Tue, 20 Oct 2020

Package torch updated to version 0.1.1 with previous version 0.1.0 dated 2020-09-28

Title: Tensors and Neural Networks with 'GPU' Acceleration
Description: Provides functionality to define and train neural networks similar to 'PyTorch' by Paszke et al (2019) <arXiv:1912.01703> but written entirely in R using the 'libtorch' library. Also supports low-level tensor operations and 'GPU' acceleration.
Author: Daniel Falbel [aut, cre, cph], Javier Luraschi [aut, cph], Dmitriy Selivanov [ctb], Athos Damiani [ctb], RStudio [cph]
Maintainer: Daniel Falbel <daniel@rstudio.com>

Diff between torch versions 0.1.0 dated 2020-09-28 and 0.1.1 dated 2020-10-20

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More information about torch at CRAN
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Package pkgmaker updated to version 0.32.2 with previous version 0.31.1 dated 2020-03-19

Title: Development Utilities for R Packages
Description: Provides some low-level utilities to use for package development. It currently provides managers for multiple package specific options and registries, vignette, unit test and bibtex related utilities. It serves as a base package for packages like NMF, RcppOctave, doRNG, and as an incubator package for other general purposes utilities, that will eventually be packaged separately. It is still under heavy development and changes in the interface(s) are more than likely to happen.
Author: Renaud Gaujoux [aut, cre]
Maintainer: Renaud Gaujoux <renozao@protonmail.com>

Diff between pkgmaker versions 0.31.1 dated 2020-03-19 and 0.32.2 dated 2020-10-20

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Package wellknown updated to version 0.7.0 with previous version 0.6.0 dated 2020-01-10

Title: Convert Between 'WKT' and 'GeoJSON'
Description: Convert 'WKT' to 'GeoJSON' and 'GeoJSON' to 'WKT'. Functions included for converting between 'GeoJSON' to 'WKT', creating both 'GeoJSON' features, and non-features, creating 'WKT' from R objects (e.g., lists, data.frames, vectors), and linting 'WKT'.
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>)
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

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Package VGAMdata updated to version 1.1-4 with previous version 1.0-3 dated 2017-01-10

Title: Data Supporting the 'VGAM' Package
Description: Mainly data sets to accompany the VGAM package and the book "Vector Generalized Linear and Additive Models: With an Implementation in R" (Yee, 2015) <DOI:10.1007/978-1-4939-2818-7>. These are used to illustrate vector generalized linear and additive models (VGLMs/VGAMs), and associated models (Reduced-Rank VGLMs, Quadratic RR-VGLMs, Row-Column Interaction Models, and constrained and unconstrained ordination models in ecology). This package now contains some old VGAM family functions which have been replaced by newer ones (often because they are now special cases).
Author: Thomas Yee [aut, cre, cph], James Gray [dtc]
Maintainer: Thomas Yee <t.yee@auckland.ac.nz>

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More information about VGAMdata at CRAN
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New package ripserr with initial version 0.1.1
Package: ripserr
Title: Calculate Persistent Homology with Ripser-Based Engines
Version: 0.1.1
Authors@R: c(person(given = "Raoul", family = "Wadhwa", role = c("aut", "cre"), email = "raoulwadhwa@gmail.com", comment = c(ORCID = "0000-0003-0503-9580")), person(given = "Matt", family = "Piekenbrock", role = "aut", email = "matt.piekenbrock@gmail.com"), person(given = "Jacob", family = "Scott", role = "aut", comment = c(ORCID = "0000-0003-2971-7673")), person(given = "Takeki", family = "Sudo", role = c("cph", "ctb"), comment = paste("Takeki Sudo is a copyright holder for Cubical", "Ripser (GPL-3 license), which was refactored", "prior to inclusion in ripserr.")), person(given = "Kazushi", family = "Ahara", role = c("cph", "ctb"), comment = paste("Kazushi Ahara is a copyright holder for Cubical", "Ripser (GPL-3 license), which was refactored", "prior to inclusion in ripserr.")), person(given = "Ulrich", family = "Bauer", role = c("cph", "ctb"), comment = paste("Ulrich Bauer holds the copyright to Ripser", "(MIT license), which was refactored prior", "to inclusion in ripserr.")))
Description: Ports the Ripser <arXiv:1908.02518> and Cubical Ripser <arXiv:2005.12692> persistent homology calculation engines from C++. Can be used as a rapid calculation tool in topological data analysis pipelines.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
URL: https://rrrlw.github.io/ripserr/
BugReports: https://github.com/rrrlw/ripserr/issues
LinkingTo: Rcpp
Depends: R (>= 3.5.0)
Imports: methods (>= 3.0), Rcpp (>= 1.0), stats (>= 3.0)
SystemRequirements: C++11
Suggests: testthat (>= 2.3), covr (>= 3.5), knitr (>= 1.29), rmarkdown (>= 2.3)
NeedsCompilation: yes
Packaged: 2020-10-15 10:51:01 UTC; appveyor
Author: Raoul Wadhwa [aut, cre] (<https://orcid.org/0000-0003-0503-9580>), Matt Piekenbrock [aut], Jacob Scott [aut] (<https://orcid.org/0000-0003-2971-7673>), Takeki Sudo [cph, ctb] (Takeki Sudo is a copyright holder for Cubical Ripser (GPL-3 license), which was refactored prior to inclusion in ripserr.), Kazushi Ahara [cph, ctb] (Kazushi Ahara is a copyright holder for Cubical Ripser (GPL-3 license), which was refactored prior to inclusion in ripserr.), Ulrich Bauer [cph, ctb] (Ulrich Bauer holds the copyright to Ripser (MIT license), which was refactored prior to inclusion in ripserr.)
Maintainer: Raoul Wadhwa <raoulwadhwa@gmail.com>
Repository: CRAN
Date/Publication: 2020-10-20 20:10:03 UTC

More information about ripserr at CRAN
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Package representr updated to version 0.1.1 with previous version 0.1.0 dated 2020-10-17

Title: Create Representative Records After Entity Resolution
Description: An implementation of Kaplan, Betancourt, Steorts (2020) <arXiv:1810.01538> that creates representative records for use in downstream tasks after entity resolution is performed. Multiple methods for creating the representative records (data sets) are provided.
Author: Andee Kaplan [aut, cre], Brenda Betancourt [aut], Rebecca C. Steorts [aut]
Maintainer: Andee Kaplan <andee.kaplan@colostate.edu>

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Package arrow updated to version 2.0.0 with previous version 1.0.1 dated 2020-08-28

Title: Integration to 'Apache' 'Arrow'
Description: 'Apache' 'Arrow' <https://arrow.apache.org/> is a cross-language development platform for in-memory data. It specifies a standardized language-independent columnar memory format for flat and hierarchical data, organized for efficient analytic operations on modern hardware. This package provides an interface to the 'Arrow C++' library.
Author: Romain François [aut] (<https://orcid.org/0000-0002-2444-4226>), Jeroen Ooms [aut], Neal Richardson [aut, cre], Javier Luraschi [ctb], Jeffrey Wong [ctb], Apache Arrow [aut, cph]
Maintainer: Neal Richardson <neal@ursalabs.org>

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More information about arrow at CRAN
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Package sharpshootR updated to version 1.6.5 with previous version 1.6 dated 2020-01-30

Title: A Soil Survey Toolkit
Description: Miscellaneous soil data management, summary, visualization, and conversion utilities to support soil survey.
Author: Dylan Beaudette [cre], Jay Skovlin [aut], Stephen Roecker [aut], USDA-NRCS Soil Survey Staff [ctb]
Maintainer: Dylan Beaudette <dylan.beaudette@usda.gov>

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Package lgr updated to version 0.4.1 with previous version 0.3.4 dated 2020-03-20

Title: A Fully Featured Logging Framework
Description: A flexible, feature-rich yet light-weight logging framework based on 'R6' classes. It supports hierarchical loggers, custom log levels, arbitrary data fields in log events, logging to plaintext, 'JSON', (rotating) files, memory buffers. For extra appenders that support logging to databases, email and push notifications see the the package lgr.app.
Author: Stefan Fleck [aut, cre] (<https://orcid.org/0000-0003-3344-9851>)
Maintainer: Stefan Fleck <stefan.b.fleck@gmail.com>

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Package hisse updated to version 1.9.9 with previous version 1.9.8 dated 2020-06-15

Title: Hidden State Speciation and Extinction
Description: Sets up and executes a HiSSE model (Hidden State Speciation and Extinction) on a phylogeny and character sets to test for hidden shifts in trait dependent rates of diversification. Beaulieu and O'Meara (2016) <doi:10.1093/sysbio/syw022>.
Author: Jeremy Beaulieu [aut, cre], Brian O'Meara [aut], Daniel Caetano [aut], James Boyko [aut]
Maintainer: Jeremy Beaulieu <jmbeauli@uark.edu>

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Package fdaACF updated to version 1.0.0 with previous version 0.2.0 dated 2020-08-11

Title: Autocorrelation Function for Functional Time Series
Description: Quantify the serial correlation across lags of a given functional time series using the autocorrelation function and a partial autocorrelation function for functional time series proposed in Mestre et al. (2021) <doi:10.1016/j.csda.2020.107108>. The autocorrelation functions are based on the L2 norm of the lagged covariance operators of the series. Functions are available for estimating the distribution of the autocorrelation functions under the assumption of strong functional white noise.
Author: Guillermo Mestre Marcos [aut, cre], José Portela González [aut], Gregory Rice [aut], Antonio Muñoz San Roque [ctb], Estrella Alonso Pérez [ctb]
Maintainer: Guillermo Mestre Marcos <guillermo.mestre@comillas.edu>

