Wed, 21 Oct 2020

Package spatsoc updated to version 0.1.15 with previous version 0.1.14 dated 2020-07-05

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>

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Package signnet updated to version 0.7.0 with previous version 0.6.0 dated 2020-08-13

Title: Methods to Analyse Signed Networks
Description: Methods for the analysis of signed networks. This includes several measures for structural balance as introduced by Cartwright and Harary (1956) <doi:10.1037/h0046049>, blockmodeling algorithms from Doreian (2008) <doi:10.1016/j.socnet.2008.03.005>, various centrality indices, and projections of signed two-mode networks introduced by Schoch (2020) <doi:10.1080/0022250X.2019.1711376>.
Author: David Schoch [aut, cre]
Maintainer: David Schoch <david.schoch@manchester.ac.uk>

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Package StempCens updated to version 1.1.0 with previous version 0.1.0 dated 2019-02-08

Title: Spatio-Temporal Estimation and Prediction for Censored/Missing Responses
Description: It estimates the parameters of a censored or missing data in spatio-temporal models using the SAEM algorithm (Delyon et al., 1999). This algorithm is a stochastic approximation of the widely used EM algorithm and an important tool for models in which the E-step does not have an analytic form. Besides the expressions obtained to estimate the parameters to the proposed model, we include the calculations for the observed information matrix using the method developed by Louis (1982). To examine the performance of the fitted model, case-deletion measure are provided.
Author: Larissa A. Matos [aut, cre] (<https://orcid.org/0000-0002-2635-0901>), Katherine L. Valeriano [aut] (<https://orcid.org/0000-0001-6388-4753>), Victor H. Lachos [ctb] (<https://orcid.org/0000-0002-7239-2459>)
Maintainer: Larissa A. Matos <larissa.amatos@gmail.com>

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Package SQUAREM updated to version 2020.5 with previous version 2020.4 dated 2020-08-26

Title: Squared Extrapolation Methods for Accelerating EM-Like Monotone Algorithms
Description: Algorithms for accelerating the convergence of slow, monotone sequences from smooth, contraction mapping such as the EM algorithm. It can be used to accelerate any smooth, linearly convergent acceleration scheme. A tutorial style introduction to this package is available in a vignette on the CRAN download page or, when the package is loaded in an R session, with vignette("SQUAREM"). Refer to the J Stat Software article: <doi:10.18637/jss.v092.i07>.
Author: Ravi Varadhan
Maintainer: Ravi Varadhan <ravi.varadhan@jhu.edu>

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Package SDAR updated to version 0.9-55 with previous version 0.9-5 dated 2020-10-20

Title: Stratigraphic Data Analysis
Description: A fast, consistent tool for plotting and facilitating the analysis of stratigraphic and sedimentological data. Taking advantage of the flexible plotting tools available in R, 'SDAR' uses stratigraphic and sedimentological data to produce detailed graphic logs for outcrop sections and borehole logs. These logs can include multiple features (e.g., bed thickness, lithology, samples, sedimentary structures, colors, fossil content, bioturbation index, gamma ray logs) (Johnson, 1992, <ISSN 0037-0738>).
Author: John R. Ortiz [aut, cre], Carlos Jaramillo [aut], Carlos Moreno [ctb]
Maintainer: John R. Ortiz <jrortizt@unal.edu.co>

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Package Quartet updated to version 1.2.0 with previous version 1.1.0 dated 2020-01-28

Title: Comparison of Phylogenetic Trees Using Quartet and Split Measures
Description: Calculates the number of four-taxon subtrees consistent with a pair of cladograms, calculating the symmetric quartet distance of Bandelt & Dress (1986), Reconstructing the shape of a tree from observed dissimilarity data, Advances in Applied Mathematics, 7, 309-343 <doi:10.1016/0196-8858(86)90038-2>, and using the tqDist algorithm of Sand et al. (2014), tqDist: a library for computing the quartet and triplet distances between binary or general trees, Bioinformatics, 30, 2079–2080 <doi:10.1093/bioinformatics/btu157> for pairs of binary trees.
Author: Martin R. Smith [aut, cre, cph] (<https://orcid.org/0000-0001-5660-1727>), Andreas Sand [ant], Gerth Stølting Brodal [ant], Rolf Fagerberg [ant], Thomas Mailund [ant], Christian N. S. Pedersen [ant], Jens Johansen [ant], Morten K. Holt [ant]
Maintainer: Martin R. Smith <martin.smith@durham.ac.uk>

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Package QCA updated to version 3.10 with previous version 3.9 dated 2020-09-01

