serguei Sokol <sokol@insa-toulouse.fr>

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Package provenance updated to version 3.0 with previous version 2.4 dated 2020-03-19

Title: Statistical Toolbox for Sedimentary Provenance Analysis
Description: Bundles a number of established statistical methods to facilitate the visual interpretation of large datasets in sedimentary geology. Includes functionality for adaptive kernel density estimation, principal component analysis, correspondence analysis, multidimensional scaling, generalised procrustes analysis and individual differences scaling using a variety of dissimilarity measures. Univariate provenance proxies, such as single-grain ages or (isotopic) compositions are compared with the Kolmogorov-Smirnov, Kuiper or Sircombe-Hazelton L2 distances. Categorical provenance proxies such as chemical compositions are compared with the Aitchison and Bray-Curtis distances, and point-counting data with the chi-square distance. Also included are tools to plot compositional and point-counting data on ternary diagrams and point-counting data on radial plots, to calculate the sample size required for specified levels of statistical precision, and to assess the effects of hydraulic sorting on detrital compositions. Includes an intuitive query-based user interface for users who are not proficient in R.
Author: Pieter Vermeesch [aut, cre]
Maintainer: Pieter Vermeesch <p.vermeesch@ucl.ac.uk>

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Package permutes updated to version 2.0.1 with previous version 2.0 dated 2021-02-22

Title: Permutation Tests for Time Series Data
Description: Helps you determine the analysis window to use when analyzing densely-sampled time-series data, such as EEG data, using permutation testing (Maris & Oostenveld, 2007) <doi:10.1016/j.jneumeth.2007.03.024>. These permutation tests can help identify the timepoints where significance of an effect begins and ends, and the results can be plotted in various types of heatmap for reporting. Mixed-effects models are supported using an implementation of the approach by Lee & Braun (2012) <doi:10.1111/j.1541-0420.2011.01675.x>.
Author: Cesko C. Voeten [aut, cre]
Maintainer: Cesko C. Voeten <cvoeten@gmail.com>

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Package eudract updated to version 0.9.3 with previous version 0.9.2 dated 2020-04-06

Title: Creates Safety Results Summary in XML to Upload to EudraCT
Description: The remit of the European Clinical Trials Data Base (EudraCT <https://eudract.ema.europa.eu/> ) is to provide open access to summaries of all registered clinical trial results; thus aiming to prevent non-reporting of negative results and provide open-access to results to inform future research. The amount of information required and the format of the results, however, imposes a large extra workload at the end of studies on clinical trial units. In particular, the adverse-event-reporting component requires entering: each unique combination of treatment group and safety event; for every such event above, a further 4 pieces of information (body system, number of occurrences, number of subjects, number exposed) for non-serious events, plus an extra three pieces of data for serious adverse events (numbers of causally related events, deaths, causally related deaths). This package prepares the required statistics needed by EudraCT and formats them into the precise requirements to directly upload an XML file into the web portal, with no further data entry by hand.
Author: Simon Bond [cre], Beatrice Pantaleo [aut]
Maintainer: Simon Bond <simon.bond@addenbrookes.nhs.uk>

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Package ctsem updated to version 3.4.2 with previous version 3.4.1 dated 2020-12-18

Title: Continuous Time Structural Equation Modelling
Description: Hierarchical continuous time state space modelling, for linear and nonlinear systems measured by continuous variables, with limited support for binary data. The subject specific dynamic system is modelled as a stochastic differential equation (SDE), measurement models are typically multivariate normal factor models. Linear mixed effects SDE's estimated via maximum likelihood and optimization are the default. Nonlinearities, (state dependent parameters) and random effects on all parameters are possible, using either max likelihood / max a posteriori optimization (with optional importance sampling) or Stan's Hamiltonian Monte Carlo sampling. See <https://github.com/cdriveraus/ctsem/raw/master/vignettes/hierarchicalmanual.pdf> for details. Priors may be used. For the conceptual overview of the hierarchical Bayesian linear SDE approach, see <https://www.researchgate.net/publication/324093594_Hierarchical_Bayesian_Continuous_Time_Dynamic_Modeling>. Exogenous inputs may also be included, for an overview of such possibilities see <https://www.researchgate.net/publication/328221807_Understanding_the_Time_Course_of_Interventions_with_Continuous_Time_Dynamic_Models> . Stan based functions are not available on 32 bit Windows systems at present. <https://cdriver.netlify.app/> contains some tutorial blog posts.
Author: Charles Driver [aut, cre, cph], Manuel Voelkle [aut, cph], Han Oud [aut, cph], Trustees of Columbia University [cph]
Maintainer: Charles Driver <driver@mpib-berlin.mpg.de>

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Package cmstatr updated to version 0.8.0 with previous version 0.7.1 dated 2020-12-10

Title: Statistical Methods for Composite Material Data
Description: An implementation of the statistical methods commonly used for advanced composite materials in aerospace applications. This package focuses on calculating basis values (lower tolerance bounds) for material strength properties, as well as performing the associated diagnostic tests. This package provides functions for calculating basis values assuming several different distributions, as well as providing functions for non-parametric methods of computing basis values. Functions are also provided for testing the hypothesis that there is no difference between strength and modulus data from an alternate sample and that from a "qualification" or "baseline" sample. For a discussion of these statistical methods and their use, see the Composite Materials Handbook, Volume 1 (2012, ISBN: 978-0-7680-7811-4). Additional details about this package are available in the paper by Kloppenborg (2020, <doi:10.21105/joss.02265>).
Author: Stefan Kloppenborg [aut, cre], Billy Cheng [ctb], Ally Fraser [ctb]
Maintainer: Stefan Kloppenborg <stefan@kloppenborg.ca>

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Package RPEnsemble updated to version 0.5 with previous version 0.4 dated 2017-10-07

Title: Random Projection Ensemble Classification
Description: Implements the methodology of "Cannings, T. I. and Samworth, R. J. (2017) Random-projection ensemble classification, J. Roy. Statist. Soc., Ser. B. (with discussion), 79, 959--1035". The random projection ensemble classifier is a general method for classification of high-dimensional data, based on careful combination of the results of applying an arbitrary base classifier to random projections of the feature vectors into a lower-dimensional space. The random projections are divided into non-overlapping blocks, and within each block the projection yielding the smallest estimate of the test error is selected. The random projection ensemble classifier then aggregates the results of applying the base classifier on the selected projections, with a data-driven voting threshold to determine the final assignment.
Author: Timothy I. Cannings and Richard J. Samworth
Maintainer: Timothy I. Cannings <timothy.cannings@ed.ac.uk>