Diff between fdaACF versions 0.2.0 dated 2020-08-11 and 1.0.0 dated 2020-10-20

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New package animint2 with initial version 2020.9.18
Package: animint2
Title: Animated Interactive Grammar of Graphics
Version: 2020.9.18
URL: https://github.com/tdhock/animint2
BugReports: https://github.com/tdhock/animint2/issues
Authors@R: c( person("Toby", "Hocking", email="toby.hocking@r-project.org", role=c("aut", "cre"), comment="Original animint code"), person("Hadley", "Wickham", role=c("aut"), comment="Forked ggplot2 code"), person("Winston", "Chang", role="aut", comment="Forked ggplot2 code"), person("RStudio", role = c("cph"), comment="Forked ggplot2 code"), person("Nicholas", "Lewin-Koh", role="aut", comment="hexGrob"), person("Martin", "Maechler", role="aut", comment="hexGrob"), person("Randall", "Prium", role="aut", comment="cut_width"), person("Susan", "VanderPlas", role="aut", comment="Animint GSOC 2013"), person("Carson", "Sievert", role="aut", comment="Animint GSOC 2014"), person("Kevin", "Ferris", role="aut", comment="Animint GSOC 2015"), person("Jun", "Cai", role="aut", comment="Animint GSOC 2015"), person("Faizan", "Khan", role="aut", comment="Animint GSOC 2016-2017"), person("Vivek", "Kumar", role="aut", comment="Animint GSOC 2018"), person("Himanshu", "Singh", role="aut", comment="Animint2 GSoC 2020"))
Description: Functions are provided for defining animated, interactive data visualizations in R code, and rendering on a web page. The 2018 Journal of Computational and Graphical Statistics paper, <doi:10.1080/10618600.2018.1513367> describes the concepts implemented.
Depends: R (>= 3.4.0)
Imports: digest, RJSONIO, grid, gtable (>= 0.1.1), MASS, plyr (>= 1.7.1), reshape2, scales (>= 0.4.1), stats, tibble, lazyeval, knitr (>= 1.5.33)
Suggests: servr, gistr (>= 0.2), shiny, htmltools, rmarkdown, testthat, devtools, httr, maps, ggplot2movies, hexbin, Hmisc, lattice, mapproj, maptools, mgcv, nlme, quantreg, rpart, svglite
Enhances: sp
License: GPL-3
Encoding: UTF-8
LazyData: true
Collate: 'gganimintproto.r' 'aaa-.r' 'aes-calculated.r' 'aes-colour-fill-alpha.r' 'aes-group-order.r' 'aes-linetype-size-shape.r' 'aes-position.r' 'utilities.r' 'aes.r' 'legend-draw.r' 'geom-.r' 'annotation-custom.r' 'annotation-logticks.r' 'geom-polygon.r' 'geom-map.r' 'annotation-map.r' 'geom-raster.r' 'annotation-raster.r' 'annotation.r' 'autoplot.r' 'bench.r' 'bin.R' 'coord-.r' 'coord-cartesian-.r' 'coord-fixed.r' 'coord-flip.r' 'coord-map.r' 'coord-munch.r' 'coord-polar.r' 'coord-quickmap.R' 'coord-transform.r' 'data.R' 'facet-.r' 'facet-grid-.r' 'facet-labels.r' 'facet-layout.r' 'facet-locate.r' 'facet-null.r' 'facet-viewports.r' 'facet-wrap.r' 'fortify-lm.r' 'fortify-map.r' 'fortify-spatial.r' 'fortify.r' 'stat-.r' 'geom-abline.r' 'geom-rect.r' 'geom-bar.r' 'geom-bin2d.r' 'geom-blank.r' 'geom-boxplot.r' 'geom-path.r' 'geom-contour.r' 'geom-count.r' 'geom-crossbar.r' 'geom-segment.r' 'geom-curve.r' 'geom-defaults.r' 'geom-ribbon.r' 'geom-density.r' 'geom-density2d.r' 'geom-dotplot.r' 'geom-errorbar.r' 'geom-errorbarh.r' 'geom-freqpoly.r' 'geom-hex.r' 'geom-histogram.r' 'geom-hline.r' 'geom-jitter.r' 'geom-label.R' 'geom-linerange.r' 'geom-point.r' 'geom-pointrange.r' 'geom-quantile.r' 'geom-rug.r' 'geom-smooth.r' 'geom-spoke.r' 'geom-text.r' 'geom-tile.r' 'geom-violin.r' 'geom-vline.r' 'ggplot2.r' 'grob-absolute.r' 'grob-dotstack.r' 'grob-null.r' 'grouping.r' 'guide-colorbar.r' 'guide-legend.r' 'guides-.r' 'guides-axis.r' 'guides-grid.r' 'hexbin.R' 'labels.r' 'layer.r' 'limits.r' 'margins.R' 'panel.r' 'plot-build.r' 'plot-construction.r' 'plot-last.r' 'plot.r' 'position-.r' 'position-collide.r' 'position-dodge.r' 'position-fill.r' 'position-identity.r' 'position-jitter.r' 'position-jitterdodge.R' 'position-nudge.R' 'position-stack.r' 'quick-plot.r' 'range.r' 'save.r' 'scale-.r' 'scale-alpha.r' 'scale-brewer.r' 'scale-continuous.r' 'scale-date.r' 'scale-discrete-.r' 'scale-gradient.r' 'scale-grey.r' 'scale-hue.r' 'scale-identity.r' 'scale-linetype.r' 'scale-manual.r' 'scale-shape.r' 'scale-size.r' 'scale-type.R' 'scales-.r' 'stat-bin.r' 'stat-bin2d.r' 'stat-bindot.r' 'stat-binhex.r' 'stat-boxplot.r' 'stat-contour.r' 'stat-count.r' 'stat-density-2d.r' 'stat-density.r' 'stat-ecdf.r' 'stat-ellipse.R' 'stat-function.r' 'stat-identity.r' 'stat-qq.r' 'stat-quantile.r' 'stat-smooth-methods.r' 'stat-smooth.r' 'stat-sum.r' 'stat-summary-2d.r' 'stat-summary-bin.R' 'stat-summary-hex.r' 'stat-summary.r' 'stat-unique.r' 'stat-ydensity.r' 'summary.r' 'theme-defaults.r' 'theme-elements.r' 'theme.r' 'translate-qplot-ggplot.r' 'translate-qplot-lattice.r' 'utilities-break.r' 'utilities-grid.r' 'utilities-help.r' 'utilities-matrix.r' 'utilities-resolution.r' 'utilities-table.r' 'uu_zxx.r' 'uu_zzz.r' 'z_animint.R' 'z_animintHelpers.R' 'z_facets.R' 'z_geoms.R' 'z_gist.R' 'z_helperFunctions.R' 'z_knitr.R' 'z_print.R' 'z_scales.R' 'z_theme_animint.R' 'z_transformShape.R'
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-10-19 22:51:31 UTC; tdhock
Author: Toby Hocking [aut, cre] (Original animint code), Hadley Wickham [aut] (Forked ggplot2 code), Winston Chang [aut] (Forked ggplot2 code), RStudio [cph] (Forked ggplot2 code), Nicholas Lewin-Koh [aut] (hexGrob), Martin Maechler [aut] (hexGrob), Randall Prium [aut] (cut_width), Susan VanderPlas [aut] (Animint GSOC 2013), Carson Sievert [aut] (Animint GSOC 2014), Kevin Ferris [aut] (Animint GSOC 2015), Jun Cai [aut] (Animint GSOC 2015), Faizan Khan [aut] (Animint GSOC 2016-2017), Vivek Kumar [aut] (Animint GSOC 2018), Himanshu Singh [aut] (Animint2 GSoC 2020)
Maintainer: Toby Hocking <toby.hocking@r-project.org>
Repository: CRAN
Date/Publication: 2020-10-20 20:00:19 UTC

More information about animint2 at CRAN
Permanent link

Package adoptr updated to version 0.4.1 with previous version 0.3.2 dated 2020-01-09

Title: Adaptive Optimal Two-Stage Designs in R
Description: Optimize one or two-arm, two-stage designs for clinical trials with respect to several pre-implemented objective criteria or implement custom objectives. Optimization under uncertainty and conditional (given stage-one outcome) constraints are supported. See Pilz M, Kunzmann K, Herrmann C, Rauch G, Kieser M. A variational approach to optimal two-stage designs. Statistics in Medicine. 2019;38(21):4159–4171. <doi:10.1002/sim.8291> for details.
Author: Kevin Kunzmann [aut, cre], Maximilian Pilz [aut]
Maintainer: Kevin Kunzmann <kevin.kunzmann@mrc-bsu.cam.ac.uk>

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Package OUwie updated to version 2.5 with previous version 2.4 dated 2020-08-04

Title: Analysis of Evolutionary Rates in an OU Framework
Description: Estimates rates for continuous character evolution under Brownian motion and a new set of Ornstein-Uhlenbeck based Hansen models that allow both the strength of the pull and stochastic motion to vary across selective regimes. Beaulieu et al (2012) <doi:10.1111/j.1558-5646.2012.01619.x>.
Author: Jeremy M. Beaulieu <jmbeauli@uark.edu>, Brian O'Meara <bomeara@utk.edu>
Maintainer: Jeremy Beaulieu <jmbeauli@uark.edu>