Title: Qualitative Comparative Analysis
Description: An extensive set of functions to perform Qualitative Comparative Analysis: crisp sets ('csQCA'), temporal ('tQCA'), multi-value ('mvQCA') and fuzzy sets ('fsQCA'), using a GUI - graphical user interface. 'QCA' is a methodology that bridges the qualitative and quantitative divide in social science research. It uses a Boolean algorithm that results in a minimal causal combination that explains a given phenomenon.
Author: Adrian Dusa [aut, cre, cph] (<https://orcid.org/0000-0002-3525-9253>), Ciprian Paduraru [ctb] (<https://orcid.org/0000-0002-4518-374X>), jQuery Foundation [cph] (jQuery library and jQuery UI library), jQuery contributors [ctb, cph] (jQuery library; authors listed in inst/gui/www/lib/jquery-AUTHORS.txt), lp_solve [cph] (http://lpsolve.sourceforge.net), Vasil Dinkov [ctb, cph] (jquery.smartmenus.js library), Dmitry Baranovskiy [ctb, cph] (raphael.js library), Emmanuel Quentin [ctb, cph] (raphael.inline_text_editing.js library), Jimmy Breck-McKye [ctb, cph] (raphael-paragraph.js library), Alrik Thiem [aut] (from version 1.0-0 up to version 1.1-3)
Maintainer: Adrian Dusa <dusa.adrian@unibuc.ro>

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Package paradox updated to version 0.5.0 with previous version 0.4.0 dated 2020-07-21

Title: Define and Work with Parameter Spaces for Complex Algorithms
Description: Define parameter spaces, constraints and dependencies for arbitrary algorithms, to program on such spaces. Also includes statistical designs and random samplers. Objects are implemented as 'R6' classes.
Author: Michel Lang [cre, aut] (<https://orcid.org/0000-0001-9754-0393>), Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>), Jakob Richter [aut] (<https://orcid.org/0000-0003-4481-5554>), Xudong Sun [aut] (<https://orcid.org/0000-0003-3269-2307>), Martin Binder [aut], Marc Becker [ctb] (<https://orcid.org/0000-0002-8115-0400>)
Maintainer: Michel Lang <michellang@gmail.com>

Diff between paradox versions 0.4.0 dated 2020-07-21 and 0.5.0 dated 2020-10-21

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More information about paradox at CRAN
Permanent link

Package nonmemica updated to version 0.9.6 with previous version 0.9.4 dated 2020-10-02

Title: Create and Evaluate NONMEM Models in a Project Context
Description: Systematically creates and modifies NONMEM(R) control streams. Harvests NONMEM output, builds run logs, creates derivative data, generates diagnostics. NONMEM (ICON Development Solutions <http://www.iconplc.com/>) is software for nonlinear mixed effects modeling. See 'package?nonmemica'.
Author: Tim Bergsma
Maintainer: Tim Bergsma <bergsmat@gmail.com>

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Package lefko3 updated to version 3.0.0 with previous version 2.4.2 dated 2020-09-17

Title: Historical and Ahistorical Population Projection Matrix Analysis
Description: Creates matrix population models for use in population ecological analyses. Specializes on the construction of historical matrices, which are 2d matrices comprising 3 time intervals of demographic information. Estimates both raw and function-based forms of historical and standard ahistorical matrices. Methodology based on Ehrlen (2000) <doi:10.1890/0012-9658(2000)081[1675:TDOPPD]2.0.CO;2>.
Author: Richard P. Shefferson [aut, cre] (<https://orcid.org/0000-0002-5234-3131>), Johan Ehrlen [aut] (<https://orcid.org/0000-0001-8539-8967>)
Maintainer: Richard P. Shefferson <cdorm@g.ecc.u-tokyo.ac.jp>

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Package ghypernet updated to version 1.0.1 with previous version 1.0.0 dated 2020-05-20

Title: Fit and Simulate Generalised Hypergeometric Ensembles of Graphs
Description: Provides functions for model fitting and selection of generalised hypergeometric ensembles of random graphs (gHypEG). To learn how to use it, check the vignettes for a quick tutorial. Please reference its use as Casiraghi, G., Nanumyan, V. (2019) <doi:10.5281/zenodo.2555300> together with those relevant references from the one listed below. The package is based on the research developed at the Chair of Systems Design, ETH Zurich. Casiraghi, G., Nanumyan, V., Scholtes, I., Schweitzer, F. (2016) <arXiv:1607.02441>. Casiraghi, G., Nanumyan, V., Scholtes, I., Schweitzer, F. (2017) <doi:10.1007/978-3-319-67256-4_11>. Casiraghi, G., (2017) <arxiv:1702.02048> Casiraghi, G., Nanumyan, V. (2018) <arXiv:1810.06495>. Brandenberger, L., Casiraghi, G., Nanumyan, V., Schweitzer, F. (2019) <doi:10.1145/3341161.3342926> Casiraghi, G. (2019) <doi:10.1007/s41109-019-0241-1>.
Author: Giona Casiraghi [aut, cre] (<https://orcid.org/0000-0003-0233-5747>), Vahan Nanumyan [aut] (<https://orcid.org/0000-0001-9054-3217>), Laurence Brandenberger [aut], Giacomo Vaccario [ctb]
Maintainer: Giona Casiraghi <giona@ethz.ch>

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Package behaviorchange updated to version 0.2.4 with previous version 0.2.2 dated 2020-03-01