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Package ratematrix updated to version 1.2.3 with previous version 1.2.2 dated 2020-02-26

Title: Bayesian Estimation of the Evolutionary Rate Matrix
Description: The Evolutionary Rate Matrix is a variance-covariance matrix which describes both the rates of trait evolution and the evolutionary correlation among multiple traits. This package has functions to estimate these parameters using Bayesian MCMC. It is possible to test if the pattern of evolutionary correlations among traits has changed between predictive regimes painted along the branches of the phylogenetic tree. Regimes can be created a priori or estimated as part of the MCMC under a joint estimation approach. The package has functions to run MCMC chains, plot results, evaluate convergence, and summarize posterior distributions.
Author: Daniel Caetano [aut, cre], Luke Harmon [aut]
Maintainer: Daniel Caetano <caetanods1@gmail.com>

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Package econetwork updated to version 0.5.0 with previous version 0.4.1 dated 2020-09-02

Title: Analyzing Ecological Networks
Description: A collection of advanced tools, methods and models specifically designed for analyzing different types of ecological networks - especially antagonistic (food webs, host-parasite), mutualistic (plant-pollinator, plant-fungus, etc) and competitive networks, as well as their variability in time and space. Statistical models are developed to describe and understand the mechanisms that determine species interactions, and to decipher the organization of these ecological networks (Ohlmann et al. (2019) <doi:10.1111/ele.13221>, Gonzalez et al. (2020) <doi:10.1101/2020.04.02.021691>, Miele et al. (2021) submitted).
Author: Stephane Dray [ctb], Catherine Matias [ctb], Vincent Miele [aut, cre], Marc Ohlmann [aut], Giovanni Poggiato [ctb], Wilfried Thuiller [ctb]
Maintainer: Vincent Miele <vincent.miele@univ-lyon1.fr>

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 econetwork-0.5.0/econetwork/man/virtualComCompetition.Rd |only
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 11 files changed, 31 insertions(+), 15 deletions(-)

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Package meta updated to version 4.17-0 with previous version 4.16-2 dated 2021-01-27

Title: General Package for Meta-Analysis
Description: User-friendly general package providing standard methods for meta-analysis and supporting Schwarzer, Carpenter, and Rücker <DOI:10.1007/978-3-319-21416-0>, "Meta-Analysis with R" (2015): - fixed effect and random effects meta-analysis; - several plots (forest, funnel, Galbraith / radial, L'Abbe, Baujat, bubble); - statistical tests and trim-and-fill method to evaluate bias in meta-analysis; - import data from 'RevMan 5'; - prediction interval, Hartung-Knapp method for random effects model; - cumulative meta-analysis and leave-one-out meta-analysis; - meta-regression; - generalised linear mixed models; - produce forest plot summarising several (subgroup) meta-analyses.
Author: Guido Schwarzer [cre, aut] (<https://orcid.org/0000-0001-6214-9087>)
Maintainer: Guido Schwarzer <sc@imbi.uni-freiburg.de>

Diff between meta versions 4.16-2 dated 2021-01-27 and 4.17-0 dated 2021-02-24

 DESCRIPTION           |   10 
 MD5                   |   70 ++--
 NAMESPACE             |    1 
 NEWS.md               |   44 ++-
 R/Pagliaro1992.R      |only
 R/crtitle.R           |   31 +-
 R/linregcore.R        |   92 ++----
 R/meta-internal.R     |   15 -
 R/meta-package.R      |    8 
 R/metabias.R          |  724 ++++++++++++++++++++++++++++++++++----------------
 R/metabin.R           |   14 
 R/metacont.R          |    7 
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 R/metainc.R           |   10 
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 R/metaprop.R          |    7 
 R/metarate.R          |    7 
 R/print.meta.R        |   40 ++
 R/setmethodbias.R     |only
 R/settings.meta.R     |    4 
 R/summary.meta.R      |    8 
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 R/update.meta.R       |   34 +-
 data/Pagliaro1992.rda |only
 man/Pagliaro1992.Rd   |only
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 man/metacont.Rd       |    5 
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 man/metainc.Rd        |    8 
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 man/metaprop.Rd       |    5 
 man/metarate.Rd       |    5 
 man/print.meta.Rd     |   18 +
 man/trimfill.Rd       |    2 
 man/update.meta.Rd    |    6 
 38 files changed, 929 insertions(+), 473 deletions(-)

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Package lime updated to version 0.5.2 with previous version 0.5.1 dated 2019-11-12

Title: Local Interpretable Model-Agnostic Explanations
Description: When building complex models, it is often difficult to explain why the model should be trusted. While global measures such as accuracy are useful, they cannot be used for explaining why a model made a specific prediction. 'lime' (a port of the 'lime' 'Python' package) is a method for explaining the outcome of black box models by fitting a local model around the point in question an perturbations of this point. The approach is described in more detail in the article by Ribeiro et al. (2016) <arXiv:1602.04938>.
Author: Thomas Lin Pedersen [cre, aut] (<https://orcid.org/0000-0002-5147-4711>), Michaël Benesty [aut]
Maintainer: Thomas Lin Pedersen <thomasp85@gmail.com>

Diff between lime versions 0.5.1 dated 2019-11-12 and 0.5.2 dated 2021-02-24

 DESCRIPTION                              |   14 
 MD5                                      |   52 -
 NAMESPACE                                |   24 
 NEWS.md                                  |    5 
 R/lime.R                                 |    2 
 R/plot_text.R                            |    8 
 R/shiny.R                                |   43 
 README.md                                |   41 
 build/vignette.rds                       |binary
 inst/doc/Understanding_lime.R            |   22 
 inst/doc/Understanding_lime.Rmd          |   16 
 inst/doc/Understanding_lime.html         | 1406 +++++--------------------------
 man/explain.Rd                           |   64 +
 man/figures/README-unnamed-chunk-2-1.png |binary
 man/figures/README-unnamed-chunk-3-1.png |binary
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 man/plot_features.Rd                     |    5 
 man/plot_image_explanation.Rd            |   13 
 man/plot_superpixels.Rd                  |   11 
 man/stop_words_sentences.Rd              |    4 
 man/test_sentences.Rd                    |    6 
 man/text_explanations.Rd                 |    7 
 man/train_sentences.Rd                   |    6 
 vignettes/Understanding_lime.Rmd         |   16 
 27 files changed, 466 insertions(+), 1340 deletions(-)

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Package marginalRisk (with last version 2021.1-7) was removed from CRAN

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

2021-01-13 2021.1-7

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Package RcppParallel updated to version 5.0.3 with previous version 5.0.2 dated 2020-06-24

