Thu, 27 Jun 2024

Package CWT updated to version 0.2.1 with previous version 0.1.1 dated 2024-05-28

Title: Continuous Wavelet Transformation for Spectroscopy
Description: Fast application of Continuous Wavelet Transformation ('CWT') on time series with special attention to spectroscopy. It is written using data.table and 'C++' language and in some functions it is possible to use parallel processing to speed-up the computation over samples. Currently, only the second derivative of a Gaussian wavelet function is implemented.
Author: J. Antonio Guzman Q. [cre, aut, cph]
Maintainer: J. Antonio Guzman Q. <antguz06@gmail.com>

Diff between CWT versions 0.1.1 dated 2024-05-28 and 0.2.1 dated 2024-06-27

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 15 files changed, 58 insertions(+), 26 deletions(-)

More information about CWT at CRAN
Permanent link

Package ggpmisc updated to version 0.6.0 with previous version 0.5.6 dated 2024-05-07

Title: Miscellaneous Extensions to 'ggplot2'
Description: Extensions to 'ggplot2' respecting the grammar of graphics paradigm. Statistics: locate and tag peaks and valleys; label plot with the equation of a fitted polynomial or other types of models; labels with P-value, R^2 or adjusted R^2 or information criteria for fitted models; label with ANOVA table for fitted models; label with summary for fitted models. Model fit classes for which suitable methods are provided by package 'broom' and 'broom.mixed' are supported. Scales and stats to build volcano and quadrant plots based on outcomes, fold changes, p-values and false discovery rates.
Author: Pedro J. Aphalo [aut, cre] , Kamil Slowikowski [ctb] , Samer Mouksassi [ctb]
Maintainer: Pedro J. Aphalo <pedro.aphalo@helsinki.fi>

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More information about ggpmisc at CRAN
Permanent link

Package dartR.popgen updated to version 1.0.0 with previous version 0.32 dated 2023-11-21

Title: Analysing 'SNP' and 'Silicodart' Data Generated by Genome-Wide Restriction Fragment Analysis
Description: Facilitates the analysis of SNP (single nucleotide polymorphism) and silicodart (presence/absence) data. 'dartR.popgen' provides a suit of functions to analyse such data in a population genetics context. It provides several functions to calculate population genetic metrics and to study population structure. Quite a few functions need additional software to be able to run (gl.run.structure(), gl.blast(), gl.LDNe()). You find detailed description in the help pages how to download and link the packages so the function can run the software. 'dartR.popgen' is part of the the 'dartRverse' suit of packages. Gruber et al. (2018) <doi:10.1111/1755-0998.12745>. Mijangos et al. (2022) <doi:10.1111/2041-210X.13918>.
Author: Bernd Gruber [aut, cre], Arthur Georges [aut], Jose L. Mijangos [aut], Carlo Pacioni [aut], Peter J. Unmack [ctb], Oliver Berry [ctb], Lindsay V. Clark [ctb], Floriaan Devloo-Delva [ctb], Eric Archer [ctb]
Maintainer: Bernd Gruber <bernd.gruber@canberra.edu.au>

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More information about dartR.popgen at CRAN
Permanent link

Package mpath updated to version 0.4-2.26 with previous version 0.4-2.25 dated 2024-03-09

Title: Regularized Linear Models
Description: Algorithms compute robust estimators for loss functions in the concave convex (CC) family by the iteratively reweighted convex optimization (IRCO), an extension of the iteratively reweighted least squares (IRLS). The IRCO reduces the weight of the observation that leads to a large loss; it also provides weights to help identify outliers. Applications include robust (penalized) generalized linear models and robust support vector machines. The package also contains penalized Poisson, negative binomial, zero-inflated Poisson, zero-inflated negative binomial regression models and robust models with non-convex loss functions. Wang et al. (2014) <doi:10.1002/sim.6314>, Wang et al. (2015) <doi:10.1002/bimj.201400143>, Wang et al. (2016) <doi:10.1177/0962280214530608>, Wang (2021) <doi:10.1007/s11749-021-00770-2>, Wang (2024) <doi:10.1111/anzs.12409>.
Author: Zhu Wang, with contributions from Achim Zeileis, Simon Jackman, Brian Ripley, and Patrick Breheny
Maintainer: Zhu Wang <zwang145@uthsc.edu>