Title: Tools for Behavior Change Researchers and Professionals
Description: Contains specialised analyses and visualisation tools for behavior change science. These facilitate conducting determinant studies (for example, using confidence interval-based estimation of relevance, CIBER, or CIBERlite plots, see Crutzen, Noijen & Peters (2017) <doi:10.3389/fpubh.2017.00165>), systematically developing, reporting, and analysing interventions (for example, using Acyclic Behavior Change Diagrams), and reporting about intervention effectiveness (for example, using the Numbers Needed for Change, see Gruijters & Peters (2017) <doi:10.31234/osf.io/2bau7>), and computing the required sample size (using the Meaningful Change Definition, see Gruijters & Peters (2019) <doi:10.31234/osf.io/jc295>). This package is especially useful for researchers in the field of behavior change or health psychology and to behavior change professionals such as intervention developers and prevention workers.
Author: Gjalt-Jorn Peters [aut, cre] (<https://orcid.org/0000-0002-0336-9589>), Rik Crutzen [ctb] (<https://orcid.org/0000-0002-3731-6610>), Stefan Gruijters [ctb] (<https://orcid.org/0000-0003-0141-0071>)
Maintainer: Gjalt-Jorn Peters <gjalt-jorn@a-bc.eu>

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Package batchtools updated to version 0.9.14 with previous version 0.9.13 dated 2020-03-19

Title: Tools for Computation on Batch Systems
Description: As a successor of the packages 'BatchJobs' and 'BatchExperiments', this package provides a parallel implementation of the Map function for high performance computing systems managed by schedulers 'IBM Spectrum LSF' (<https://www.ibm.com/products/hpc-workload-management>), 'OpenLava' (<https://www.openlava.org/>), 'Univa Grid Engine'/'Oracle Grid Engine' (<https://www.univa.com/>), 'Slurm' (<https://slurm.schedmd.com/>), 'TORQUE/PBS' (<https://adaptivecomputing.com/cherry-services/torque-resource-manager/>), or 'Docker Swarm' (<https://docs.docker.com/engine/swarm/>). A multicore and socket mode allow the parallelization on a local machines, and multiple machines can be hooked up via SSH to create a makeshift cluster. Moreover, the package provides an abstraction mechanism to define large-scale computer experiments in a well-organized and reproducible way.
Author: Michel Lang [cre, aut] (<https://orcid.org/0000-0001-9754-0393>), Bernd Bischl [aut], Dirk Surmann [ctb] (<https://orcid.org/0000-0003-0873-137X>)
Maintainer: Michel Lang <michellang@gmail.com>

Diff between batchtools versions 0.9.13 dated 2020-03-19 and 0.9.14 dated 2020-10-21

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Package Arothron updated to version 2.0.1 with previous version 1.1.1 dated 2019-12-05

Title: Geometric Morphometric Methods and Virtual Anthropology Tools
Description: Tools for geometric morphometric analysis. The package includes tools of virtual anthropology to align two not articulated parts belonging to the same specimen, to build virtual cavities as endocast (Profico et al, 2018 <doi:10.1002/ajpa.23493>).
Author: Antonio Profico, Costantino Buzi, Silvia Castiglione, Marina Melchionna, Paolo Piras, Pasquale Raia, Alessio Veneziano
Maintainer: Antonio Profico <antonio.profico@york.ac.uk>

Diff between Arothron versions 1.1.1 dated 2019-12-05 and 2.0.1 dated 2020-10-21

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Package ACEt updated to version 1.8.1 with previous version 1.8.0 dated 2017-05-07

Title: Estimation of Dynamic Heritability and Comparison of Twin Models
Description: Estimate the dynamic behaviour of the variance components in the classical twin models with respect to age using B-splines and P-splines.
Author: Liang He [aut, cre]
Maintainer: Liang He <liang.he@duke.edu>

Diff between ACEt versions 1.8.0 dated 2017-05-07 and 1.8.1 dated 2020-10-21

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Package redland updated to version 1.0.17-14 with previous version 1.0.17-13 dated 2020-10-09

Title: RDF Library Bindings in R
Description: Provides methods to parse, query and serialize information stored in the Resource Description Framework (RDF). RDF is described at <https://www.w3.org/TR/rdf-primer/>. This package supports RDF by implementing an R interface to the Redland RDF C library, described at <http://librdf.org/docs/api/index.html>. In brief, RDF provides a structured graph consisting of Statements composed of Subject, Predicate, and Object Nodes.
Author: Matthew B. Jones [aut, cre], Peter Slaughter [aut], Jeroen Ooms [aut], Carl Boettiger [aut], Scott Chamberlain [aut], David Beckett [cph], University of Bristol [cph], Regents of the University of California [cph]
Maintainer: Matthew B. Jones <jones@nceas.ucsb.edu>

Diff between redland versions 1.0.17-13 dated 2020-10-09 and 1.0.17-14 dated 2020-10-21

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Package waterquality updated to version 0.2.6 with previous version 0.2.5 dated 2020-10-02