Title: Parallel Programming Tools for 'Rcpp'
Description: High level functions for parallel programming with 'Rcpp'. For example, the 'parallelFor()' function can be used to convert the work of a standard serial "for" loop into a parallel one and the 'parallelReduce()' function can be used for accumulating aggregate or other values.
Author: JJ Allaire [aut], Romain Francois [aut, cph], Kevin Ushey [aut, cre], Gregory Vandenbrouck [aut], Marcus Geelnard [aut, cph] (TinyThread library, http://tinythreadpp.bitsnbites.eu/), RStudio [cph], Intel [aut, cph] (Intel TBB library, https://www.threadingbuildingblocks.org/), Microsoft [cph]
Maintainer: Kevin Ushey <kevin@rstudio.com>

Diff between RcppParallel versions 5.0.2 dated 2020-06-24 and 5.0.3 dated 2021-02-24

 DESCRIPTION             |    6 +++---
 MD5                     |   11 +++++++----
 inst/NEWS               |    4 ++++
 inst/lib                |only
 src/Makevars.in         |   11 +++++++++++
 src/tbb/build/macos.inc |    4 ++++
 6 files changed, 29 insertions(+), 7 deletions(-)

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New package optimLanduse with initial version 0.0.4
Package: optimLanduse
Title: Robust Land-Use Optimization
Version: 0.0.4
Authors@R: c( person(given = "Kai", family = "Husmann", role = c("aut", "cre"), email = "kai.husmann@uni-goettingen.de"), person(given = "Volker", family = "von Groß", role = "aut", email = "volker.vongross@uni-goettingen.de"), person(given = "Jasper", family = "Fuchs", role = "aut", email = "jasper.fuchs@uni-goettingen.de"), person(given = "Kai", family = "Bödeker", role = "aut", email = "kai.boedeker@tum.de") )
Description: Robust multi-criteria land-allocation optimization that explicitly accounts for the uncertainty of the indicators in the objective function. Solves the problem of allocating scarce land to various land-use options with regard to multiple, coequal indicators. The method aims to find the land allocation that represents the indicator composition with the best possible trade-off under uncertainty. optimLanduse includes the actual optimization procedure as described by Knoke et al. (2016) <doi:10.1038/ncomms11877> and the post-hoc calculation of the portfolio performance as presented by Gosling et al. (2020) <doi:10.1007/s10457-020-00519-0>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: lpSolveAPI (>= 5.5.2.0-17.7), tidyr (>= 1.1.2), dplyr (>= 1.0.0)
Suggests: readxl, ggplot2
URL: https://gitlab.gwdg.de/forest_economics_goettingen/optimlanduse
NeedsCompilation: no
Packaged: 2021-02-23 14:59:34 UTC; kai
Author: Kai Husmann [aut, cre], Volker von Groß [aut], Jasper Fuchs [aut], Kai Bödeker [aut]
Maintainer: Kai Husmann <kai.husmann@uni-goettingen.de>
Repository: CRAN
Date/Publication: 2021-02-24 10:30:02 UTC

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New package newsmd with initial version 0.3.1
Package: newsmd
Title: Creation of NEWS.md File
Version: 0.3.1
Date: 2021-02-23
Authors@R: person(given = "Jakob", family = "Gepp", role = c("cre", "aut"), email = "jakob.gepp@yahoo.de")
Description: Adding updates (version or bullet points) to the NEWS.md file.
License: MIT + file LICENSE
URL: https://github.com/Dschaykib/newsmd
BugReports: https://github.com/Dschaykib/newsmd/issues
Depends: R (>= 3.3)
Imports: R6
Suggests: desc, knitr, lintr, rmarkdown, testthat
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-GB
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-02-23 16:20:56 UTC; jakobgepp
Author: Jakob Gepp [cre, aut]
Maintainer: Jakob Gepp <jakob.gepp@yahoo.de>
Repository: CRAN
Date/Publication: 2021-02-24 10:50:02 UTC

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New package mscp with initial version 1.0
Package: mscp
Type: Package
Title: Multiscale Change Point Detection via Gradual Bandwidth Adjustment in Moving Sum Processes
Version: 1.0
Date: 2021-02-19
Authors@R: c(person("Tijana", "Levajkovic", role = "aut"), person("Michael", "Messer", role = c("aut", "cre"), email = "michael.messer@tuwien.ac.at"))
Maintainer: Michael Messer <michael.messer@tuwien.ac.at>
Description: Multiscale moving sum procedure for the detection of changes in expectation in univariate sequences. References - Multiscale change point detection via gradual bandwidth adjustment in moving sum processes (2021+), Tijana Levajkovic and Michael Messer.
License: GPL-3
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-02-23 11:13:14 UTC; messer
Author: Tijana Levajkovic [aut], Michael Messer [aut, cre]
Repository: CRAN
Date/Publication: 2021-02-24 10:10:02 UTC

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New package lgrExtra with initial version 0.0.5
Type: Package
Package: lgrExtra
Title: Extra Appenders for 'lgr'
Version: 0.0.5
Authors@R: person(given = "Stefan", family = "Fleck", role = c("aut", "cre"), email = "stefan.b.fleck@gmail.com", comment = c(ORCID = "0000-0003-3344-9851"))
Maintainer: Stefan Fleck <stefan.b.fleck@gmail.com>
Description: Additional appenders for the logging package 'lgr' that support logging to databases, email and push notifications.
License: MIT + file LICENSE
Imports: data.table, lgr
Suggests: covr, DBI, gmailr, jsonlite, RMariaDB, RPostgres, RPushbullet, RSQLite, rsyslog, sendmailR, testthat, knitr, rmarkdown
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1.9000
NeedsCompilation: no
Packaged: 2021-02-23 10:42:24 UTC; hoelk
Author: Stefan Fleck [aut, cre] (<https://orcid.org/0000-0003-3344-9851>)
Repository: CRAN
Date/Publication: 2021-02-24 10:10:05 UTC

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Package EWS updated to version 0.2.0 with previous version 0.1.0 dated 2020-04-07