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Permanent link

Package fields updated to version 16.2 with previous version 15.2 dated 2023-08-17

Title: Tools for Spatial Data
Description: For curve, surface and function fitting with an emphasis on splines, spatial data, geostatistics, and spatial statistics. The major methods include cubic, and thin plate splines, Kriging, and compactly supported covariance functions for large data sets. The splines and Kriging methods are supported by functions that can determine the smoothing parameter (nugget and sill variance) and other covariance function parameters by cross validation and also by restricted maximum likelihood. For Kriging there is an easy to use function that also estimates the correlation scale (range parameter). A major feature is that any covariance function implemented in R and following a simple format can be used for spatial prediction. There are also many useful functions for plotting and working with spatial data as images. This package also contains an implementation of sparse matrix methods for large spatial data sets and currently requires the sparse matrix (spam) package. Use help(fields) to get star [...truncated...]
Author: Douglas Nychka [aut, cre], Reinhard Furrer [aut], John Paige [aut], Stephan Sain [aut], Florian Gerber [aut], Matthew Iverson [aut], Rider Johnson [aut]
Maintainer: Douglas Nychka <douglasnychka@gmail.com>

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More information about fields at CRAN
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Package rpmodel updated to version 1.2.3 with previous version 1.2.0 dated 2021-06-09

Title: P-Model
Description: Implements the P-model (Stocker et al., 2020 <doi:10.5194/gmd-13-1545-2020>), predicting acclimated parameters of the enzyme kinetics of C3 photosynthesis, assimilation, and dark respiration rates as a function of the environment (temperature, CO2, vapour pressure deficit, light, atmospheric pressure).
Author: Benjamin Stocker [aut, cre] , Koen Hufkens [ctb]
Maintainer: Benjamin Stocker <benjamin.stocker@gmail.com>

Diff between rpmodel versions 1.2.0 dated 2021-06-09 and 1.2.3 dated 2024-06-27

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Package waywiser updated to version 0.6.0 with previous version 0.5.1 dated 2023-10-31

Title: Ergonomic Methods for Assessing Spatial Models
Description: Assessing predictive models of spatial data can be challenging, both because these models are typically built for extrapolating outside the original region represented by training data and due to potential spatially structured errors, with "hot spots" of higher than expected error clustered geographically due to spatial structure in the underlying data. Methods are provided for assessing models fit to spatial data, including approaches for measuring the spatial structure of model errors, assessing model predictions at multiple spatial scales, and evaluating where predictions can be made safely. Methods are particularly useful for models fit using the 'tidymodels' framework. Methods include Moran's I ('Moran' (1950) <doi:10.2307/2332142>), Geary's C ('Geary' (1954) <doi:10.2307/2986645>), Getis-Ord's G ('Ord' and 'Getis' (1995) <doi:10.1111/j.1538-4632.1995.tb00912.x>), agreement coefficients from 'Ji' and Gallo (2006) (<doi: 10.14358/PERS.72.7.823>), agreement m [...truncated...]
Author: Michael Mahoney [aut, cre] , Lucas Johnson [ctb] , Virgilio Gomez-Rubio [rev] for rOpenSci, see <https://github.com/ropensci/software-review/issues/571>), Jakub Nowosad [rev] for rOpenSci, see <https://github.com/ropensci/software-review/issues/571 [...truncated...]
Maintainer: Michael Mahoney <mike.mahoney.218@gmail.com>

Diff between waywiser versions 0.5.1 dated 2023-10-31 and 0.6.0 dated 2024-06-27

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Package rsi updated to version 0.2.1 with previous version 0.2.0 dated 2024-03-29