Title: Satellite Derived Water Quality Detection Algorithms
Description: The main purpose of waterquality is to quickly and easily convert satellite-based reflectance imagery into one or many well-known water quality algorithms designed for the detection of harmful algal blooms or the following pigment proxies: chlorophyll-a, blue-green algae (phycocyanin), and turbidity. Johansen et al. (2019) <doi:10.21079/11681/35053>.
Author: Richard Johansen [aut, cre] (<https://orcid.org/0000-0003-4287-9677>), Jakub Nowosad [aut] (<https://orcid.org/0000-0002-1057-3721>), Molly Reif [aut] (<https://orcid.org/0000-0003-4207-1459>), Erich Emery [aut], U.S. Army Corps of Engineers [fnd]
Maintainer: Richard Johansen <richard.a.johansen@erdc.dren.mil>

Diff between waterquality versions 0.2.5 dated 2020-10-02 and 0.2.6 dated 2020-10-21

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Package warp updated to version 0.2.0 with previous version 0.1.0 dated 2020-01-14

Title: Group Dates
Description: Tooling to group dates by a variety of periods including: yearly, monthly, by second, by week of the month, and more. The groups are defined in such a way that they also represent the distance between dates in terms of the period. This extracts valuable information that can be used in further calculations that rely on a specific temporal spacing between observations.
Author: Davis Vaughan [aut, cre], RStudio [cph]
Maintainer: Davis Vaughan <davis@rstudio.com>

Diff between warp versions 0.1.0 dated 2020-01-14 and 0.2.0 dated 2020-10-21

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Package reticulate updated to version 1.17 with previous version 1.16 dated 2020-05-27

Title: Interface to 'Python'
Description: Interface to 'Python' modules, classes, and functions. When calling into 'Python', R data types are automatically converted to their equivalent 'Python' types. When values are returned from 'Python' to R they are converted back to R types. Compatible with all versions of 'Python' >= 2.7.
Author: Kevin Ushey [aut, cre], JJ Allaire [aut], RStudio [cph, fnd], Yuan Tang [aut, cph] (<https://orcid.org/0000-0001-5243-233X>), Dirk Eddelbuettel [ctb, cph], Bryan Lewis [ctb, cph], Sigrid Keydana [ctb], Ryan Hafen [ctb, cph], Marcus Geelnard [ctb, cph] (TinyThread library, http://tinythreadpp.bitsnbites.eu/)
Maintainer: Kevin Ushey <kevin@rstudio.com>

Diff between reticulate versions 1.16 dated 2020-05-27 and 1.17 dated 2020-10-21

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Package PMCMRplus updated to version 1.6.1 with previous version 1.6.0 dated 2020-10-14

Title: Calculate Pairwise Multiple Comparisons of Mean Rank Sums Extended
Description: For one-way layout experiments the one-way ANOVA can be performed as an omnibus test. All-pairs multiple comparisons tests (Tukey-Kramer test, Scheffe test, LSD-test) and many-to-one tests (Dunnett test) for normally distributed residuals and equal within variance are available. Furthermore, all-pairs tests (Games-Howell test, Tamhane's T2 test, Dunnett T3 test, Ury-Wiggins-Hochberg test) and many-to-one (Tamhane-Dunnett Test) for normally distributed residuals and heterogeneous variances are provided. Van der Waerden's normal scores test for omnibus, all-pairs and many-to-one tests is provided for non-normally distributed residuals and homogeneous variances. The Kruskal-Wallis, BWS and Anderson-Darling omnibus test and all-pairs tests (Nemenyi test, Dunn test, Conover test, Dwass-Steele-Critchlow- Fligner test) as well as many-to-one (Nemenyi test, Dunn test, U-test) are given for the analysis of variance by ranks. Non-parametric trend tests (Jonckheere test, Cuzick test, Johnson-Mehrotra test, Spearman test) are included. In addition, a Friedman-test for one-way ANOVA with repeated measures on ranks (CRBD) and Skillings-Mack test for unbalanced CRBD is provided with consequent all-pairs tests (Nemenyi test, Siegel test, Miller test, Conover test, Exact test) and many-to-one tests (Nemenyi test, Demsar test, Exact test). A trend can be tested with Pages's test. Durbin's test for a two-way balanced incomplete block design (BIBD) is given in this package as well as Gore's test for CRBD with multiple observations per cell is given. Outlier tests, Mandel's k- and h statistic as well as functions for Type I error and Power analysis as well as generic summary, print and plot methods are provided.
Author: Thorsten Pohlert [aut, cre] (<https://orcid.org/0000-0003-3855-3025>)
Maintainer: Thorsten Pohlert <thorsten.pohlert@gmx.de>

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Package furrr updated to version 0.2.1 with previous version 0.2.0 dated 2020-10-12

Title: Apply Mapping Functions in Parallel using Futures
Description: Implementations of the family of map() functions from 'purrr' that can be resolved using any 'future'-supported backend, e.g. parallel on the local machine or distributed on a compute cluster.
Author: Davis Vaughan [aut, cre], Matt Dancho [aut], RStudio [cph]
Maintainer: Davis Vaughan <davis@rstudio.com>