Title: Early Warning System
Description: The purpose of Early Warning Systems (EWS) is to detect accurately the occurrence of a crisis, which is represented by a binary variable which takes the value of one when the event occurs, and the value of zero otherwise. EWS are a toolbox for policymakers to prevent or attenuate the impact of economic downturns. Modern EWS are based on the econometric framework of Kauppi and Saikkonen (2008) <doi:10.1162/rest.90.4.777>. Specifically, this framework includes four dichotomous models, relying on a logit approach to model the relationship between yield spreads and future recessions, controlling for recession risk factors. These models can be estimated in a univariate or a balanced panel framework as in Candelon, Dumitrescu and Hurlin (2014) <doi:10.1016/j.ijforecast.2014.03.015>. This package provides both methods for estimating these models and a dataset covering 13 OECD countries over a period of 45 years. In addition, this package also provides methods for the analysis of the propagation mechanisms of an exogenous shock, as well as robust confidence intervals for these response functions using a block-bootstrap method as in Lajaunie (2021). This package constitutes a useful toolbox (data and functions) for scholars as well as policymakers.
Author: Jean-Baptiste Hasse [aut], Quentin Lajaunie [aut, cre]
Maintainer: Quentin Lajaunie <quentin_lajaunie@hotmail.fr>

Diff between EWS versions 0.1.0 dated 2020-04-07 and 0.2.0 dated 2021-02-24

 EWS-0.1.0/EWS/R/Functions_EWS.R             |only
 EWS-0.2.0/EWS/DESCRIPTION                   |   16 ++++-------
 EWS-0.2.0/EWS/MD5                           |   29 ++++++++++++++-------
 EWS-0.2.0/EWS/NAMESPACE                     |    4 +-
 EWS-0.2.0/EWS/R/EWS_functions.R             |only
 EWS-0.2.0/EWS/data/data_USA.rda             |binary
 EWS-0.2.0/EWS/data/data_panel.rda           |binary
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 EWS-0.2.0/EWS/man/data_USA.Rd               |   16 ++++++++---
 EWS-0.2.0/EWS/man/data_panel.Rd             |    7 +++--
 21 files changed, 58 insertions(+), 61 deletions(-)

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New package tinyspotifyr with initial version 0.2.2
Package: tinyspotifyr
Title: Tinyverse R Wrapper for the 'Spotify' Web API
Version: 0.2.2
Authors@R: c(person("Troy", "Hernandez", email = "troy.hernandez.phd@gmail.com", role = c("aut", "cre")), person("Charlie", "Thompson", email = "chuck@rcharlie.com", role = c("aut")), person("Josiah", "Parry", email = "josiah.parry@yahoo.com", role = "aut"), person("Donal", "Phipps", email = "donal.phipps@gmail.com", role = "aut"), person("Tom", "Wolff", email = "tom.wolff@duke.edu", role = "aut"))
Author: Troy Hernandez [aut, cre], Charlie Thompson [aut], Josiah Parry [aut], Donal Phipps [aut], Tom Wolff [aut]
Maintainer: Troy Hernandez <troy.hernandez.phd@gmail.com>
Description: An R wrapper for the 'Spotify' Web API <https://developer.spotify.com/web-api/>.
Depends: R (>= 3.2)
Imports: httr, jsonlite
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
URL: https://github.com/TroyHernandez/tinyspotifyr
BugReports: https://github.com/TroyHernandez/tinyspotifyr/issues
NeedsCompilation: no
Packaged: 2021-02-21 13:52:51 UTC; troy
Repository: CRAN
Date/Publication: 2021-02-24 09:30:02 UTC

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New package stlTDNN with initial version 0.1.0
Package: stlTDNN
Type: Package
Title: STL Decomposition and TDNN Hybrid Time Series Forecasting
Version: 0.1.0
Authors@R: c(person(given = "Girish Kumar", family = "Jha", role = c("aut", "cre"), email = "girish.stat@gmail.com"), person(given = "Ronit", family = "Jaiswal", role = c("aut", "ctb")), person(given = "Kapil", family = "Choudhary", role = "ctb"), person(given = "Rajeev Ranjan", family = "Kumar", role = "ctb"))
Maintainer: Girish Kumar Jha <girish.stat@gmail.com>
Description: Implementation of hybrid STL decomposition based time delay neural network model for univariate time series forecasting. For method details see Jha G K, Sinha, K (2014). <doi:10.1007/s00521-012-1264-z>, Xiong T, Li C, Bao Y (2018). <doi:10.1016/j.neucom.2017.11.053>.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: forecast, nnfor
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2021-02-22 14:54:50 UTC; Rajeev-PC
Author: Girish Kumar Jha [aut, cre], Ronit Jaiswal [aut, ctb], Kapil Choudhary [ctb], Rajeev Ranjan Kumar [ctb]
Repository: CRAN
Date/Publication: 2021-02-24 09:20:03 UTC