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Package NMOF updated to version 2.2-2 with previous version 2.1-0 dated 2020-04-06

Title: Numerical Methods and Optimization in Finance
Description: Functions, examples and data from the first and the second edition of "Numerical Methods and Optimization in Finance" by M. Gilli, D. Maringer and E. Schumann (2019, ISBN:978-0128150658). The package provides implementations of optimisation heuristics (Differential Evolution, Genetic Algorithms, Particle Swarm Optimisation, Simulated Annealing and Threshold Accepting), and other optimisation tools, such as grid search and greedy search. There are also functions for the valuation of financial instruments such as bonds and options, for portfolio selection and functions that help with stochastic simulations.
Author: Enrico Schumann [aut, cre] (<https://orcid.org/0000-0001-7601-6576>)
Maintainer: Enrico Schumann <es@enricoschumann.net>

Diff between NMOF versions 2.1-0 dated 2020-04-06 and 2.2-2 dated 2020-10-20

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Package miRNAss updated to version 1.5 with previous version 1.4 dated 2018-01-02

Title: Genome-Wide Discovery of Pre-miRNAs with few Labeled Examples
Description: Machine learning method specifically designed for pre-miRNA prediction. It takes advantage of unlabeled sequences to improve the prediction rates even when there are just a few positive examples, when the negative examples are unreliable or are not good representatives of its class. Furthermore, the method can automatically search for negative examples if the user is unable to provide them. MiRNAss can find a good boundary to divide the pre-miRNAs from other groups of sequences; it automatically optimizes the threshold that defines the classes boundaries, and thus, it is robust to high class imbalance. Each step of the method is scalable and can handle large volumes of data.
Author: Cristian Yones
Maintainer: Cristian Yones <cyones@sinc.unl.edu.ar>

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Package anomalize updated to version 0.2.2 with previous version 0.2.1 dated 2020-06-19

Title: Tidy Anomaly Detection
Description: The 'anomalize' package enables a "tidy" workflow for detecting anomalies in data. The main functions are time_decompose(), anomalize(), and time_recompose(). When combined, it's quite simple to decompose time series, detect anomalies, and create bands separating the "normal" data from the anomalous data at scale (i.e. for multiple time series). Time series decomposition is used to remove trend and seasonal components via the time_decompose() function and methods include seasonal decomposition of time series by Loess ("stl") and seasonal decomposition by piecewise medians ("twitter"). The anomalize() function implements two methods for anomaly detection of residuals including using an inner quartile range ("iqr") and generalized extreme studentized deviation ("gesd"). These methods are based on those used in the 'forecast' package and the Twitter 'AnomalyDetection' package. Refer to the associated functions for specific references for these methods.
Author: Matt Dancho [aut, cre], Davis Vaughan [aut]
Maintainer: Matt Dancho <mdancho@business-science.io>

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Package streambugs updated to version 1.2 with previous version 1.1 dated 2019-09-19

Title: Parametric Ordinary Differential Equations Model of Growth, Death, and Respiration of Macroinvertebrate and Algae Taxa
Description: Numerically solve and plot solutions of a parametric ordinary differential equations model of growth, death, and respiration of macroinvertebrate and algae taxa dependent on pre-defined environmental factors. The model (version 1.0) is introduced in Schuwirth, N. and Reichert, P., (2013) <DOI:10.1890/12-0591.1>. This package includes model extensions and the core functions introduced and used in Schuwirth, N. et al. (2016) <DOI:10.1111/1365-2435.12605>, Kattwinkel, M. et al. (2016) <DOI:10.1021/acs.est.5b04068>, Mondy, C. P., and Schuwirth, N. (2017) <DOI:10.1002/eap.1530>, and Paillex, A. et al. (2017) <DOI:10.1111/fwb.12927>.
Author: Nele Schuwirth, Peter Reichert, Mikolaj Rybinski
Maintainer: Nele Schuwirth <nele.schuwirth@eawag.ch>

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Package dfoptim updated to version 2020.10-1 with previous version 2018.2-1 dated 2018-04-02

Title: Derivative-Free Optimization
Description: Derivative-Free optimization algorithms. These algorithms do not require gradient information. More importantly, they can be used to solve non-smooth optimization problems.
Author: Ravi Varadhan[aut, cre], Johns Hopkins University, Hans W. Borchers[aut], ABB Corporate Research, and Vincent Bechard[aut], HEC Montreal (Montreal University)
Maintainer: Ravi Varadhan <ravi.varadhan@jhu.edu>

Diff between dfoptim versions 2018.2-1 dated 2018-04-02 and 2020.10-1 dated 2020-10-20

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Permanent link

New package r5r with initial version 0.2-0
Type: Package
Package: r5r
Title: Rapid Realistic Routing with 'R5'
Version: 0.2-0
Authors@R: c( person(given="Marcus", family="Saraiva", email="marcus.saraiva@gmail.com", role="aut", comment = c(ORCID = "0000-0001-6218-2338")), person(given="Rafael H. M.", family="Pereira", email="rafa.pereira.br@gmail.com", role=c("aut", "cre"), comment = c(ORCID = "0000-0003-2125-7465")), person(given="Daniel", family="Herszenhut", email="dhersz@gmail.com", role="aut", comment = c(ORCID = "0000-0001-8066-1105")), person(given="Carlos Kaue Vieira", family="Braga", email="kaue@kauebraga.dev", role="aut", comment = c(ORCID = "0000-0002-6104-7297")), person("Ipea - Institue for Applied Economic Research", role = c("cph", "fnd")) )
Description: Rapid realistic routing on multimodal transport networks (walk, bike, public transport and car) using 'R5', the Rapid Realistic Routing on Real-world and Reimagined networks <https://github.com/conveyal/r5>. The package allows users to generate detailed routing analysis or calculate travel time matrices using seamless parallel computing on top of the R5 Java machine.
Date: 2020-10-04
URL: https://github.com/ipeaGIT/r5r
BugReports: https://github.com/ipeaGIT/r5r/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: TRUE
Depends: R (>= 3.6)
Suggests: covr, ggplot2 (>= 3.3.1), knitr, mapview, rmarkdown, testthat
Imports: checkmate, data.table, methods, jdx (>= 0.1.4), rJava (>= 0.9-10), sf (>= 0.9-3), sfheaders, utils
SystemRequirements: Java JDK (>= 11.0)
RoxygenNote: 7.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-10-20 14:54:00 UTC; user
Author: Marcus Saraiva [aut] (<https://orcid.org/0000-0001-6218-2338>), Rafael H. M. Pereira [aut, cre] (<https://orcid.org/0000-0003-2125-7465>), Daniel Herszenhut [aut] (<https://orcid.org/0000-0001-8066-1105>), Carlos Kaue Vieira Braga [aut] (<https://orcid.org/0000-0002-6104-7297>), Ipea - Institue for Applied Economic Research [cph, fnd]
Maintainer: Rafael H. M. Pereira <rafa.pereira.br@gmail.com>
Repository: CRAN
Date/Publication: 2020-10-20 15:40:02 UTC

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Package mrf2d updated to version 0.4.1 with previous version 0.4.0 dated 2020-06-30

Title: Markov Random Field Models for Image Analysis
Description: Model fitting, sampling and visualization for the (Hidden) Markov Random Field model with pairwise interactions and general interaction structure from Freguglia, Garcia & Bicas (2020) <doi:10.1002/env.2613>, which has many popular models used in 2-dimensional lattices as particular cases, like the Ising Model and Potts Model.
Author: Victor Freguglia [aut, cre] (<https://orcid.org/0000-0002-6189-4453>)
Maintainer: Victor Freguglia <victorfreguglia@gmail.com>

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Package leaflet.extras2 updated to version 1.1.0 with previous version 1.0.0 dated 2020-05-18

Title: Extra Functionality for 'leaflet' Package
Description: Several 'leaflet' plugins are integrated, which are available as extension to the 'leaflet' package.
Author: Gatscha Sebastian [aut, cre]
Maintainer: Gatscha Sebastian <sebastian_gatscha@gmx.at>

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Package windfarmGA updated to version 2.3.0 with previous version 2.2.3 dated 2019-12-16

Title: Genetic Algorithm for Wind Farm Layout Optimization
Description: The genetic algorithm is designed to optimize wind farms of any shape. It requires a predefined amount of turbines, a unified rotor radius and an average wind speed value for each incoming wind direction. A terrain effect model can be included that downloads an 'SRTM' elevation model and loads a Corine Land Cover raster to approximate surface roughness.
Author: Sebastian Gatscha [aut, cre]
Maintainer: Sebastian Gatscha <sebastian_gatscha@gmx.at>