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Package gausscov updated to version 0.0.8 with previous version 0.0.7 dated 2020-09-14

Title: The Gaussian Covariate Method for Variable Selection
Description: Given the standard linear model the traditional way of deciding whether to include the jth covariate is to apply the F-test to decide whether the corresponding beta coefficient is zero. The Gaussian covariate method is completely different. The question as to whether the beta coefficient is or is not zero is replaced by the question as to whether the covariate is better or worse than i.i.d. Gaussian noise. The P-value for the covariate is the probability that Gaussian noise is better. Surprisingly this can be given exactly and it is the same a the P-value for the classical model based on the F-distribution. The Gaussian covariate P-value is model free, it is the same for any data set. Using the idea it is possible to do covariate selection for a small number of covariates 25 by considering all subsets. Post selection inference causes no problems as the P-values hold whatever the data. The idea extends to stepwise regression again with exact probabilities. In the simplest version the only parameter is a specified cut-off P-value which can be interpreted as the probability of a false positive being included in the final selection. For more information see the website below and the accompanying papers: L. Davies and L. Duembgen, "Covariate Selection Based on a Model-free Approach to Linear Regression with Exact Probabilities", 2020, <arXiv:1906.01990>. L. Davies, "Lasso, Knockoff and Gaussian covariates: A comparison", 2018, <arXiv:1807.09633>.
Author: Laurie Davies [aut, cre]
Maintainer: Laurie Davies <laurie.davies@uni-due.de>

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Package tidyquant updated to version 1.0.2 with previous version 1.0.1 dated 2020-07-02

Title: Tidy Quantitative Financial Analysis
Description: Bringing business and financial analysis to the 'tidyverse'. The 'tidyquant' package provides a convenient wrapper to various 'xts', 'zoo', 'quantmod', 'TTR' and 'PerformanceAnalytics' package functions and returns the objects in the tidy 'tibble' format. The main advantage is being able to use quantitative functions with the 'tidyverse' functions including 'purrr', 'dplyr', 'tidyr', 'ggplot2', 'lubridate', etc. See the 'tidyquant' website for more information, documentation and examples.
Author: Matt Dancho [aut, cre], Davis Vaughan [aut]
Maintainer: Matt Dancho <mdancho@business-science.io>

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Package occCite updated to version 0.4.0 with previous version 0.3.0 dated 2020-10-06

Title: Querying and Managing Large Biodiversity Occurrence Datasets
Description: Facilitates the gathering of biodiversity occurrence data from disparate sources. Metadata is managed throughout the process to facilitate reporting and enhanced ability to repeat analyses.
Author: Hannah L. Owens [aut, cre] (<https://orcid.org/0000-0003-0071-1745>), Cory Merow [aut] (<https://orcid.org/0000-0003-0561-053X>), Brian Maitner [aut] (<https://orcid.org/0000-0002-2118-9880>), Jamie M. Kass [aut] (<https://orcid.org/0000-0002-9432-895X>), Vijay Barve [aut] (<https://orcid.org/0000-0002-4852-2567>), Robert P. Guralnick [aut] (<https://orcid.org/0000-0001-6682-1504>)
Maintainer: Hannah L. Owens <hannah.owens@gmail.com>

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Package netgwas updated to version 1.12 with previous version 1.11 dated 2019-10-15

Title: Network-Based Genome Wide Association Studies
Description: A multi-core R package that contains a set of tools based on copula graphical models for accomplishing the three interrelated goals in genetics and genomics in an unified way: (1) linkage map construction, (2) constructing linkage disequilibrium networks, and (3) exploring high-dimensional genotype-phenotype network and genotype- phenotype-environment interactions networks. The netgwas package can deal with biparental inbreeding and outbreeding species with any ploidy level, namely diploid (2 sets of chromosomes), triploid (3 sets of chromosomes), tetraploid (4 sets of chromosomes) and so on. We target on high-dimensional data where number of variables p is considerably larger than number of sample sizes (p >> n). The computations is memory-optimized using the sparse matrix output. The package is implemented the recent methodological developments in Behrouzi and Wit (2017) <doi:10.1111/rssc.12287> and Behrouzi and Wit (2017) <doi:10.1093/bioinformatics/bty777>. NOTICE proper functionality of 'netgwas' requires that the 'RBGL' package is installed from 'bioconductor'; for installation instruction please refer to the 'RBGL' web page given below.
Author: Pariya Behrouzi <https://orcid.org/0000-0001-6762-5433> and Ernst C. Wit
Maintainer: Pariya Behrouzi <pariya.behrouzi@gmail.com>

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Package mlr3 updated to version 0.8.0 with previous version 0.7.0 dated 2020-10-07