Title: Efficiently Retrieve and Process Satellite Imagery
Description: Downloads spatial data from spatiotemporal asset catalogs ('STAC'), computes standard spectral indices from the Awesome Spectral Indices project (Montero et al. (2023) <doi:10.1038/s41597-023-02096-0>) against raster data, and glues the outputs together into predictor bricks. Methods focus on interoperability with the broader spatial ecosystem; function arguments and outputs use classes from 'sf' and 'terra', and data downloading functions support complex 'CQL2' queries using 'rstac'.
Author: Michael Mahoney [aut, cre] , Permian Global [cph, fnd]
Maintainer: Michael Mahoney <mike.mahoney.218@gmail.com>

Diff between rsi versions 0.2.0 dated 2024-03-29 and 0.2.1 dated 2024-06-27

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Package zoltr updated to version 1.0.1 with previous version 0.5.1 dated 2020-04-14

Title: Interface to the 'Zoltar' Forecast Repository API
Description: 'Zoltar' <https://www.zoltardata.com/> is a website that provides a repository of model forecast results in a standardized format and a central location. It supports storing, retrieving, comparing, and analyzing time series forecasts for prediction challenges of interest to the modeling community. This package provides functions for working with the 'Zoltar' API, including connecting and authenticating, getting meta information (projects, models, and forecasts, and truth), and uploading, downloading, and deleting forecast and truth data.
Author: Matthew Cornell [aut, cre], Nicholas Reich [aut, cph]
Maintainer: Matthew Cornell <cornell@umass.edu>

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Package PeakSegJoint updated to version 2024.6.27 with previous version 2024.1.24 dated 2024-01-24

Title: Joint Peak Detection in Several ChIP-Seq Samples
Description: Jointly segment several ChIP-seq samples to find the peaks which are the same and different across samples. The fast approximate maximum Poisson likelihood algorithm is described in "PeakSegJoint: fast supervised peak detection via joint segmentation of multiple count data samples" <doi:10.48550/arXiv.1506.01286> by TD Hocking and G Bourque.
Author: Toby Dylan Hocking
Maintainer: Toby Dylan Hocking <toby.hocking@r-project.org>

Diff between PeakSegJoint versions 2024.1.24 dated 2024-01-24 and 2024.6.27 dated 2024-06-27

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Package OlinkAnalyze updated to version 3.8.2 with previous version 3.7.0 dated 2024-02-22

Title: Facilitate Analysis of Proteomic Data from Olink
Description: A collection of functions to facilitate analysis of proteomic data from Olink, primarily NPX data that has been exported from Olink Software. The functions also work on QUANT data from Olink by log- transforming the QUANT data. The functions are focused on reading data, facilitating data wrangling and quality control analysis, performing statistical analysis and generating figures to visualize the results of the statistical analysis. The goal of this package is to help users extract biological insights from proteomic data run on the Olink platform.
Author: Kathleen Nevola [aut, cre] , Marianne Sandin [aut] , Jamey Guess [aut] , Simon Forsberg [aut] , Christoffer Cambronero [aut] , Pascal Pucholt [aut] , Boxi Zhang [aut] , Masoumeh Sheikhi [aut] , Klev Diamanti [aut] , Amrita Kar [aut] , Lei Conze [aut] [...truncated...]
Maintainer: Kathleen Nevola <biostattools@olink.com>

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Package ecce updated to version 3.0.2 with previous version 3.0.1 dated 2024-05-17

Title: Translate English Sentence into Chinese, or Translate Chinese Sentence into English
Description: If translate English or Chinese sentence, there is a faster way for R user. You can pass in an English or Chinese sentence, ecce package support both English and Chinese translation. It also support browse translation results in website. In addition, also support obtain the pinyin of the Chinese character, you can more easily understand the pronunciation of the Chinese character.
Author: Xinyuan Chu [aut, cre]
Maintainer: Xinyuan Chu <chuxinyuan@outlook.com>