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New package singcar with initial version 0.1.0
Package: singcar
Title: Comparing Single Cases to Small Samples
Version: 0.1.0
Authors@R: c(person(given = "Jonathan", family = "Rittmo", role = c("aut", "cre"), email = "j.rittmo@gmail.com", comment = c(ORCID = "0000-0001-5075-0166")), person(given = "Robert", family = "McIntosh", role = c("aut"), email = "r.d.mcintosh@ed.ac.uk", comment = c(ORCID = "0000-0002-7615-6699")))
Description: When comparing single cases to control populations and no parameters are known researchers and clinicians must estimate these with a control sample. This is often done when testing a case's abnormality on some variable or testing abnormality of the discrepancy between two variables. Appropriate frequentist and Bayesian methods for doing this are here implemented, including tests allowing for the inclusion of covariates. These have been developed first and foremost by John Crawford and Paul Garthwaite, e.g. in Crawford and Howell (1998) <doi:10.1076/clin.12.4.482.7241>, Crawford and Garthwaite (2005) <doi:10.1037/0894-4105.19.3.318>, Crawford and Garthwaite (2007) <doi:10.1080/02643290701290146> and Crawford, Garthwaite and Ryan (2011) <doi:10.1016/j.cortex.2011.02.017>. The package is also equipped with power calculators for each method.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 2.10)
Imports: stats, CholWishart, MASS, withr
Suggests: knitr, rmarkdown, bookdown, testthat (>= 2.1.0)
VignetteBuilder: knitr
URL: https://github.com/jorittmo/singcar
BugReports: https://github.com/jorittmo/singcar/issues
NeedsCompilation: no
Packaged: 2020-10-13 08:36:34 UTC; jritt
Author: Jonathan Rittmo [aut, cre] (<https://orcid.org/0000-0001-5075-0166>), Robert McIntosh [aut] (<https://orcid.org/0000-0002-7615-6699>)
Maintainer: Jonathan Rittmo <j.rittmo@gmail.com>
Repository: CRAN
Date/Publication: 2020-10-20 15:00:02 UTC

More information about singcar at CRAN
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Package rotor updated to version 0.3.2 with previous version 0.3.1 dated 2020-10-18

Title: Log Rotation and Conditional Backups
Description: Conditionally rotate or back-up files based on their size or the date of the last backup; inspired by the 'Linux' utility 'logrotate'.
Author: Stefan Fleck [aut, cre] (<https://orcid.org/0000-0003-3344-9851>)
Maintainer: Stefan Fleck <stefan.b.fleck@gmail.com>

Diff between rotor versions 0.3.1 dated 2020-10-18 and 0.3.2 dated 2020-10-20

 DESCRIPTION                 |    6 +++---
 MD5                         |    6 +++---
 R/Cache.R                   |    3 ++-
 tests/testthat/test_Cache.R |   32 +++++++++++++++++++++-----------
 4 files changed, 29 insertions(+), 18 deletions(-)

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Package rEDM updated to version 1.6.1 with previous version 1.5.0 dated 2020-07-06

Title: Empirical Dynamic Modeling ('EDM')
Description: An implementation of 'EDM' algorithms based on research software developed for internal use at the Sugihara Lab ('UCSD/SIO'). The package is implemented with 'Rcpp' wrappers around the 'cppEDM' library. It implements the 'simplex' projection method from Sugihara & May (1990) <doi:10.1038/344734a0>, the 'S-map' algorithm from Sugihara (1994) <doi:10.1098/rsta.1994.0106>, convergent cross mapping described in Sugihara et al. (2012) <doi:10.1126/science.1227079>, and, 'multiview embedding' described in Ye & Sugihara (2016) <doi:10.1126/science.aag0863>.
Author: Joseph Park [aut, cre] (<https://orcid.org/0000-0001-5411-1409>), Cameron Smith [aut], George Sugihara [aut, ccp] (<https://orcid.org/0000-0002-2863-6946>), Ethan Deyle [aut] (<https://orcid.org/0000-0001-8704-8434>), Erik Saberski [ctb] (<https://orcid.org/0000-0002-6475-6187>), Hao Ye [ctb] (<https://orcid.org/0000-0002-8630-1458>), The Regents of the University of California [cph]
Maintainer: Joseph Park <JosephPark@IEEE.org>

Diff between rEDM versions 1.5.0 dated 2020-07-06 and 1.6.1 dated 2020-10-20

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Package QRIpkg updated to version 0.2.1 with previous version 0.2.0 dated 2020-09-20

Title: Quantile Regression Index Score
Description: The QRI_func() function performs quantile regression analysis using age and sex as predictors to calculate the Quantile Regression Index (QRI) score for each individual’s regional brain imaging metrics and then averages across the regional scores to generate an average tissue specific score for each subject. The QRI_plot() is used to plot QRI and generate the normative curves for individual measurements.
Author: Peter Kochunov [aut], Si Gao [aut, cre], Meghann Ryan [aut]
Maintainer: Si Gao <sgao@som.umaryland.edu>

Diff between QRIpkg versions 0.2.0 dated 2020-09-20 and 0.2.1 dated 2020-10-20

 DESCRIPTION     |    6 +++---
 MD5             |    6 +++---
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New package parallelly with initial version 1.20.0
Package: parallelly
Version: 1.20.0
Title: Enhancing the 'parallel' Package
Imports: parallel, tools, utils
Authors@R: c(person("Henrik", "Bengtsson", role=c("aut", "cre", "cph"), email = "henrikb@braju.com"))
Description: Utility functions that enhances the 'parallel' packages and that are used for the built-in parallel backends of the 'future' package. For example, availableCores() gives the number of CPU cores available to your R process as given by relevant R options and environment variables including those set by job schedulers on high-performance compute clusters. If none is set, it will fall back to parallel::detectCores(). Another example is makeClusterPSOCK(), which is backward compatible with parallel::makePSOCKcluster() while doing a better job in setting up a remote cluster workers without the need for configuring the firewall to do port-forwarding to your local computer.
License: LGPL (>= 2.1)
LazyLoad: TRUE
ByteCompile: TRUE
URL: https://github.com/HenrikBengtsson/parallelly
BugReports: https://github.com/HenrikBengtsson/parallelly/issues
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-10-10 21:27:10 UTC; hb
Author: Henrik Bengtsson [aut, cre, cph]
Maintainer: Henrik Bengtsson <henrikb@braju.com>
Repository: CRAN
Date/Publication: 2020-10-20 14:20:02 UTC

More information about parallelly at CRAN
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New package packer with initial version 0.0.6
Package: packer
Title: An Opinionated Framework for Using 'JavaScript'
Date: 2020-10-11
Version: 0.0.6
Authors@R: person(given = "John", family = "Coene", role = c("aut", "cre"), email = "jcoenep@gmail.com", comment = c(ORCID = "0000-0002-6637-4107"))
Description: Enforces good practice and provides convenience functions to make work with 'JavaScript' not just easier but also scalable. It is a robust wrapper to 'NPM' and 'webpack' that enables to compartmentalize 'JavaScript' code, leverage 'NPM' packages, and much more.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1.9000
Imports: fs, usethis, jsonlite, htmlwidgets, cli, assertthat, rprojroot, rstudioapi
URL: https://github.com/JohnCoene/packer, https://packer.john-coene.com
BugReports: https://github.com/JohnCoene/packer/issues
Suggests: testthat, covr, golem
NeedsCompilation: no
Packaged: 2020-10-12 20:19:34 UTC; jp
Author: John Coene [aut, cre] (<https://orcid.org/0000-0002-6637-4107>)
Maintainer: John Coene <jcoenep@gmail.com>
Repository: CRAN
Date/Publication: 2020-10-20 14:30:02 UTC

More information about packer at CRAN
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Package EpiNow2 updated to version 1.2.1 with previous version 1.1.0 dated 2020-09-01

Title: Estimate Real-Time Case Counts and Time-Varying Epidemiological Parameters
Description: Estimates the time-varying reproduction number, rate of spread, and doubling time using a range of open-source tools (Abbott et al. (2020) <doi:10.12688/wellcomeopenres.16006.1>), and current best practices (Gostic et al. (2020) <doi:10.1101/2020.06.18.20134858>). It aims to help users avoid some of the limitations of naive implementations in a framework that is informed by community feedback and is under active development.
Author: Sam Abbott [aut, cre] (<https://orcid.org/0000-0001-8057-8037>), Joel Hellewell [aut] (<https://orcid.org/0000-0003-2683-0849>), Robin Thompson [aut], Katelyn Gostic [aut], Katharine Sherratt [aut], Sophie Meakin [aut], James Munday [aut], Nikos Bosse [aut], Joe Hickson [aut], Paul Mee [ctb], Peter Ellis [ctb], Hamada S. Badr [ctb] (<https://orcid.org/0000-0002-9808-2344>), Michael DeWitt [ctb] (<https://orcid.org/0000-0001-8940-1967>), EpiForecasts [aut], Sebastian Funk [aut]
Maintainer: Sam Abbott <sam.abbott@lshtm.ac.uk>

Diff between EpiNow2 versions 1.1.0 dated 2020-09-01 and 1.2.1 dated 2020-10-20

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Package bootcluster updated to version 0.2.0 with previous version 0.1.0 dated 2017-11-13

Title: Bootstrapping Estimates of Clustering Stability
Description: Implementation of the bootstrapping approach for the estimation of clustering stability and its application in estimating the number of clusters, as introduced by Yu et al<doi:10.1142/9789814749411_0007>. Implementation of the non-parametric bootstrap approach to assessing the stability of module detection in a graph, the extension for the selection of a parameter set that defines a graph from data in a way that optimizes stability and the corresponding visualization functions, as introduced by Tian et al.
Author: Han Yu, Mingmei Tian
Maintainer: Mingmei Tian <mingmeit@buffalo.edu>

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Package BIOMASS updated to version 2.1.4 with previous version 2.1.3 dated 2020-06-25