Title: Machine Learning in R - Next Generation
Description: Efficient, object-oriented programming on the building blocks of machine learning. Provides 'R6' objects for tasks, learners, resamplings, and measures. The package is geared towards scalability and larger datasets by supporting parallelization and out-of-memory data-backends like databases. While 'mlr3' focuses on the core computational operations, add-on packages provide additional functionality.
Author: Michel Lang [cre, aut] (<https://orcid.org/0000-0001-9754-0393>), Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>), Jakob Richter [aut] (<https://orcid.org/0000-0003-4481-5554>), Patrick Schratz [aut] (<https://orcid.org/0000-0003-0748-6624>), Giuseppe Casalicchio [ctb] (<https://orcid.org/0000-0001-5324-5966>), Stefan Coors [ctb] (<https://orcid.org/0000-0002-7465-2146>), Quay Au [ctb] (<https://orcid.org/0000-0002-5252-8902>), Martin Binder [aut], Marc Becker [ctb] (<https://orcid.org/0000-0002-8115-0400>)
Maintainer: Michel Lang <michellang@gmail.com>

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Package traitdataform updated to version 0.6.0 with previous version 0.5.7 dated 2020-04-05

Title: Formatting and Harmonizing Ecological Trait-Data
Description: Assistance for handling ecological trait data and applying the Ecological Trait-Data Standard terminology (Schneider et al. 2019 <doi:10.1111/2041-210X.13288>). There are two major use cases: (1) preparation of own trait datasets for upload into public data bases, and (2) harmonizing trait datasets from different sources by re-formatting them into a unified format. See 'traitdataform' website for full documentation.
Author: Florian D. Schneider [aut, cre] (<https://orcid.org/0000-0002-1494-5684>), Caterina Penone [ctb] (<https://orcid.org/0000-0002-8170-6659>), Andreas Ostrowski [ctb] (<https://orcid.org/0000-0002-2033-779X>), Dennis Heimann [ctb], Felix Neff [ctb], Markus J. Ankenbrand [ctb], Jessica Burnett [ctb]
Maintainer: Florian D. Schneider <florian.dirk.schneider@gmail.com>

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Package mixl updated to version 1.2.3 with previous version 1.2.2 dated 2020-07-13

Title: Simulated Maximum Likelihood Estimation of Mixed Logit Models for Large Datasets
Description: Specification and estimation of multinomial logit models. Large datasets and complex models are supported, with an intuitive syntax. Multinomial Logit Models, Mixed models, random coefficients and Hybrid Choice are all supported. For more information, see Molloy et al. (2019) <doi:10.3929/ethz-b-000334289>.
Author: Joseph Molloy [aut, cre]
Maintainer: Joseph Molloy <joseph.molloy@ivt.baug.ethz.ch>

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Package cplm updated to version 0.7-9 with previous version 0.7-8 dated 2019-03-05

Title: Compound Poisson Linear Models
Description: Likelihood-based and Bayesian methods for various compound Poisson linear models based on Zhang, Yanwei (2013) <https://link.springer.com/article/10.1007/s11222-012-9343-7>.
Author: Yanwei (Wayne) Zhang
Maintainer: Yanwei (Wayne) Zhang <actuary_zhang@hotmail.com>

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Package soilDB updated to version 2.5.8 with previous version 2.5 dated 2020-01-28

Title: Soil Database Interface
Description: A collection of functions for reading data from USDA-NCSS soil databases.
Author: Dylan Beaudette [aut], Jay Skovlin [aut], Stephen Roecker [aut], Andrew Brown [aut, cre]
Maintainer: Andrew Brown <andrew.g.brown@usda.gov>

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Package EnvStats updated to version 2.4.0 with previous version 2.3.1 dated 2018-07-15

Title: Package for Environmental Statistics, Including US EPA Guidance
Description: Graphical and statistical analyses of environmental data, with focus on analyzing chemical concentrations and physical parameters, usually in the context of mandated environmental monitoring. Major environmental statistical methods found in the literature and regulatory guidance documents, with extensive help that explains what these methods do, how to use them, and where to find them in the literature. Numerous built-in data sets from regulatory guidance documents and environmental statistics literature. Includes scripts reproducing analyses presented in the book "EnvStats: An R Package for Environmental Statistics" (Millard, 2013, Springer, ISBN 978-1-4614-8455-4, <https://www.springer.com/book/9781461484554>).
Author: Steven P. Millard [aut], Alexander Kowarik [ctb, cre] (<https://orcid.org/0000-0001-8598-4130>)
Maintainer: Alexander Kowarik <alexander.kowarik@statistik.gv.at>

Diff between EnvStats versions 2.3.1 dated 2018-07-15 and 2.4.0 dated 2020-10-21

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Package desplot updated to version 1.8 with previous version 1.7 dated 2020-07-20

Title: Plotting Field Plans for Agricultural Experiments
Description: A function for plotting maps of agricultural field experiments that are laid out in grids.
Author: Kevin Wright [aut, cre] (<https://orcid.org/0000-0002-0617-8673>)
Maintainer: Kevin Wright <kw.stat@gmail.com>

Diff between desplot versions 1.7 dated 2020-07-20 and 1.8 dated 2020-10-21

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Package xaringan updated to version 0.18 with previous version 0.17 dated 2020-09-24