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New package RxODE with initial version 1.0.4
Package: RxODE
Version: 1.0.4
Title: Facilities for Simulating from ODE-Based Models
Authors@R: c( person("Matthew L.","Fidler", role = c("aut"), email = "matthew.fidler@gmail.com", comment=c(ORCID="0000-0001-8538-6691")), person("Melissa", "Hallow", role = "aut", email = "hallowkm@uga.edu"), person("Wenping", "Wang", role = c("aut", "cre"), email = "wwang8198@gmail.com"), person("Zufar", "Mulyukov", role="ctb", email="zufar.mulyukov@novartis.com"), person("Alan", "Hindmarsh",role="ctb"), person("Awad H.", "Al-Mohy",role="ctb"), person("Matt", "Dowle", role="ctb", email="mattjdowle@gmail.com"), person("Cleve", "Moler", role="ctb"), person("David", "Cooley", role="ctb"), person("Daniel C.", "Dillon", role="ctb"), person("Drew", "Schmidt", role="ctb"), person("Arun", "Srinivasan", role="ctb", email="arunkumar.sriniv@gmail.com"), person("Ernst", "Hairer", role="ctb"), person("Gerhard", "Wanner", role="ctb"), person("Goro", "Fuji", role="ctb", email="gfuji@cpan.org"), person("Hadley", "Wickham", role="ctb"), person("Jack", "Dongarra", role="ctb"), person("Linda", "Petzold", role="ctb"), person("Martin", "Maechler", role="ctb"), person("Matteo", "Fasiolo", email = "matteo.fasiolo@gmail.com", role = "ctb"), person("Morwenn","", role="ctb"), person("Nicholas J.", "Higham",role="ctb"), person("Roger B.", "Sidje", role="ctb"), person("Simon", "Frost", role="ctb"), person("Kevin", "Ushey", role="ctb"), person("Yu", "Feng", role="ctb") )
Maintainer: Wenping Wang <wwang8198@gmail.com>
Depends: R (>= 3.6.0)
Suggests: spelling, Matrix, DT, covr, crayon, curl, data.table (>= 1.12.4), devtools, digest, dplyr (>= 0.8.0), ggrepel, gridExtra, htmltools, knitr, learnr, microbenchmark, nlme, remotes, rlang, rmarkdown, scales, shiny, stringi, symengine, testthat, tidyr, usethis, vdiffr, xgxr, pillar, tibble, rsconnect, patchwork
Imports: PreciseSums (>= 0.3), Rcpp (>= 0.12.3), assertthat, backports, checkmate, cli (>= 2.0.0), dparser (>= 0.1.8), ggplot2, inline, lotri (>= 0.2.2), magrittr, memoise, methods, rex, qs, sys, units (>= 0.6-0), tools, utils
Description: Facilities for running simulations from ordinary differential equation ('ODE') models, such as pharmacometrics and other compartmental models. A compilation manager translates the ODE model into C, compiles it, and dynamically loads the object code into R for improved computational efficiency. An event table object facilitates the specification of complex dosing regimens (optional) and sampling schedules. NB: The use of this package requires both C and Fortran compilers, for details on their use with R please see Section 6.3, Appendix A, and Appendix D in the "R Administration and Installation" manual. Also the code is mostly released under GPL. The 'VODE' and 'LSODA' are in the public domain. The information is available in the inst/COPYRIGHTS.
BugReports: https://github.com/nlmixrdevelopment/RxODE/issues
NeedsCompilation: yes
VignetteBuilder: knitr
License: GPL (>= 3)
URL: https://nlmixrdevelopment.github.io/RxODE/
RoxygenNote: 7.1.1
Biarch: true
LinkingTo: dparser (>= 0.1.8), PreciseSums (>= 0.3), RcppEigen (>= 0.3.3.3.0), RcppArmadillo (>= 0.9.300.2.0), sitmo, StanHeaders (>= 2.18.0), BH, checkmate, qs
Encoding: UTF-8
LazyData: true
Language: en-US
Packaged: 2021-02-18 13:44:52 UTC; annie
Author: Matthew L. Fidler [aut] (<https://orcid.org/0000-0001-8538-6691>), Melissa Hallow [aut], Wenping Wang [aut, cre], Zufar Mulyukov [ctb], Alan Hindmarsh [ctb], Awad H. Al-Mohy [ctb], Matt Dowle [ctb], Cleve Moler [ctb], David Cooley [ctb], Daniel C. Dillon [ctb], Drew Schmidt [ctb], Arun Srinivasan [ctb], Ernst Hairer [ctb], Gerhard Wanner [ctb], Goro Fuji [ctb], Hadley Wickham [ctb], Jack Dongarra [ctb], Linda Petzold [ctb], Martin Maechler [ctb], Matteo Fasiolo [ctb], Morwenn [ctb], Nicholas J. Higham [ctb], Roger B. Sidje [ctb], Simon Frost [ctb], Kevin Ushey [ctb], Yu Feng [ctb]
Repository: CRAN
Date/Publication: 2021-02-24 09:40:10 UTC

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New package rtsVis with initial version 0.0.1
Package: rtsVis
Type: Package
Title: Raster Time Series Visualization
Version: 0.0.1
Depends: R (>= 3.5.0)
Date: 2021-02-23
Authors@R: c(person("Johannes", "Mast", role = c("aut", "cre"), email = "johannes.mast@stud-mail.uni-wuerzburg.de", comment = c(ORCID = "0000-0001-6595-5834")), person("Jakob", "Schwalb-Willmann", email = "movevis@schwalb-willmann.de", role = c("aut"), comment = c(ORCID = "0000-0003-2665-1509")))
Description: A lightweight 'R' package to visualize large raster time series, building on a fast temporal interpolation core.
License: GPL-3
Encoding: UTF-8
Imports: ggplot2, RStoolbox, moveVis, raster, stats, dplyr, pbapply, sp, sf, tidyr, assertthat
BugReports: https://github.com/JohMast/rtsVis/issues
RoxygenNote: 7.1.1
Suggests: spelling
LazyData: true
Language: en-US
NeedsCompilation: no
Packaged: 2021-02-23 09:37:50 UTC; b
Author: Johannes Mast [aut, cre] (<https://orcid.org/0000-0001-6595-5834>), Jakob Schwalb-Willmann [aut] (<https://orcid.org/0000-0003-2665-1509>)
Maintainer: Johannes Mast <johannes.mast@stud-mail.uni-wuerzburg.de>
Repository: CRAN
Date/Publication: 2021-02-24 10:00:02 UTC

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New package rlog with initial version 0.1.0
Package: rlog
Title: A Simple, Opinionated Logging Utility
Version: 0.1.0
Authors@R: person(given = "Mark", family = "Sellors", role = c("aut", "cre"), email = "rstats@5vcc.com")
Description: A very lightweight package that writes out log messages in an opinionated way. Simpler and lighter than other logging packages, 'rlog' provides a compact feature set that focuses on getting the job done in a Unix-like way.
URL: https://github.com/sellorm/rlog
BugReports: https://github.com/sellorm/rlog/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: testthat (>= 3.0.0)
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2021-02-22 15:04:40 UTC; sellorm
Author: Mark Sellors [aut, cre]
Maintainer: Mark Sellors <rstats@5vcc.com>
Repository: CRAN
Date/Publication: 2021-02-24 09:20:05 UTC

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Package ProAE updated to version 0.1.1 with previous version 0.1.0 dated 2021-02-22

Title: PRO-CTCAE Data Management, Analysis, and Graphical Tools
Description: A collection of tools to facilitate standardized analysis and graphical procedures when using the National Cancer Institute’s Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE).
Author: Blake Langlais [aut, cre], Amylou Dueck [aut]
Maintainer: Blake Langlais <langlais.blake@mayo.edu>

Diff between ProAE versions 0.1.0 dated 2021-02-22 and 0.1.1 dated 2021-02-24

 DESCRIPTION           |    6 +++---
 MD5                   |   18 +++++++++---------
 R/ProAE.R             |   12 ++++++------
 R/toxFigures.R        |    8 ++++----
 R/toxScores.R         |    2 +-
 man/PROCTCAE_table.Rd |    4 ++--
 man/tox_acute.Rd      |    2 +-
 man/tox_chronic.Rd    |    2 +-
 man/tox_cumulative.Rd |    2 +-
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New package NADA2 with initial version 1.0.0
Package: NADA2
Type: Package
Title: Data Analysis for Censored Environmental Data
Version: 1.0.0
Date: 2021-02-21
Authors@R: c(person("Paul", "Julian",role=c("aut","cre"), email="pauljulianphd@gmail.com"), person("Dennis", "Helsel",role=c("aut","cph"), email="dhelsel@practicalstats.com"))
Maintainer: Paul Julian <pauljulianphd@gmail.com>
URL: https://github.com/SwampThingPaul/NADA2
BugReports: https://github.com/SwampThingPaul/NADA2/issues
Description: Contains methods described by Dennis Helsel in his book "Statistics for Censored Environmental Data using `Minitab` and R" (2011) and courses and videos at <https://practicalstats.com>. This package adds new functions to the `NADA` Package.
License: MIT + file LICENSE
Depends: R (>= 3.6)
Imports: grDevices, graphics, stats, utils, EnvStats, fitdistrplus, Kendall, multcomp, NADA, perm, survminer, mgcv, cenGAM, vegan, coin, survival
Suggests: knitr, rmarkdown
Encoding: UTF-8
LazyLoad: yes
LazyData: yes
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-02-22 18:42:04 UTC; Julian_P
Author: Paul Julian [aut, cre], Dennis Helsel [aut, cph]
Repository: CRAN
Date/Publication: 2021-02-24 09:50:05 UTC