Title: Estimating Aboveground Biomass and Its Uncertainty in Tropical Forests
Description: Contains functions to estimate aboveground biomass/carbon and its uncertainty in tropical forests. These functions allow to (1) retrieve and to correct taxonomy, (2) estimate wood density and its uncertainty, (3) construct height-diameter models, (4) manage tree and plot coordinates, (5) estimate the aboveground biomass/carbon at the stand level with associated uncertainty. To cite BIOMASS, please use citation("BIOMASS"). See more in the article of Réjou-Méchain et al. (2017) <doi:10.1111/2041-210X.12753>.
Author: Maxime Réjou-Méchain [aut, cre, dtc], Arthur Pere [aut], Guillaume Cornu [aut] (<https://orcid.org/0000-0002-7523-5176>), Ariane Tanguy [aut], Camille Piponiot [aut], Jerome Chave [dtc], Bruno Hérault [aut], Ted Feldpausch [dtc], Philippe Verley [ctb]
Maintainer: Maxime Réjou-Méchain <maxime.rejou@gmail.com>

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Package GofKmt updated to version 2.2.0 with previous version 2.1.1 dated 2020-02-21

Title: Khmaladze Martingale Transformation Goodness-of-Fit Test
Description: Consider a goodness-of-fit (GOF) problem of testing whether a random sample comes from one sample location-scale model where location and scale parameters are unknown. It is well known that Khmaladze martingale transformation method - which was proposed by Khmaladze (1981) <DOI:10.1137/1126027> - provides asymptotic distribution free test for the GOF problem. This package contains one function: KhmaladzeTrans(). In this version, KhmaladzeTrans() provides test statistic and critical value of GOF test for normal, Cauchy, and logistic distributions. This package used the main algorithm proposed by Kim (2020) <DOI:10.1007/s00180-020-00971-7> and tests for other distributions will be available at the later version.
Author: Jiwoong Kim <jwboys26 at gmail.com>
Maintainer: Jiwoong Kim <jwboys26@gmail.com>

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Package tm1r updated to version 1.1.5 with previous version 1.1.4 dated 2020-03-19

Title: The Integration Between 'IBM COGNOS TM1' and R
Description: Useful functions to connect to 'TM1' <https://www.ibm.com/uk-en/products/planning-and-analytics> instance from R via REST API. With the functions in the package, data can be imported from 'TM1' via mdx view or native view, data can be sent to 'TM1', processes and chores can be executed, and cube and dimension metadata information can be taken.
Author: Muhammed Ali Onder
Maintainer: Muhammed Ali Onder <muhammedalionder@gmail.com>

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Package SKAT updated to version 2.0.1 with previous version 2.0.0 dated 2020-03-09

Title: SNP-Set (Sequence) Kernel Association Test
Description: Functions for kernel-regression-based association tests including Burden test, SKAT and SKAT-O. These methods aggregate individual SNP score statistics in a SNP set and efficiently compute SNP-set level p-values.
Author: Seunggeun (Shawn) Lee and Zhangchen Zhao, with contributions from Larisa Miropolsky and Michael Wu
Maintainer: Seunggeun (Shawn) Lee <lee7801@snu.ac.kr>

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Package mlr3oml updated to version 0.4.0 with previous version 0.3.0 dated 2020-10-05

Title: Connector Between 'mlr3' and 'OpenML'
Description: Provides an interface to 'OpenML.org' to list and download machine learning data and tasks. Data and tasks can be automatically converted to 'mlr3' tasks. For a more sophisticated interface which also allows uploading experiments, see the 'OpenML' package.
Author: Michel Lang [cre, aut] (<https://orcid.org/0000-0001-9754-0393>)
Maintainer: Michel Lang <michellang@gmail.com>

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Package chronosphere updated to version 0.4.0 with previous version 0.3.1 dated 2020-08-10

Title: Earth System History Variables
Description: The purpose of the 'chronosphere' project is to facilitate spatially explicit analyses of (paleo)environmental/ecological research. The package serves as a gateway to plate tectonic reconstructions, deep time global climate model results as well as fossil occurrence datasets such as the Paleobiology Database <https://paleobiodb.org/> and the PaleoReefs Database <https://www.paleo-reefs.pal.uni-erlangen.de/>. Environmental data stored on a remote server can be downloaded and imported directly to the R environment. Query functions to the GPlates <https://www.gplates.org/> desktop application or the GPlates Web Service <https://gws.gplates.org/> allow users to reconstruct coordinates, static plates, and Spatial objects. A wrapper class 'RasterArray' is implemented around the 'RasterLayer' class, allowing the organization of spatially explicit raster data in n-dimensional arrays. The project is developed under the umbrella of the DFG (Deutsche Forschungsgemeinschaft) Research Unit TERSANE2 (For 2332, TEmperature Related Stressors in ANcient Extinctions).
Author: Adam T. Kocsis, Nussaibah B. Raja
Maintainer: Adam T. Kocsis <adam.t.kocsis@gmail.com>

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More information about chronosphere at CRAN
Permanent link

Package SDAR updated to version 0.9-5 with previous version 0.9-3 dated 2019-10-24

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>

Diff between SDAR versions 0.9-3 dated 2019-10-24 and 0.9-5 dated 2020-10-20

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More information about SDAR at CRAN
Permanent link

Package RcppZiggurat updated to version 0.1.6 with previous version 0.1.5 dated 2018-06-10

Title: 'Rcpp' Integration of Different "Ziggurat" Normal RNG Implementations
Description: The Ziggurat generator for normally distributed random numbers, originally proposed by Marsaglia and Tsang (2000, <doi:10.18637/jss.v005.i08>) has been improved upon a few times starting with Leong et al (2005, <doi:10.18637/jss.v012.i07>). This package provides an aggregation in order to compare different implementations in order to provide an 'faster but good enough' alternative for use with R and C++ code.
Author: Dirk Eddelbuettel
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between RcppZiggurat versions 0.1.5 dated 2018-06-10 and 0.1.6 dated 2020-10-20

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 18 files changed, 235 insertions(+), 75 deletions(-)

More information about RcppZiggurat at CRAN
Permanent link

Package RcppArmadillo updated to version 0.10.1.0.0 with previous version 0.9.900.3.0 dated 2020-09-03

Title: 'Rcpp' Integration for the 'Armadillo' Templated Linear Algebra Library
Description: 'Armadillo' is a templated C++ linear algebra library (by Conrad Sanderson) that aims towards a good balance between speed and ease of use. Integer, floating point and complex numbers are supported, as well as a subset of trigonometric and statistics functions. Various matrix decompositions are provided through optional integration with LAPACK and ATLAS libraries. The 'RcppArmadillo' package includes the header files from the templated 'Armadillo' library. Thus users do not need to install 'Armadillo' itself in order to use 'RcppArmadillo'. From release 7.800.0 on, 'Armadillo' is licensed under Apache License 2; previous releases were under licensed as MPL 2.0 from version 3.800.0 onwards and LGPL-3 prior to that; 'RcppArmadillo' (the 'Rcpp' bindings/bridge to Armadillo) is licensed under the GNU GPL version 2 or later, as is the rest of 'Rcpp'. Note that Armadillo requires a fairly recent compiler; for the g++ family at least version 4.6.* is required.
Author: Dirk Eddelbuettel, Romain Francois, Doug Bates and Binxiang Ni
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between RcppArmadillo versions 0.9.900.3.0 dated 2020-09-03 and 0.10.1.0.0 dated 2020-10-20