Title: Presentation Ninja
Description: Create HTML5 slides with R Markdown and the JavaScript library 'remark.js' (<https://remarkjs.com>).
Author: Yihui Xie [aut, cre] (<https://orcid.org/0000-0003-0645-5666>), Alessandro Gasparini [ctb] (<https://orcid.org/0000-0002-8319-7624>), Benjie Gillam [ctb], Claus Thorn Ekstrøm [ctb], Daniel Anderson [ctb], Dawei Lang [ctb], Emi Tanaka [ctb], Garrick Aden-Buie [ctb] (<https://orcid.org/0000-0002-7111-0077>), Iñaki Ucar [ctb] (<https://orcid.org/0000-0001-6403-5550>), John Little [ctb], Joselyn Chávez [ctb] (<https://orcid.org/0000-0002-4974-4591>), Joseph Casillas [ctb], Lucy D'Agostino McGowan [ctb] (<https://orcid.org/0000-0001-7297-9359>), Malcolm Barrett [ctb] (<https://orcid.org/0000-0003-0299-5825>), Matthew Mark Strasiotto [ctb] (mstr3336), Michael Wayne Kearney [ctb], Nan-Hung Hsieh [ctb], Ole Petter Bang [ctb] (CSS in rmarkdown/templates/xaringan/resources/default.css), Patrick Schratz [ctb], Paul Klemm [ctb] (<https://orcid.org/0000-0002-5985-1737>), Paul Lemmens [ctb], Sean Lopp [ctb], Susan VanderPlas [ctb] (<https://orcid.org/0000-0002-3803-0972>), Waldir Leoncio [ctb], Yongfu Liao [ctb], Yue Jiang [ctb] (<https://orcid.org/0000-0002-9798-5517>)
Maintainer: Yihui Xie <xie@yihui.name>

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Package SuessR updated to version 0.1.1 with previous version 0.1.0 dated 2020-09-09

Title: Suess and Laws Corrections for Marine Stable Carbon Isotope Data
Description: Generates region-specific Suess and Laws corrections for stable carbon isotope data from marine organisms collected between 1850 and 2019. Version 0.1.1 of 'SuessR' contains four built-in regions: the Bering Sea ('Bering Sea'), the Aleutian archipelago ('Aleutians Islands'), the Gulf of Alaska ('Gulf of Alaska'), and the subpolar North Atlantic ('Subpolar North Atlantic'). Users can supply their own environmental data for regions currently not built into the package to generate corrections for those regions.
Author: Casey Clark [cre, aut], Mattias Cape [aut], Mark Shapley [aut], Franz Mueter [aut], Bruce Finney [aut], Nicole Misarti [aut]
Maintainer: Casey Clark <casey.t.clark@gmail.com>

Diff between SuessR versions 0.1.0 dated 2020-09-09 and 0.1.1 dated 2020-10-21

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Package rmarkdown updated to version 2.5 with previous version 2.4 dated 2020-09-30

Title: Dynamic Documents for R
Description: Convert R Markdown documents into a variety of formats.
Author: JJ Allaire [aut], Yihui Xie [aut, cre] (<https://orcid.org/0000-0003-0645-5666>), Jonathan McPherson [aut], Javier Luraschi [aut], Kevin Ushey [aut], Aron Atkins [aut], Hadley Wickham [aut], Joe Cheng [aut], Winston Chang [aut], Richard Iannone [aut] (<https://orcid.org/0000-0003-3925-190X>), Andrew Dunning [ctb] (<https://orcid.org/0000-0003-0464-5036>), Atsushi Yasumoto [ctb, cph] (<https://orcid.org/0000-0002-8335-495X>, Number sections Lua filter), Barret Schloerke [ctb], Christophe Dervieux [ctb], Frederik Aust [ctb] (<https://orcid.org/0000-0003-4900-788X>), Jeff Allen [ctb], JooYoung Seo [ctb] (<https://orcid.org/0000-0002-4064-6012>), Malcolm Barrett [ctb], Rob Hyndman [ctb], Romain Lesur [ctb], Roy Storey [ctb], Ruben Arslan [ctb], Sergio Oller [ctb], RStudio, PBC [cph], jQuery Foundation [cph] (jQuery library), jQuery contributors [ctb, cph] (jQuery library; authors listed in inst/rmd/h/jquery-AUTHORS.txt), jQuery UI contributors [ctb, cph] (jQuery UI library; authors listed in inst/rmd/h/jqueryui-AUTHORS.txt), Mark Otto [ctb] (Bootstrap library), Jacob Thornton [ctb] (Bootstrap library), Bootstrap contributors [ctb] (Bootstrap library), Twitter, Inc [cph] (Bootstrap library), Alexander Farkas [ctb, cph] (html5shiv library), Scott Jehl [ctb, cph] (Respond.js library), Ivan Sagalaev [ctb, cph] (highlight.js library), Greg Franko [ctb, cph] (tocify library), John MacFarlane [ctb, cph] (Pandoc templates), Google, Inc. [ctb, cph] (ioslides library), Dave Raggett [ctb] (slidy library), W3C [cph] (slidy library), Dave Gandy [ctb, cph] (Font-Awesome), Ben Sperry [ctb] (Ionicons), Drifty [cph] (Ionicons), Aidan Lister [ctb, cph] (jQuery StickyTabs), Benct Philip Jonsson [ctb, cph] (pagebreak Lua filter), Albert Krewinkel [ctb, cph] (pagebreak Lua filter)
Maintainer: Yihui Xie <xie@yihui.name>