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Package Hmsc updated to version 3.0-11 with previous version 3.0-9 dated 2020-10-29

Title: Hierarchical Model of Species Communities
Description: Hierarchical Modelling of Species Communities (HMSC) is a model-based approach for analyzing community ecological data. This package implements it in the Bayesian framework with Gibbs Markov chain Monte Carlo (MCMC) sampling (Tikhonov et al. (2020) <doi:10.1111/2041-210X.13345>).
Author: Gleb Tikhonov [aut], Otso Ovaskainen [aut, cre] (<https://orcid.org/0000-0001-9750-4421>), Jari Oksanen [aut], Melinda de Jonge [aut], Oystein Opedal [aut], Tad Dallas [aut]
Maintainer: Otso Ovaskainen <otso.ovaskainen@helsinki.fi>

Diff between Hmsc versions 3.0-9 dated 2020-10-29 and 3.0-11 dated 2021-02-24

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New package fspe with initial version 0.1.0
Package: fspe
Type: Package
Title: Estimating the Number of Factors in EFA with Out-of-Sample Prediction Errors
Version: 0.1.0
Authors@R: c(person(given = "Jonas", family = "Haslbeck", role = c("aut", "cre"), email = "jonashaslbeck@gmail.com"), person(given = "Riet", family = "van Bork", email = "rietvanbork@hotmail.com", role = "ctb"))
BugReports: https://github.com/jmbh/fspe/issues
Depends: R (>= 3.5.0)
Description: Estimating the number of factors in Exploratory Factor Analysis (EFA) with out-of-sample prediction errors using a cross-validation scheme. Haslbeck & van Bork (Preprint) <https://psyarxiv.com/qktsd>.
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: psych, corpcor, GPArotation
NeedsCompilation: no
Packaged: 2021-02-23 10:02:47 UTC; jonas
Author: Jonas Haslbeck [aut, cre], Riet van Bork [ctb]
Maintainer: Jonas Haslbeck <jonashaslbeck@gmail.com>
Repository: CRAN
Date/Publication: 2021-02-24 10:00:05 UTC

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New package flightplanning with initial version 0.8.4
Package: flightplanning
Type: Package
Title: UAV Flight Planning
Version: 0.8.4
Authors@R: c( person("Caio", "Hamamura", email = "caiohamamura@gmail.com", role = c("aut", "cre")), person("Danilo Roberti Alves de", "Almeida", email = "daniloflorestas@gmail.com", role = c("aut")), person("Daniel de Almeida", "Papa", email = "daniel.papa@embrapa.br", role = c("aut")), person("Hudson Franklin Pessoa", "Veras", email = "hudson@engeverde.com", role = c("aut")), person("Evandro Orfanó", "Figueiredo", email = "evandro.figueiredo@embrapa.br", role = c("aut")))
Description: Utility functions for creating flight plans for unmanned aerial vehicles (UAV), specially for the Litchi Hub platform. It calculates the flight and camera settings based on the camera specifications, exporting the flight plan CSV format ready to import into Litchi Hub.
Imports: graphics, grDevices, methods, rgdal, rgeos, sp
Depends: R (>= 3.0)
Suggests: testthat
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
URL: https://github.com/caiohamamura/flightplanning-R
BugReports: https://github.com/caiohamamura/flightplanning-R/issues
Author: Caio Hamamura [aut, cre], Danilo Roberti Alves de Almeida [aut], Daniel de Almeida Papa [aut], Hudson Franklin Pessoa Veras [aut], Evandro Orfanó Figueiredo [aut]
Maintainer: Caio Hamamura <caiohamamura@gmail.com>
Repository: CRAN
Repository/R-Forge/Project: flightplanning
Repository/R-Forge/Revision: 17
Repository/R-Forge/DateTimeStamp: 2021-02-23 14:15:25
Date/Publication: 2021-02-24 09:40:02 UTC
NeedsCompilation: no
Packaged: 2021-02-23 14:27:09 UTC; rforge

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New package fabisearch with initial version 0.0.2.4
Package: fabisearch
Title: Change Point Detection in High-Dimensional Time Series Networks
Version: 0.0.2.4
Authors@R: c(person("Martin", "Ondrus", email = "mondrus@ualberta.ca", role = c("aut", "cre")), person("Ivor", "Cribben", email = "cribben@ualberta.ca", role = "aut"))
Description: Implementation of the Factorized Binary Search (FaBiSearch) methodology for the estimation of the number and location of multiple change points in the network (or clustering) structure of multivariate high-dimensional time series. The method is motivated by the detection of change points in functional connectivity networks for functional magnetic resonance imaging (fMRI) data. FaBiSearch uses non-negative matrix factorization (NMF), an unsupervised dimension reduction technique, and a new binary search algorithm to identify multiple change points. It also requires minimal assumptions. The main routines of the package are detect.cps(), for multiple change point detection, est.net(), for estimating a network between stationary multivariate time series, net.3dplot(), for plotting the estimated functional connectivity networks, and opt.rank(), for finding the optimal rank in NMF for a given data set. The functions have been extensively tested on simulated multivariate high-dimensional time series data and fMRI data. For details on the FaBiSearch methodology, please see Ondrus et al. (2021).
URL: https://github.com/mondrus96/FaBiSearch
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: testthat (>= 3.0.0)
Config/testthat/edition: 3
Imports: rgl, reshape2
Depends: R (>= 3.10), NMF
Packaged: 2021-02-22 01:43:01 UTC; Martin
Author: Martin Ondrus [aut, cre], Ivor Cribben [aut]
Maintainer: Martin Ondrus <mondrus@ualberta.ca>
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2021-02-24 09:40:05 UTC