Diff between ecce versions 3.0.1 dated 2024-05-17 and 3.0.2 dated 2024-06-27

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Package BRBVS updated to version 0.2.1 with previous version 0.1.1 dated 2024-01-09

Title: Variable Selection and Ranking in Copula Survival Models Affected by General Censoring Scheme
Description: Performs variable selection and ranking based on several measures for the class of copula survival model(s) in high dimensional domain. The package is based on the class of copula survival model(s) implemented in the 'GJRM' package.
Author: Danilo Petti [aut, cre, cph] , Marcella Niglio [aut] , Marialuisa Restaino [aut]
Maintainer: Danilo Petti <d.petti@essex.ac.uk>

Diff between BRBVS versions 0.1.1 dated 2024-01-09 and 0.2.1 dated 2024-06-27

 DESCRIPTION                      |   23 ++++++++++++++---------
 MD5                              |   12 +++++++++---
 NAMESPACE                        |    3 +++
 R/BackwardSelectionBivCop.R      |only
 R/ForwardSelectionBivCop.R       |only
 R/LinkFunction_Selection.R       |only
 inst/CITATION                    |   17 +++++++++++------
 man/Select_link_BivCop.Rd        |only
 man/backward_selection_BivCop.Rd |only
 man/forward_selection_BivCop.Rd  |only
 10 files changed, 37 insertions(+), 18 deletions(-)

More information about BRBVS at CRAN
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Package WASP (with last version 1.4.3) was removed from CRAN

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

2022-08-22 1.4.3
2022-02-21 1.4.2
2021-09-02 1.4.1
2021-08-23 1.4.0

Permanent link
Package FAIRmaterials updated to version 0.4.2.1 with previous version 0.4.2 dated 2024-06-24

Title: Ontology Tools with Data FAIRification in Development
Description: Translates several CSV files with ontological terms and corresponding data into RDF triples. These RDF triples are stored in OWL and JSON-LD files, facilitating data accessibility, interoperability, and knowledge unification. The triples are also visualized in a graph saved as an SVG. The input CSVs must be formatted with a template from a public Google Sheet; see README or vignette for more information. This is a tool is used by the SDLE Research Center at Case Western Reserve University to create and visualize material science ontologies, and it includes example ontologies to demonstrate its capabilities. This work was supported by the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) under Solar Energy Technologies Office (SETO) Agreement Numbers E-EE0009353 and DE-EE0009347, Department of Energy (National Nuclear Security Administration) under Award Number DE-NA0004104 and Contract number B647887, and U.S. National Science Foundation Award under Aw [...truncated...]
Author: Jonathan E Gordon [aut] , Alexander Harding Bradley [aut] , Priyan Rajamohan [aut] , Nathaniel Hahn [aut], Kiefer Lin [aut], Arafath Nihar [aut] , Hayden Cadwell [aut], Jiana Kambo [aut], Jayvic Jimenez [aut] , Kristen J Hernandez [aut] , Hein Htet-A [...truncated...]
Maintainer: Roger H French <roger.french@case.edu>

Diff between FAIRmaterials versions 0.4.2 dated 2024-06-24 and 0.4.2.1 dated 2024-06-27

 DESCRIPTION                                  |    8 -
 MD5                                          |   25 +--
 R/extra_functions.R                          |    1 
 R/process_ontology_files.R                   |   26 ++-
 inst/WORDLIST                                |    1 
 inst/doc/FAIRmaterials.R                     |   12 +
 inst/doc/FAIRmaterials.Rmd                   |   18 ++
 inst/doc/FAIRmaterials.html                  |   58 ++++----
 inst/extdata/FAIRSheetTemplatesZIP.zip       |only
 inst/extdata/PV/ontology_data-output.ttl     |    1 
 inst/extdata/XRay/ontology_data-output.ttl   |    1 
 man/process_ontology_files.Rd                |   26 ++-
 tests/testthat/test-process_ontology_files.R |  186 +++++++++++++++++++++++++--
 vignettes/FAIRmaterials.Rmd                  |   18 ++
 14 files changed, 299 insertions(+), 82 deletions(-)