Diff between rmarkdown versions 2.4 dated 2020-09-30 and 2.5 dated 2020-10-21

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Package RaSEn updated to version 1.1.0 with previous version 1.0.0 dated 2020-06-12

Title: Random Subspace Ensemble Classification
Description: We propose a flexible ensemble classification framework, RaSE algorithm, for the sparse classification problem. In RaSE algorithm, for each weak learner, some random subspaces are generated and the optimal one is chosen to train the model on the basis of some criterion. To be adapted to the problem, a novel criterion, ratio information criterion (RIC) is put up with based on Kullback-Leibler divergence. Besides minimizing RIC, multiple criteria can be applied, for instance, minimizing extended Bayesian information criterion (eBIC), minimizing training error, minimizing the validation error, minimizing the cross-validation error, minimizing leave-one-out error. And the choices of base classifiers are also various, for instance, linear discriminant analysis, quadratic discriminant analysis, k-nearest neighbor, logistic regression, decision trees, random forest, support vector machines. RaSE algorithm can also be applied to do feature ranking, providing us the importance of each feature based on the selected percentage in multiple subspaces. In addition, to relax the requirement of the number of random subspaces to be generated, we propose an iterative version of RaSE, which is shown to be effective under many sparse binary classification settings.
Author: Ye Tian [aut, cre] and Yang Feng [aut]
Maintainer: Ye Tian <ye.t@columbia.edu>

Diff between RaSEn versions 1.0.0 dated 2020-06-12 and 1.1.0 dated 2020-10-21

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Package PRISM.forecast updated to version 0.2.1 with previous version 0.2.0 dated 2020-04-22

Title: Penalized Regression with Inferred Seasonality Module - Forecasting Unemployment Initial Claims using 'Google Trends' Data
Description: Implements Penalized Regression with Inferred Seasonality Module (PRISM) to generate forecast estimation of weekly unemployment initial claims using 'Google Trends' data. It includes required data and tools for backtesting the performance in 2007-2020.
Author: Dingdong Yi [aut, cre], Samuel Kou [aut], Shaoyang Ning [aut]
Maintainer: Dingdong Yi <ryan.ddyi@gmail.com>

Diff between PRISM.forecast versions 0.2.0 dated 2020-04-22 and 0.2.1 dated 2020-10-21

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More information about PRISM.forecast at CRAN
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Package mvrsquared updated to version 0.1.1 with previous version 0.1.0 dated 2020-06-25

Title: Compute the Coefficient of Determination for Vector or Matrix Outcomes
Description: Compute the coefficient of determination for outcomes in n-dimensions. May be useful for multidimensional predictions (such as a multinomial model) or calculating goodness of fit from latent variable models such as probabilistic topic models like latent Dirichlet allocation or deterministic topic models like latent semantic analysis. Based on Jones (2019) <arXiv:1911.11061>.
Author: Tommy Jones [aut, cre]
Maintainer: Tommy Jones <jones.thos.w@gmail.com>

Diff between mvrsquared versions 0.1.0 dated 2020-06-25 and 0.1.1 dated 2020-10-21

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Package MARSS updated to version 3.11.3 with previous version 3.11.1 dated 2020-08-27

Title: Multivariate Autoregressive State-Space Modeling
Description: The MARSS package provides maximum-likelihood parameter estimation for constrained and unconstrained linear multivariate autoregressive state-space (MARSS) models fit to multivariate time-series data. Fitting is primarily via an Expectation-Maximization (EM) algorithm, although fitting via the BFGS algorithm (using the optim function) is also provided. MARSS models are a class of dynamic linear model (DLM) and vector autoregressive model (VAR) model. Functions are provided for parametric and innovations bootstrapping, Kalman filtering and smoothing, bootstrap model selection criteria (AICb), confidences intervals via the Hessian approximation and via bootstrapping and calculation of auxiliary residuals for detecting outliers and shocks. The user guide shows examples of using MARSS for parameter estimation for a variety of applications, model selection, dynamic factor analysis, outlier and shock detection, and addition of covariates. Type RShowDoc("UserGuide", package="MARSS") at the R command line to open the MARSS user guide. Online workshops (lectures and computer labs) at <https://nwfsc-timeseries.github.io/> See the NEWS file for update information.
Author: Eli Holmes, Eric Ward, Mark Scheuerell, and Kellie Wills, NOAA, Seattle, USA
Maintainer: Elizabeth Holmes - NOAA Federal <eli.holmes@noaa.gov>

Diff between MARSS versions 3.11.1 dated 2020-08-27 and 3.11.3 dated 2020-10-21

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More information about MARSS at CRAN
Permanent link


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