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Package cotram updated to version 0.2-1 with previous version 0.2-0 dated 2020-03-30

Title: Count Transformation Models
Description: Count transformation models featuring parameters interpretable as discrete hazard ratios, odds ratios, reverse-time discrete hazard ratios, or transformed expectations. An appropriate data transformation for a count outcome and regression coefficients are simultaneously estimated by maximising the exact discrete log-likelihood using the computational framework provided in package 'mlt', technical details are given in Siegfried & Hothorn (2020) <DOI:10.1111/2041-210X.13383>.
Author: Sandra Siegfried [aut] (<https://orcid.org/0000-0002-7312-1001>), Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>)
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

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Package mlt updated to version 1.2-3 with previous version 1.2-2 dated 2021-02-12

Title: Most Likely Transformations
Description: Likelihood-based estimation of conditional transformation models via the most likely transformation approach described in Hothorn et al. (2018) <DOI:10.1111/sjos.12291>.
Author: Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>)
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

Diff between mlt versions 1.2-2 dated 2021-02-12 and 1.2-3 dated 2021-02-24

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Package ISOcodes updated to version 2021.02.24 with previous version 2020.12.04 dated 2020-12-04

Title: Selected ISO Codes
Description: ISO language, territory, currency, script and character codes. Provides ISO 639 language codes, ISO 3166 territory codes, ISO 4217 currency codes, ISO 15924 script codes, and the ISO 8859 character codes as well as the UN M.49 area codes.
Author: Christian Buchta [aut], Kurt Hornik [aut, cre] (<https://orcid.org/0000-0003-4198-9911>)
Maintainer: Kurt Hornik <Kurt.Hornik@R-project.org>

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Package polAr (with last version 0.2.0.1) was removed from CRAN

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

2021-02-22 0.2.0.1
2020-09-14 0.2.0
2020-05-16 0.1.3

Permanent link
Package spatsoc updated to version 0.1.16 with previous version 0.1.15 dated 2020-10-21

Title: Group Animal Relocation Data by Spatial and Temporal Relationship
Description: Detects spatial and temporal groups in GPS relocations (Robitaille et al. (2020) <doi:10.1111/2041-210X.13215>). It can be used to convert GPS relocations to gambit-of-the-group format to build proximity-based social networks In addition, the randomizations function provides data-stream randomization methods suitable for GPS data.
Author: Alec L. Robitaille [aut, cre] (<https://orcid.org/0000-0002-4706-1762>), Quinn Webber [aut] (<https://orcid.org/0000-0002-0434-9360>), Eric Vander Wal [aut] (<https://orcid.org/0000-0002-8534-4317>)
Maintainer: Alec L. Robitaille <robit.alec@gmail.com>

Diff between spatsoc versions 0.1.15 dated 2020-10-21 and 0.1.16 dated 2021-02-24

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Package rdrobust updated to version 1.0.1 with previous version 0.99.9 dated 2020-08-26

Title: Robust Data-Driven Statistical Inference in Regression-Discontinuity Designs
Description: Regression-discontinuity (RD) designs are quasi-experimental research designs popular in social, behavioral and natural sciences. The RD design is usually employed to study the (local) causal effect of a treatment, intervention or policy. This package provides tools for data-driven graphical and analytical statistical inference in RD designs: rdrobust() to construct local-polynomial point estimators and robust confidence intervals for average treatment effects at the cutoff in Sharp, Fuzzy and Kink RD settings, rdbwselect() to perform bandwidth selection for the different procedures implemented, and rdplot() to conduct exploratory data analysis (RD plots).
Author: Sebastian Calonico <sebastian.calonico@columbia.edu>, Matias D. Cattaneo <cattaneo@princeton.edu>, Max H. Farrell <max.farrell@chicagobooth.edu>, Rocio Titiunik <titiunik@princeton.edu>
Maintainer: Sebastian Calonico <sebastian.calonico@columbia.edu>

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Package RcppSimdJson updated to version 0.1.5 with previous version 0.1.4 dated 2021-02-12

Title: 'Rcpp' Bindings for the 'simdjson' Header-Only Library for 'JSON' Parsing
Description: The 'JSON' format is ubiquitous for data interchange, and the 'simdjson' library written by Daniel Lemire (and many contributors) provides a high-performance parser for these files which by relying on parallel 'SIMD' instruction manages to parse these files as faster than disk speed. See the <arXiv:1902.08318> paper for more details about 'simdjson'. This package parses 'JSON' from string, file, or remote URLs under a variety of settings.
Author: Dirk Eddelbuettel, Brendan Knapp
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package dfadjust updated to version 1.0.2 with previous version 1.0.1 dated 2019-12-16

Title: Degrees of Freedom Adjustment for Robust Standard Errors
Description: Computes small-sample degrees of freedom adjustment for heteroskedasticity robust standard errors, and for clustered standard errors in linear regression. See Imbens and Kolesár (2016) <doi:10.1162/REST_a_00552> for a discussion of these adjustments.
Author: Michal Kolesár [aut, cre] (<https://orcid.org/0000-0002-2482-7796>)
Maintainer: Michal Kolesár <kolesarmi@googlemail.com>

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Package ARTool updated to version 0.11.0 with previous version 0.10.8 dated 2020-10-31

Title: Aligned Rank Transform
Description: The Aligned Rank Transform for nonparametric factorial ANOVAs as described by J. O. Wobbrock, L. Findlater, D. Gergle, & J. J. Higgins, "The Aligned Rank Transform for nonparametric factorial analyses using only ANOVA procedures", CHI 2011 <DOI:10.1145/1978942.1978963>.
Author: Matthew Kay [aut, cre], Lisa A. Elkin [aut], James J. Higgins [aut], Jacob O. Wobbrock [aut]
Maintainer: Matthew Kay <mjskay@northwestern.edu>

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Package argo updated to version 3.0.1 with previous version 2.0.2 dated 2020-04-25

Title: Accurate Estimation of Influenza Epidemics using Google Search Data
Description: Augmented Regression with General Online data (ARGO) for accurate estimation of influenza epidemics in United States on national level, regional level and state level. It replicates the method introduced in paper Yang, S., Santillana, M. and Kou, S.C. (2015) <doi:10.1073/pnas.1515373112>; Ning, S., Yang, S. and Kou, S.C. (2019) <doi:10.1038/s41598-019-41559-6>; Yang, S., Ning, S. and Kou, S.C. (2021) <doi:10.1038/s41598-021-83084-5>.
Author: Shaoyang Ning, Shihao Yang, S. C. Kou
Maintainer: Shihao Yang <shihao.yang@isye.gatech.edu>