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Package SPARTAAS updated to version 1.2.4 with previous version 1.2.1 dated 2023-06-06

Title: Statistical Pattern Recognition and daTing using Archaeological Artefacts assemblageS
Description: Statistical pattern recognition and dating using archaeological artefacts assemblages. Package of statistical tools for archaeology. hclustcompro()/perioclust(): Bellanger Lise, Coulon Arthur, Husi Philippe (2021, ISBN:978-3-030-60103-4). mapclust(): Bellanger Lise, Coulon Arthur, Husi Philippe (2021) <doi:10.1016/j.jas.2021.105431>. seriograph(): Desachy Bruno (2004) <doi:10.3406/pica.2004.2396>. cerardat(): Bellanger Lise, Husi Philippe (2012) <doi:10.1016/j.jas.2011.06.031>.
Author: Arthur Coulon [aut, cre], Lise Bellanger [aut], Philippe Husi [aut], Bruno Desachy [ctb], Benjamin Martineau [ctb]
Maintainer: Arthur Coulon <arthur-coulon@outlook.fr>

Diff between SPARTAAS versions 1.2.1 dated 2023-06-06 and 1.2.4 dated 2024-06-27

 DESCRIPTION                                      |   20 -
 MD5                                              |   41 +--
 NAMESPACE                                        |    6 
 R/cerardat.R                                     |  248 +++++++++++++++--------
 R/perioclust.R                                   |    2 
 R/util.R                                         |    4 
 build/partial.rdb                                |binary
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 inst/shiny-examples/serio.app/ui.R               |   31 ++
 inst/shiny-examples/serio.app/www/GS/exemple.png |only
 man/SPARTAAS-package.Rd                          |    2 
 man/cerardat.Rd                                  |    4 
 man/cerardat_estim_nf.Rd                         |    2 
 man/datarcheo.Rd                                 |    2 
 man/extract_results.Rd                           |   11 -
 man/hclustcompro.Rd                              |    2 
 man/plot.cerardat_obj.Rd                         |    4 
 22 files changed, 380 insertions(+), 193 deletions(-)

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New package simpletex with initial version 1.0.3
Package: simpletex
Title: Mathematical Formulas and Character Recognition
Version: 1.0.3
Maintainer: Xinyuan Chu <chuxinyuan@outlook.com>
Date: 2024-06-26 12:29:14 UTC
Description: By calling the 'SimpleTex' <https://simpletex.cn/> open API implements text and mathematical formula recognition on the image, and the output formula can be used directly with 'Markdown' and 'LaTeX'.
License: MIT + file LICENSE
URL: https://gitlab.com/chuxinyuan/simpletex
BugReports: https://gitlab.com/chuxinyuan/simpletex/-/issues
Depends: R (>= 3.6)
Imports: glue, digest, httr, jsonlite
Suggests: testthat (>= 2.1.0), knitr, rmarkdown
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2024-06-26 12:33:33 UTC; cxy
Author: Xinyuan Chu [aut, cre]
Repository: CRAN
Date/Publication: 2024-06-27 14:30:02 UTC