 RcppArmadillo-0.10.1.0.0/RcppArmadillo/ChangeLog                                                 |   24 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/DESCRIPTION                                               |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/MD5                                                       |  517 ++---
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/README.md                                                 |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/configure                                                 |   18 
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 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo                                    |   56 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/Base_bones.hpp                |    3 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/Base_meat.hpp                 |   26 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/Col_bones.hpp                 |   22 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/Col_meat.hpp                  |  214 +-
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/CubeToMatOp_bones.hpp         |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/Cube_bones.hpp                |   39 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/Cube_meat.hpp                 |  433 ++--
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/GenCube_bones.hpp             |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/Gen_bones.hpp                 |   12 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/GlueCube_bones.hpp            |    5 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/Glue_bones.hpp                |   16 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/MapMat_bones.hpp              |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/MapMat_meat.hpp               |  142 -
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/Mat_bones.hpp                 |   85 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/Mat_meat.hpp                  |  888 +++++-----
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/OpCube_bones.hpp              |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/Op_bones.hpp                  |   16 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/Proxy.hpp                     |  780 ++++----
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 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/SpCol_bones.hpp               |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/SpCol_meat.hpp                |   14 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/SpGlue_bones.hpp              |    8 
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 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/SpMat_iterators_meat.hpp      |  263 +-
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/SpMat_meat.hpp                |  487 +++--
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/SpOp_bones.hpp                |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/SpProxy.hpp                   |  173 +
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/SpRow_bones.hpp               |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/SpRow_meat.hpp                |   10 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/SpSubview_bones.hpp           |  195 +-
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 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/SpToDOp_bones.hpp             |   17 
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 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/arma_static_check.hpp         |   46 
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 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/config.hpp                    |   45 
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 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/debug.hpp                     |   13 
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 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/diskio_bones.hpp              |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/diskio_meat.hpp               |  325 +--
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/eGlueCube_bones.hpp           |    8 
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 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/eOpCube_bones.hpp             |    8 
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 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/eglue_core_meat.hpp           |   22 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/eop_aux.hpp                   |   93 -
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/eop_core_bones.hpp            |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/eop_core_meat.hpp             |   22 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fft_engine.hpp                |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/field_bones.hpp               |   14 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/field_meat.hpp                |  401 ++--
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_approx_equal.hpp           |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_as_scalar.hpp              |    2 
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 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_conv.hpp                   |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_conv_to.hpp                |   44 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_det.hpp                    |   40 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_eig_gen.hpp                |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_eig_sym.hpp                |    2 
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 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_elem.hpp                   |   16 
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 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_find.hpp                   |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_hess.hpp                   |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_inplace_strans.hpp         |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_inplace_trans.hpp          |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_interp1.hpp                |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_interp2.hpp                |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_inv.hpp                    |  204 --
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_log_det.hpp                |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_log_normpdf.hpp            |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_lu.hpp                     |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_misc.hpp                   |   20 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_norm.hpp                   |   12 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_normalise.hpp              |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_normcdf.hpp                |  128 -
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_normpdf.hpp                |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_ones.hpp                   |   10 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_pinv.hpp                   |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_princomp.hpp               |   10 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_qr.hpp                     |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_qz.hpp                     |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_randg.hpp                  |  189 --
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_randi.hpp                  |   10 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_randn.hpp                  |   10 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_randu.hpp                  |   10 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_rank.hpp                   |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_reshape.hpp                |   52 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_schur.hpp                  |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_solve.hpp                  |  192 --
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_sort.hpp                   |   82 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_sort_index.hpp             |   48 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_speye.hpp                  |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_sprandn.hpp                |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_sprandu.hpp                |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_spsolve.hpp                |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_strans.hpp                 |   16 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_svd.hpp                    |   16 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_svds.hpp                   |   20 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_syl_lyap.hpp               |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_trans.hpp                  |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_zeros.hpp                  |   14 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_affmul_bones.hpp         |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_atan2_meat.hpp           |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_conv_bones.hpp           |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_cor_bones.hpp            |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_cov_bones.hpp            |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_cross_bones.hpp          |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_hist_bones.hpp           |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_histc_bones.hpp          |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_intersect_bones.hpp      |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_join_bones.hpp           |   12 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_kron_bones.hpp           |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_mixed_bones.hpp          |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_mvnrnd_bones.hpp         |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_polyfit_bones.hpp        |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_polyval_bones.hpp        |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_quantile_bones.hpp       |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_solve_bones.hpp          |   42 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_times_bones.hpp          |   16 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_trapz_bones.hpp          |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/gmm_diag_bones.hpp            |   12 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/gmm_diag_meat.hpp             |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/gmm_full_bones.hpp            |   12 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/gmm_full_meat.hpp             |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/hdf5_misc.hpp                 |  238 +-
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/injector_bones.hpp            |   30 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/injector_meat.hpp             |   23 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/memory.hpp                    |   66 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/mtGlueCube_bones.hpp          |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/mtGlue_bones.hpp              |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/mtOpCube_bones.hpp            |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/mtOp_bones.hpp                |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/mtSpGlue_bones.hpp            |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/mtSpOp_bones.hpp              |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/mul_gemm.hpp                  |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/mul_gemv.hpp                  |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/mul_herk.hpp                  |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_all_bones.hpp              |   10 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_any_bones.hpp              |   10 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_chi2rnd_bones.hpp          |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_chi2rnd_meat.hpp           |  101 -
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_diagmat_bones.hpp          |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_diagvec_bones.hpp          |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_expmat_meat.hpp            |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_find_bones.hpp             |   20 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_htrans_bones.hpp           |   37 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_htrans_meat.hpp            |   20 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_index_max_bones.hpp        |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_index_min_bones.hpp        |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_logmat_meat.hpp            |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_max_bones.hpp              |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_median_bones.hpp           |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_min_bones.hpp              |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_norm_bones.hpp             |   12 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_reshape_bones.hpp          |   12 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_reshape_meat.hpp           |  213 --
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_sort_meat.hpp              |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_sp_minus_meat.hpp          |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_strans_bones.hpp           |   12 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_trimat_bones.hpp           |   11 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_trimat_meat.hpp            |  232 --
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_wishrnd_meat.hpp           |  126 -
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/operator_div.hpp              |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/operator_relational.hpp       |   40 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/podarray_bones.hpp            |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/podarray_meat.hpp             |   29 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/promote_type.hpp              |   72 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/restrictors.hpp               |   20 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/running_stat_bones.hpp        |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/running_stat_vec_bones.hpp    |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/sp_auxlib_bones.hpp           |   87 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/sp_auxlib_meat.hpp            |  721 ++++++--
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/span.hpp                      |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spdiagview_bones.hpp          |   14 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spglue_join_bones.hpp         |   12 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spglue_kron_bones.hpp         |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spglue_max_meat.hpp           |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spglue_merge_meat.hpp         |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spglue_min_meat.hpp           |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spglue_minus_meat.hpp         |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spglue_plus_meat.hpp          |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spglue_relational_bones.hpp   |   28 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spglue_relational_meat.hpp    |  263 ++
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spglue_schur_meat.hpp         |   55 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spglue_times_bones.hpp        |   18 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spglue_times_meat.hpp         |    9 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spop_htrans_bones.hpp         |   10 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spop_max_bones.hpp            |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spop_max_meat.hpp             |   40 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spop_mean_meat.hpp            |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spop_min_bones.hpp            |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spop_min_meat.hpp             |   40 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spop_strans_bones.hpp         |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spop_var_bones.hpp            |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spop_var_meat.hpp             |   14 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/strip.hpp                     |   24 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/subview_bones.hpp             |   65 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/subview_cube_bones.hpp        |    9 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/subview_cube_each_bones.hpp   |   12 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/subview_cube_meat.hpp         |   86 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/subview_cube_slices_bones.hpp |   10 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/subview_each_bones.hpp        |   13 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/subview_elem1_bones.hpp       |   14 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/subview_elem2_bones.hpp       |   23 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/subview_elem2_meat.hpp        |  112 +
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/subview_field_bones.hpp       |    7 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/subview_meat.hpp              |  224 +-
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/traits.hpp                    |  494 ++---
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/translate_arpack.hpp          |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/translate_superlu.hpp         |  113 +
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/typedef_elem.hpp              |   28 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/typedef_elem_check.hpp        |   30 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/typedef_mat.hpp               |   22 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/unwrap.hpp                    |  704 +++----
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/unwrap_cube.hpp               |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/unwrap_spmat.hpp              |   10 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/wall_clock_bones.hpp          |   11 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/wall_clock_meat.hpp           |   62 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/xtrans_mat_bones.hpp          |   10 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/xvec_htrans_bones.hpp         |    8 
 RcppArmadillo-0.9.900.3.0/RcppArmadillo/inst/include/armadillo_bits/compiler_extra.hpp           |only
 RcppArmadillo-0.9.900.3.0/RcppArmadillo/inst/include/armadillo_bits/config.hpp.cmake             |only
 RcppArmadillo-0.9.900.3.0/RcppArmadillo/inst/include/armadillo_bits/spglue_elem_helper_bones.hpp |only
 RcppArmadillo-0.9.900.3.0/RcppArmadillo/inst/include/armadillo_bits/spglue_elem_helper_meat.hpp  |only
 263 files changed, 7174 insertions(+), 7486 deletions(-)

More information about RcppArmadillo at CRAN
Permanent link

Package glca updated to version 1.0.2 with previous version 1.0.1 dated 2020-09-08

Title: An R Package for Estimating a Group-Effect in Latent Class Analysis
Description: Fits latent class analysis (LCA) including group variable and covariates. The group variable can be handled either by multilevel LCA described in Vermunt (2003) <DOI:10.1111/j.0081-1750.2003.t01-1-00131.x> or standard LCA at each level of group variable. The covariates can be incorporated in the form of logistic regression (Bandeen-Roche et al. (1997) <DOI:10.1080/01621459.1997.10473658>).
Author: Youngsun Kim [aut, cre], Hwan Chung [aut]
Maintainer: Youngsun Kim <kim0sun@korea.ac.kr>

Diff between glca versions 1.0.1 dated 2020-09-08 and 1.0.2 dated 2020-10-20

 DESCRIPTION       |   15 +++++++++------
 MD5               |   22 +++++++++++++---------
 NEWS.md           |only
 R/dataset.r       |    3 ++-
 R/glca.gof.R      |    1 +
 R/glca_encode.R   |    4 ++--
 R/print.glca.R    |    6 +++---
 R/summary.glca.R  |   10 +++++-----
 build/partial.rdb |binary
 data/nyts18.rda   |binary
 inst              |only
 man/nyts18.Rd     |    6 ++----
 tests             |only
 13 files changed, 37 insertions(+), 30 deletions(-)

More information about glca at CRAN
Permanent link

Package BoSSA updated to version 3.7 with previous version 3.6 dated 2018-11-06

Title: A Bunch of Structure and Sequence Analysis
Description: Reads and plots phylogenetic placements.
Author: Pierre Lefeuvre
Maintainer: Pierre Lefeuvre <pierre.lefeuvre@cirad.fr>