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Package UniDOE (with last version 1.0.2) was removed from CRAN

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

2018-04-18 1.0.2
2017-12-08 1.0.1
2017-11-29 1.0

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Package blaster (with last version 1.0) was removed from CRAN

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2021-02-10 1.0

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Package rmetasim (with last version 3.1.14) was removed from CRAN

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

2020-02-07 3.1.14
2020-01-29 3.1.13
2018-02-15 3.1.7
2018-01-04 3.1.6
2017-11-07 3.1.5
2017-09-19 3.1.3
2017-09-16 3.1.2
2016-04-09 3.0.5
2016-04-06 3.0.4
2016-03-29 3.0.2
2016-02-26 2.0.4.1
2014-06-01 2.0.4
2014-05-27 2.0.3

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Package RSNPset (with last version 0.5.3) was removed from CRAN

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2017-12-14 0.5.3
2017-02-21 0.5.2
2015-11-20 0.5
2015-02-11 0.4
2014-12-16 0.3

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Package sppmix (with last version 1.0.2.1) was removed from CRAN

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

2020-10-14 1.0.2.1
2017-11-17 1.0.2
2017-03-31 1.0.1
2017-02-23 1.0.0.0

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Package divDyn (with last version 0.8.0) was removed from CRAN

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2019-06-12 0.8.0
2019-02-19 0.7.1
2019-01-08 0.7.0
2018-10-08 0.6.1

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Package PivotalR (with last version 0.1.18.4) was removed from CRAN

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2020-11-16 0.1.18.4
2019-01-05 0.1.18.3.1
2017-02-13 0.1.18.3
2016-10-22 0.1.18.2
2015-01-03 0.1.17.45

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Package ProcData (with last version 0.2.5) was removed from CRAN

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2020-05-12 0.2.5

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Package sharpeRratio updated to version 1.4.2 with previous version 1.4.1 dated 2020-05-15

Title: Moment-Free Estimation of Sharpe Ratios
Description: An efficient moment-free estimator of the Sharpe ratio, or signal-to-noise ratio, for heavy-tailed data (see <arXiv:1505.01333>).
Author: Damien Challet
Maintainer: Damien Challet <damien.challet@gmail.com>

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Package myTAI updated to version 0.9.3 with previous version 0.9.2 dated 2020-01-10

Title: Evolutionary Transcriptomics
Description: Investigate the evolution of biological processes by capturing evolutionary signatures in transcriptomes (Drost et al. (2017) <doi:10.1093/bioinformatics/btx835>). The aim of this tool is to provide a transcriptome analysis environment to quantify the average evolutionary age of genes contributing to a transcriptome of interest (Drost et al. (2016) <doi:10.1101/051565>).
Author: Hajk-Georg Drost [aut, cre] (<https://orcid.org/0000-0002-1567-306X>)
Maintainer: Hajk-Georg Drost <hajk-georg.drost@tuebingen.mpg.de>

Diff between myTAI versions 0.9.2 dated 2020-01-10 and 0.9.3 dated 2021-02-24

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Package gbm.auto updated to version 1.4.1 with previous version 1.4.0 dated 2021-02-15

Title: Automated Boosted Regression Tree Modelling and Mapping Suite
Description: Automates delta log-normal boosted regression tree abundance prediction. Loops through parameters provided (LR (learning rate), TC (tree complexity), BF (bag fraction)), chooses best, simplifies, & generates line, dot & bar plots, & outputs these & predictions & a report, makes predicted abundance maps, and Unrepresentativeness surfaces. Package core built around 'gbm' (gradient boosting machine) functions in 'dismo' (Hijmans, Phillips, Leathwick & Jane Elith, 2020 & ongoing), itself built around 'gbm' (Greenwell, Boehmke, Cunningham & Metcalfe, 2020 & ongoing, originally by Ridgeway). Indebted to Elith/Leathwick/Hastie 2008 'Working Guide' <doi:10.1111/j.1365-2656.2008.01390.x>; workflow follows Appendix S3. See <http://www.simondedman.com/> for published guides and papers using this package.
Author: Simon Dedman [aut, cre], Hans Gerritsen [aut]
Maintainer: Simon Dedman <simondedman@gmail.com>

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Package diathor updated to version 0.0.4 with previous version 0.0.1 dated 2020-11-26

Title: Calculate Ecological Information and Diatom Based Indices
Description: Calculates ecological information and biotic indices for diatoms in a sample. It includes number/shape of chloroplasts diversity indices, size classes, ecological guilds, and multiple biotic indices. It outputs both a dataframe with all the results and plots of all the obtained data in a defined output folder. Sample data was taken from Nicolosi Gelis, Cochero & Gómez (2020, <doi:10.1016/j.ecolind.2019.105951>). The package uses the 'Diat.Barcode' database to calculate morphological and ecological information by Rimet & Couchez (2012, <doi:10.1051/kmae/2012018>), and calculates the DES index by Descy (1979, <http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=PASCAL8060205402>), the EPID index by Dell'Uomo (1996, ISBN: 3950009002), the IDAP index by Prygiel & Coste (1993, <doi:10.1007/BF00028033>), the ID-CH index by Hürlimann & Niederhauser (2007, <https://www.bafu.admin.ch/bafu/fr/home/themes/eaux/publications/publications-eaux/methodes-analyse-appreciation-cours-eau-diatomees.html>), the IDP index by Gómez & Licursi (2001, <doi:10.1023/A:1011415209445>), the ILM index by Leclercq & Maquet (1987, <http://www.vliz.be/imisdocs/publications/286641.pdf>), the IPS index by Coste (1982, <https://www.oieau.org/eaudoc/notice/ETUDE-DES-METHODES-BIOLOGIQUES-DAPPRECIATION-QUANTITATIVE-DE-LA-QUALITE-DES-EAUX>), the LOBO index by Lobo, Callegaro, & Bender (2002, ISBN:9788585869908), the SLA by Sládeček (1986, <doi:10.1002/aheh.19860140519>), the TDI index by Kelly, & Whitton (1995, <doi:10.1007/BF00003802>), and the SPEAR(herbicide) index by Wood, Mitrovic, Lim, Warne, Dunlop, & Kefford (2019, <doi:10.1016/j.ecolind.2018.12.035>).
Author: María Mercedes Nicolosi Gelis [aut] (<https://orcid.org/0000-0001-6324-7930>), María Belén Sathicq [aut] (<https://orcid.org/0000-0002-3534-8950>), Joaquín Cochero [cre] (<https://orcid.org/0000-0003-3957-6819>)
Maintainer: Joaquín Cochero <jcochero@ilpla.edu.ar>

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