More information about simpletex at CRAN
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New package scorematchingad with initial version 0.0.64
Package: scorematchingad
Title: Score Matching Estimation by Automatic Differentiation
Version: 0.0.64
Description: Hyvärinen's score matching (Hyvärinen, 2005) <https://jmlr.org/papers/v6/hyvarinen05a.html> is a useful estimation technique when the normalising constant for a probability distribution is difficult to compute. This package implements score matching estimators using automatic differentiation in the 'CppAD' library <https://github.com/coin-or/CppAD> and is designed for quickly implementing score matching estimators for new models. Also available is general robustification (Windham, 1995) <https://www.jstor.org/stable/2346159>. Already in the package are estimators for directional distributions (Mardia, Kent and Laha, 2016) <doi:10.48550/arXiv.1604.08470> and the flexible Polynomially-Tilted Pairwise Interaction model for compositional data. The latter estimators perform well when there are zeros in the compositions (Scealy and Wood, 2023) <doi:10.1080/01621459.2021.2016422>, even many zeros (Scealy, Hingee, Kent, and Wood, 2024) <doi:10.1007/s11222-024-1 [...truncated...]
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Suggests: testthat, ks, movMF, cubature, simdd, numDeriv
Enhances: RcppEigen (>= 0.3.3.7), RcppXPtrUtils
Depends: R (>= 3.5.0)
Imports: MCMCpack, optimx, FixedPoint, Rdpack, Rcpp (>= 1.0.9), methods, stats, R6, utils, rlang, ellipsis
LinkingTo: Rcpp (>= 1.0.9), RcppEigen (>= 0.3.3.7)
NeedsCompilation: yes
Packaged: 2024-06-26 04:38:51 UTC; kassel
Author: Kassel Liam Hingee [aut, cre] , Janice Scealy [aut] , Bradley M. Bell [cph]
Maintainer: Kassel Liam Hingee <kassel.hingee@anu.edu.au>
Repository: CRAN
Date/Publication: 2024-06-27 14:40:03 UTC

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Package roads updated to version 1.2.0 with previous version 1.1.1 dated 2023-06-24

Title: Road Network Projection
Description: Iterative least cost path and minimum spanning tree methods for projecting forest road networks. The methods connect a set of target points to an existing road network using 'igraph' <https://igraph.org> to identify least cost routes. The cost of constructing a road segment between adjacent pixels is determined by a user supplied weight raster and a weight function; options include the average of adjacent weight raster values, and a function of the elevation differences between adjacent cells that penalizes steep grades. These road network projection methods are intended for integration into R workflows and modelling frameworks used for forecasting forest change, and can be applied over multiple time-steps without rebuilding a graph at each time-step.
Author: Sarah Endicott [aut, cre] , Kyle Lochhead [aut], Josie Hughes [aut], Patrick Kirby [aut], Her Majesty the Queen in Right of Canada as represented by the Minister of the Environment [cph] , Province of British Columbia [cph]
Maintainer: Sarah Endicott <sarah.endicott@ec.gc.ca>

Diff between roads versions 1.1.1 dated 2023-06-24 and 1.2.0 dated 2024-06-27

 roads-1.1.1/roads/build/partial.rdb                              |only
 roads-1.2.0/roads/DESCRIPTION                                    |   43 
 roads-1.2.0/roads/MD5                                            |  105 -
 roads-1.2.0/roads/NAMESPACE                                      |    2 
 roads-1.2.0/roads/NEWS.md                                        |   14 
 roads-1.2.0/roads/R/CLUSexample.R                                |   71 
 roads-1.2.0/roads/R/buildSimList.R                               |  436 ++---
 roads-1.2.0/roads/R/buildSnapRoads.R                             |    6 
 roads-1.2.0/roads/R/dem_example.R                                |only
 roads-1.2.0/roads/R/demoScen.R                                   |   95 -
 roads-1.2.0/roads/R/getClosestRoad.R                             |    4 
 roads-1.2.0/roads/R/getDistFromSource.R                          |  379 ++--
 roads-1.2.0/roads/R/getGraph.R                                   |  315 ++-
 roads-1.2.0/roads/R/getLandingsFromTarget.R                      |  715 ++++----
 roads-1.2.0/roads/R/lcpList.R                                    |    6 
 roads-1.2.0/roads/R/mstList.R                                    |  136 -
 roads-1.2.0/roads/R/pathsToLines.R                               |  121 -
 roads-1.2.0/roads/R/plotRoads.R                                  |  116 -
 roads-1.2.0/roads/R/prepExData.R                                 |   34 
 roads-1.2.0/roads/R/projectRoads.R                               |  789 +++++----
 roads-1.2.0/roads/R/rasterToLineSegments.R                       |  320 +--
 roads-1.2.0/roads/R/rasterizeLine.R                              |   95 -
 roads-1.2.0/roads/R/shortestPaths.R                              |  186 +-
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 roads-1.2.0/roads/README.md                                      |   42 
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 roads-1.2.0/roads/man/plotRoads.Rd                               |   10 
 roads-1.2.0/roads/man/prepExData.Rd                              |    8 
 roads-1.2.0/roads/man/projectRoads.Rd                            |  413 ++---
 roads-1.2.0/roads/man/rasterToLineSegments.Rd                    |    5 
 roads-1.2.0/roads/man/rasterizeLine.Rd                           |    3 
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 roads-1.2.0/roads/tests/testthat/test-getLandingsFromTarget.R    |  293 +--
 roads-1.2.0/roads/tests/testthat/test-projectRoads.R             |  311 ++-
 roads-1.2.0/roads/tests/testthat/test-projectRoads_CLUSexample.R |   31 
 roads-1.2.0/roads/vignettes/ReconstructRoadHistory.Rmd           |    6 
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 60 files changed, 4024 insertions(+), 3755 deletions(-)