Diff between BoSSA versions 3.6 dated 2018-11-06 and 3.7 dated 2020-10-20

 DESCRIPTION                  |    8 +-
 MD5                          |   30 +++----
 build/partial.rdb            |binary
 build/vignette.rds           |binary
 inst/doc/bossa-analysis.R    |   46 ++++++------
 inst/doc/bossa-analysis.Rmd  |   10 +-
 inst/doc/bossa-analysis.html |  164 +++++++++++++++++++++++++------------------
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Package survivalmodels updated to version 0.1.1 with previous version 0.1.0 dated 2020-10-15

Title: Models for Survival Analysis
Description: Implementations of classical and machine learning models for survival analysis, including deep neural networks via 'keras' and 'tensorflow'. Each model includes a separated fit and predict interface with consistent prediction types for predicting risk, survival probabilities, or survival distributions with 'distr6' <https://CRAN.R-project.org/package=distr6>. Models are either implemented from 'Python' via 'reticulate' <https://CRAN.R-project.org/package=reticulate>, from code in GitHub packages, or novel implementations using 'Rcpp' <https://CRAN.R-project.org/package=Rcpp>. Novel machine learning survival models wil be included in the package in near-future updates. Neural networks are implemented from the 'Python' package 'pycox' <https://github.com/havakv/pycox> and are detailed by Kvamme et al. (2019) <https://jmlr.org/papers/v20/18-424.html>. The 'Akritas' estimator is defined in Akritas (1994) <doi:10.1214/aos/1176325630>. 'DNNSurv' is defined in Zhao and Feng (2020) <arXiv:1908.02337>.
Author: Raphael Sonabend [aut, cre] (<https://orcid.org/0000-0001-9225-4654>)
Maintainer: Raphael Sonabend <raphael.sonabend.15@ucl.ac.uk>

Diff between survivalmodels versions 0.1.0 dated 2020-10-15 and 0.1.1 dated 2020-10-20

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Package sos updated to version 2.0-2 with previous version 2.0-0 dated 2017-07-03

Title: Search Contributed R Packages, Sort by Package
Description: Search contributed R packages, sort by package.
Author: Spencer Graves [cre, aut, cph], Sundar Dorai-Raj [aut], and Romain Francois [ctb]
Maintainer: Spencer Graves <spencer.graves@prodsyse.com>

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New package SimSurvNMarker with initial version 0.1.1
Package: SimSurvNMarker
Type: Package
Title: Simulate Survival Time and Markers
Version: 0.1.1
Authors@R: c(person("Benjamin", "Christoffersen", email = "boennecd@gmail.com", role = c("cre", "aut")), person("Mark", "Clements", role = "cph"), person("Ignace", "Bogaert", role = "cph"))
Maintainer: Benjamin Christoffersen <boennecd@gmail.com>
Description: Provides functions to simulate from joint survival and marker models. The user can specific all basis functions of time, random or deterministic covariates, random or deterministic left-truncation and right-censoring times, and model parameters.
License: GPL-2
Encoding: UTF-8
LazyData: true
Suggests: testthat (>= 2.1.0), splines, R.rsp, Matrix
RoxygenNote: 7.1.1
LinkingTo: Rcpp, RcppArmadillo
Imports: Rcpp
SystemRequirements: C++11
VignetteBuilder: R.rsp
NeedsCompilation: yes
Packaged: 2020-10-19 17:18:14 UTC; boennecd
Author: Benjamin Christoffersen [cre, aut], Mark Clements [cph], Ignace Bogaert [cph]
Repository: CRAN
Date/Publication: 2020-10-20 07:00:38 UTC

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New package PortalHacienda with initial version 0.1.5
Package: PortalHacienda
Type: Package
Title: Acceder Con R a Los Datos Del Portal De Hacienda
Version: 0.1.5
Authors@R: person("Fernando", "Garcia Diaz", email = "fmgarciadiaz78@gmail.com", role = c("aut", "cre"))
Description: Obtener listado de datos, acceder y extender series del Portal de Datos de Hacienda.Las proyecciones se realizan con 'forecast', Hyndman RJ, Khandakar Y (2008) <doi:10.18637/jss.v027.i03>. Search, download and forecast time-series from the Ministry of Economy of Argentina. Forecasts are built with the 'forecast' package, Hyndman RJ, Khandakar Y (2008) <doi:10.18637/jss.v027.i03>.
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/fmgarciadiaz/PortalHacienda-CRAN
Imports: dplyr (>= 0.8.5), forecast (>= 8.12), timetk (>= 2.0), lubridate (>= 1.7.8), xts (>= 0.12-0), httr, tibble (>= 3.0.1), magrittr (>= 1.5), zoo (>= 1.8-8), curl
RoxygenNote: 7.1.1
Depends: R (>= 3.6.0)
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-10-10 22:47:49 UTC; fernandogarciadiaz
Author: Fernando Garcia Diaz [aut, cre]
Maintainer: Fernando Garcia Diaz <fmgarciadiaz78@gmail.com>
Repository: CRAN
Date/Publication: 2020-10-20 07:00:41 UTC

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New package MixSIAR with initial version 3.1.12
Package: MixSIAR
Title: Bayesian Mixing Models in R
Version: 3.1.12
Authors@R: c( person("Brian", "Stock", email = "bstock09@gmail.com", role = c("cre","aut")), person("Brice", "Semmens", email = "semmens@ucsd.edu", role = "aut"), person("Eric", "Ward", role = "ctb"), person("Andrew", "Parnell", role = "ctb"), person("Andrew", "Jackson", role = "ctb"), person("Donald", "Phillips", role = "ctb"))
Description: Creates and runs Bayesian mixing models to analyze biological tracer data (i.e. stable isotopes, fatty acids), which estimate the proportions of source (prey) contributions to a mixture (consumer). 'MixSIAR' is not one model, but a framework that allows a user to create a mixing model based on their data structure and research questions, via options for fixed/ random effects, source data types, priors, and error terms. 'MixSIAR' incorporates several years of advances since 'MixSIR' and 'SIAR'.
Depends: R (>= 3.6.0)
Imports: ggplot2 (>= 3.3.0), R2jags (>= 0.5-7), MASS (>= 7.3), RColorBrewer (>= 1.1), reshape (>= 0.8.7), reshape2 (>= 1.4.3), lattice (>= 0.20-35), MCMCpack (>= 1.4-2), ggmcmc (>= 1.1), coda (>= 0.19-1), loo (>= 2.0.0), bayesplot (>= 1.4.0), splancs (>= 2.01-40)
Suggests: knitr, rmarkdown, testthat
SystemRequirements: JAGS (>= 4.3)
URL: https://github.com/brianstock/MixSIAR
BugReports: https://github.com/brianstock/MixSIAR/issues
Encoding: UTF-8
License: GPL-3
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-10-16 19:46:39 UTC; brian
Author: Brian Stock [cre, aut], Brice Semmens [aut], Eric Ward [ctb], Andrew Parnell [ctb], Andrew Jackson [ctb], Donald Phillips [ctb]
Maintainer: Brian Stock <bstock09@gmail.com>
Repository: CRAN
Date/Publication: 2020-10-20 07:00:44 UTC

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Package labeling updated to version 0.4.2 with previous version 0.3 dated 2014-08-23

Title: Axis Labeling
Description: Functions which provide a range of axis labeling algorithms.
Author: Justin Talbot,
Maintainer: Nuno Sempere <nuno.semperelh@gmail.com>

Diff between labeling versions 0.3 dated 2014-08-23 and 0.4.2 dated 2020-10-20

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Package hutilscpp updated to version 0.5.2 with previous version 0.5.1 dated 2020-10-13

Title: Miscellaneous Functions in C++
Description: Provides utility functions that are simply, frequently used, but may require higher performance that what can be obtained from base R. Incidentally provides support for 'reverse geocoding', such as matching a point with its nearest neighbour in another array. Used as a complement to package 'hutils' by sacrificing compilation or installation time for higher running speeds. The name is a portmanteau of the author and 'Rcpp'.
Author: Hugh Parsonage [aut, cre]
Maintainer: Hugh Parsonage <hugh.parsonage@gmail.com>

Diff between hutilscpp versions 0.5.1 dated 2020-10-13 and 0.5.2 dated 2020-10-20

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Package greybox updated to version 0.6.3 with previous version 0.6.2 dated 2020-09-02

Title: Toolbox for Model Building and Forecasting
Description: Implements functions and instruments for regression model building and its application to forecasting. The main scope of the package is in variables selection and models specification for cases of time series data. This includes promotional modelling, selection between different dynamic regressions with non-standard distributions of errors, selection based on cross validation, solutions to the fat regression model problem and more. Models developed in the package are tailored specifically for forecasting purposes. So as a results there are several methods that allow producing forecasts from these models and visualising them.
Author: Ivan Svetunkov [aut, cre] (Lecturer at Centre for Marketing Analytics and Forecasting, Lancaster University, UK), Yves R. Sagaert [ctb] (Visiting Research at Centre for Marketing Analytics and Forecasting, Lancaster University, UK)
Maintainer: Ivan Svetunkov <ivan@svetunkov.ru>

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New package eicm with initial version 1.0.1
Package: eicm
Version: 1.0.1
Date: 2020-10-02
Title: Explicit Interaction Community Models
Authors@R: c(person(given="Miguel", family="Porto", email="mpbertolo@gmail.com", comment = c(ORCID="0000-0001-7640-0623"), role=c("aut", "cre")), person(given="Pedro", family="Beja", comment = c(ORCID="0000-0001-8164-0760"), role="aut"))
Maintainer: Miguel Porto <mpbertolo@gmail.com>
Depends: R (>= 3.5.0)
Imports: methods, parallel, GA (>= 3.1.1), snow, doSNOW, iterators, pso, ucminf, foreach, graphics, optimParallel
Suggests: igraph, knitr, rmarkdown
VignetteBuilder: knitr
Description: Model fitting and species biotic interaction network topology selection for explicit interaction community models. Explicit interaction community models are an extension of binomial linear models for joint modelling of species communities, that incorporate both the effects of species biotic interactions and the effects of missing covariates. Species interactions are modelled as direct effects of each species on each of the others, and are estimated alongside the effects of missing covariates, modelled as latent factors. The package includes a penalized maximum likelihood fitting function, and a genetic algorithm for selecting the most parsimonious species interaction network topology.
License: GPL (>= 2)
Encoding: UTF-8
URL: https://github.com/miguel-porto/eicm
BugReports: https://github.com/miguel-porto/eicm
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2020-10-16 18:22:33 UTC; miguel
Author: Miguel Porto [aut, cre] (<https://orcid.org/0000-0001-7640-0623>), Pedro Beja [aut] (<https://orcid.org/0000-0001-8164-0760>)
Repository: CRAN
Date/Publication: 2020-10-20 07:00:20 UTC

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Package broom updated to version 0.7.2 with previous version 0.7.1 dated 2020-10-01

Title: Convert Statistical Objects into Tidy Tibbles
Description: Summarizes key information about statistical objects in tidy tibbles. This makes it easy to report results, create plots and consistently work with large numbers of models at once. Broom provides three verbs that each provide different types of information about a model. tidy() summarizes information about model components such as coefficients of a regression. glance() reports information about an entire model, such as goodness of fit measures like AIC and BIC. augment() adds information about individual observations to a dataset, such as fitted values or influence measures.
Author: David Robinson [aut], Alex Hayes [aut, cre] (<https://orcid.org/0000-0002-4985-5160>), Simon Couch [aut], Indrajeet Patil [ctb] (<https://orcid.org/0000-0003-1995-6531>), Derek Chiu [ctb], Matthieu Gomez [ctb], Boris Demeshev [ctb], Dieter Menne [ctb], Benjamin Nutter [ctb], Luke Johnston [ctb], Ben Bolker [ctb], Francois Briatte [ctb], Jeffrey Arnold [ctb], Jonah Gabry [ctb], Luciano Selzer [ctb], Gavin Simpson [ctb], Jens Preussner [ctb], Jay Hesselberth [ctb], Hadley Wickham [ctb], Matthew Lincoln [ctb], Alessandro Gasparini [ctb], Lukasz Komsta [ctb], Frederick Novometsky [ctb], Wilson Freitas [ctb], Michelle Evans [ctb], Jason Cory Brunson [ctb], Simon Jackson [ctb], Ben Whalley [ctb], Karissa Whiting [ctb], Yves Rosseel [ctb], Michael Kuehn [ctb], Jorge Cimentada [ctb], Erle Holgersen [ctb], Karl Dunkle Werner [ctb] (<https://orcid.org/0000-0003-0523-7309>), Ethan Christensen [ctb], Steven Pav [ctb], Paul PJ [ctb], Ben Schneider [ctb], Patrick Kennedy [ctb], Lily Medina [ctb], Brian Fannin [ctb], Jason Muhlenkamp [ctb], Matt Lehman [ctb], Bill Denney [ctb] (<https://orcid.org/0000-0002-5759-428X>), Nic Crane [ctb], Andrew Bates [ctb], Vincent Arel-Bundock [ctb] (<https://orcid.org/0000-0003-2042-7063>), Hideaki Hayashi [ctb], Luis Tobalina [ctb], Annie Wang [ctb], Wei Yang Tham [ctb], Clara Wang [ctb], Abby Smith [ctb] (<https://orcid.org/0000-0002-3207-0375>), Jasper Cooper [ctb] (<https://orcid.org/0000-0002-8639-3188>), E Auden Krauska [ctb] (<https://orcid.org/0000-0002-1466-5850>), Alex Wang [ctb], Malcolm Barrett [ctb] (<https://orcid.org/0000-0003-0299-5825>), Charles Gray [ctb] (<https://orcid.org/0000-0002-9978-011X>), Jared Wilber [ctb], Vilmantas Gegzna [ctb] (<https://orcid.org/0000-0002-9500-5167>), Eduard Szoecs [ctb], Frederik Aust [ctb] (<https://orcid.org/0000-0003-4900-788X>), Angus Moore [ctb], Nick Williams [ctb], Marius Barth [ctb] (<https://orcid.org/0000-0002-3421-6665>), Bruna Wundervald [ctb] (<https://orcid.org/0000-0001-8163-220X>), Joyce Cahoon [ctb] (<https://orcid.org/0000-0001-7217-4702>), Grant McDermott [ctb] (<https://orcid.org/0000-0001-7883-8573>), Kevin Zarca [ctb], Shiro Kuriwaki [ctb] (<https://orcid.org/0000-0002-5687-2647>), Lukas Wallrich [ctb] (<https://orcid.org/0000-0003-2121-5177>), James Martherus [ctb] (<https://orcid.org/0000-0002-8285-3300>), Chuliang Xiao [ctb] (<https://orcid.org/0000-0002-8466-9398>), Joseph Larmarange [ctb], Max Kuhn [ctb], Michal Bojanowski [ctb], Hakon Malmedal [ctb], Clara Wang [ctb], Sergio Oller [ctb], Luke Sonnet [ctb], Jim Hester [ctb], Cory Brunson [ctb], Ben Schneider [ctb], Bernie Gray [ctb] (<https://orcid.org/0000-0001-9190-6032>), Mara Averick [ctb], Aaron Jacobs [ctb], Andreas Bender [ctb], Sven Templer [ctb], Paul-Christian Buerkner [ctb], Matthew Kay [ctb], Erwan Le Pennec [ctb], Johan Junkka [ctb], Hao Zhu [ctb], Benjamin Soltoff [ctb], Zoe Wilkinson Saldana [ctb], Tyler Littlefield [ctb], Charles T. Gray [ctb], Shabbh E. Banks [ctb], Serina Robinson [ctb], Roger Bivand [ctb], Riinu Ots [ctb], Nicholas Williams [ctb], Nina Jakobsen [ctb], Michael Weylandt [ctb], Lisa Lendway [ctb], Karl Hailperin [ctb], Josue Rodriguez [ctb], Jenny Bryan [ctb], Chris Jarvis [ctb], Greg Macfarlane [ctb], Brian Mannakee [ctb], Drew Tyre [ctb], Shreyas Singh [ctb], Laurens Geffert [ctb], Hong Ooi [ctb], Henrik Bengtsson [ctb], Eduard Szocs [ctb], David Hugh-Jones [ctb], Matthieu Stigler [ctb], Hugo Tavares [ctb] (<https://orcid.org/0000-0001-9373-2726>), R. Willem Vervoort [ctb], Brenton M. Wiernik [ctb]
Maintainer: Alex Hayes <alexpghayes@gmail.com>

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Package SSDforR updated to version 1.5.19 with previous version 1.5.18 dated 2020-09-16

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>

Diff between SSDforR versions 1.5.18 dated 2020-09-16 and 1.5.19 dated 2020-10-20

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Package deepgmm updated to version 0.1.62 with previous version 0.1.59 dated 2019-12-16

Title: Deep Gaussian Mixture Models
Description: Deep Gaussian mixture models as proposed by Viroli and McLachlan (2019) <doi:10.1007/s11222-017-9793-z> provide a generalization of classical Gaussian mixtures to multiple layers. Each layer contains a set of latent variables that follow a mixture of Gaussian distributions. To avoid overparameterized solutions, dimension reduction is applied at each layer by way of factor models.
Author: Cinzia Viroli, Geoffrey J. McLachlan
Maintainer: Suren Rathnayake <surenr@gmail.com>

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Package winch (with last version 0.0.1) was removed from CRAN

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

2020-10-05 0.0.1

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Package GGMncv (with last version 1.1.0) was removed from CRAN

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

2020-07-11 1.1.0
2020-07-06 1.0.0

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Package hereR updated to version 0.5.1 with previous version 0.5.0 dated 2020-09-18

Title: 'sf'-Based Interface to the 'HERE' REST APIs
Description: Interface to the 'HERE' REST APIs <https://developer.here.com/develop/rest-apis>: (1) geocode and autosuggest addresses or reverse geocode POIs using the 'Geocoder' API; (2) route directions, travel distance or time matrices and isolines using the 'Routing' API; (3) request real-time traffic flow and incident information from the 'Traffic' API; (4) find request public transport connections and nearby stations from the 'Public Transit' API; (5) request intermodal routes using the 'Intermodal Routing' API; (6) get weather forecasts, reports on current weather conditions, astronomical information and alerts at a specific location from the 'Destination Weather' API. Locations, routes and isolines are returned as 'sf' objects.
Author: Merlin Unterfinger [aut, cre] (<https://orcid.org/0000-0003-2020-2366>), Daniel Possenriede [ctb] (<https://orcid.org/0000-0002-6738-9845>)
Maintainer: Merlin Unterfinger <info@munterfinger.ch>

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

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

2020-05-22 0.1.1

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Package btergm (with last version 1.9.9) was removed from CRAN

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

2020-06-18 1.9.9
2020-04-07 1.9.7

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