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New package mlts with initial version 1.0.0
Package: mlts
Title: Multilevel Latent Time Series Models with 'R' and 'Stan'
Version: 1.0.0
Description: Fit multilevel manifest or latent time-series models, including popular Dynamic Structural Equation Models (DSEM). The models can be set up and modified with user-friendly functions and are fit to the data using 'Stan' for Bayesian inference. Path models and formulas for user-defined models can be easily created with functions using 'knitr'. Asparouhov, Hamaker, & Muthen (2018) <doi:10.1080/10705511.2017.1406803>.
License: GPL (>= 3)
Encoding: UTF-8
URL: https://github.com/munchfab/mlts
BugReports: https://github.com/munchfab/mlts/issues
Imports: cowplot, dplyr (>= 1.1.3), ggplot2, methods, mvtnorm, pdftools, Rcpp (>= 0.12.0), RcppParallel (>= 5.0.1), rlang, rmarkdown, rstan (>= 2.32.3), rstantools (>= 2.4.0), stats
Suggests: knitr, testthat (>= 3.0.0)
Biarch: true
Depends: R (>= 3.5.0)
LinkingTo: BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.3.0), RcppParallel (>= 5.0.1), rstan (>= 2.18.1), StanHeaders (>= 2.18.0)
SystemRequirements: GNU make
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: yes
Packaged: 2024-06-26 10:25:36 UTC; fabi
Author: Kenneth Koslowski [aut, cre, cph] , Fabian Muench [aut] , Tobias Koch [aut] , Jana Holtmann [aut]
Maintainer: Kenneth Koslowski <kenneth.koslowski@uni-leipzig.de>
Repository: CRAN
Date/Publication: 2024-06-27 14:20:02 UTC

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Package lme4breeding updated to version 1.0.22 with previous version 1.0.21 dated 2024-06-25

Title: Relationship-Based Mixed-Effects Models
Description: Fit relationship-based and customized mixed-effects models with complex variance-covariance structures using the 'lme4' machinery. The core computational algorithms are implemented using the 'Eigen' 'C++' library for numerical linear algebra and 'RcppEigen' 'glue'.
Author: Giovanny Covarrubias-Pazaran [aut, cre]
Maintainer: Giovanny Covarrubias-Pazaran <cova_ruber@live.com.mx>

Diff between lme4breeding versions 1.0.21 dated 2024-06-25 and 1.0.22 dated 2024-06-27

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 lme4breeding-1.0.22/lme4breeding/inst/doc/lmebreed.gxe.R     |   18 ++--
 lme4breeding-1.0.22/lme4breeding/inst/doc/lmebreed.gxe.Rmd   |   20 ++---
 lme4breeding-1.0.22/lme4breeding/inst/doc/lmebreed.gxe.pdf   |binary
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 lme4breeding-1.0.22/lme4breeding/inst/doc/lmebreed.qg.pdf    |binary
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 lme4breeding-1.0.22/lme4breeding/vignettes/lmebreed.qg.Rmd   |    2 
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 22 files changed, 96 insertions(+), 94 deletions(-)

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New package LatentBMA with initial version 0.1.0
Package: LatentBMA
Title: Bayesian Model Averaging for Univariate Link Latent Gaussian Models
Version: 0.1.0
Author: Gregor Zens [aut, cre], Mark F.J. Steel [aut]
Maintainer: Gregor Zens <zens@iiasa.ac.at>
Description: Bayesian model averaging (BMA) algorithms for univariate link latent Gaussian models (ULLGMs). For detailed information, refer to Steel M.F.J. & Zens G. (2024) "Model Uncertainty in Latent Gaussian Models with Univariate Link Function" <doi:10.48550/arXiv.2406.17318>. The package supports various g-priors and a beta-binomial prior on the model space. It also includes auxiliary functions for visualizing and tabulating BMA results. Currently, it offers an out-of-the-box solution for model averaging of Poisson log-normal (PLN) and binomial logistic-normal (BiL) models. The codebase is designed to be easily extendable to other likelihoods, priors, and link functions.
Encoding: UTF-8
License: MIT + file LICENSE
Imports: ggplot2 (>= 3.5.1), knitr (>= 1.47), mnormt (>= 2.1.1), progress (>= 1.2.3), reshape2 (>= 1.4.4)
Suggests: rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-06-26 14:03:10 UTC; Gregor
Repository: CRAN
Date/Publication: 2024-06-27 14:40:26 UTC

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Package khisr updated to version 1.0.5 with previous version 1.0.4 dated 2024-06-10

Title: An R Client to Retrieve Data from DHIS2
Description: Provides a user-friendly interface for interacting with the District Health Information Software 2 (DHIS2) instance. It streamlines data retrieval, empowering researchers, analysts, and healthcare professionals to obtain and utilize data efficiently.
Author: David Kariuki [aut, cre, cph]
Maintainer: David Kariuki <hello@damurka.com>

Diff between khisr versions 1.0.4 dated 2024-06-10 and 1.0.5 dated 2024-06-27

 DESCRIPTION                                    |    6 
 MD5                                            |   44 -
 NEWS.md                                        |    6 
 R/api_get.R                                    |  154 ++--
 R/get_analytics_by_level.R                     |  198 +++---
 R/get_data_elements_with_category_options.R    |  110 +--
 R/get_datasets_by_level.R                      |  189 +++--
 R/get_metadata.R                               |  137 ++--
 R/get_organisations_by_level.R                 |  225 +++----
 R/khis_cred.R                                  |  799 ++++++++++++-------------
 R/utils.R                                      |   10 
 README.md                                      |   61 -
 inst/extdata/valid_cred_conf.json              |   14 
 man/get_analytics_by_level.Rd                  |    7 
 man/get_data_elements_with_category_options.Rd |   10 
 man/get_data_sets_by_level.Rd                  |    5 
 man/get_metadata.Rd                            |    5 
 man/get_organisations_by_level.Rd              |   11 
 man/khis_base_url.Rd                           |    5 
 man/khis_has_cred.Rd                           |    5 
 man/khis_username.Rd                           |    5 
 man/metadata-helpers.Rd                        |    1 
 tests/testthat/test-khis_cred.R                |  178 ++---
 23 files changed, 1113 insertions(+), 1072 deletions(-)

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New package greenR with initial version 0.0.1.1
Package: greenR
Title: Green Index Quantification, Analysis and Visualization
Version: 0.0.1.1
Description: Quantification, analysis, and visualization of urban greenness within city networks using data from 'OpenStreetMap' <https://www.openstreetmap.org>.
License: GPL (>= 3)
Encoding: UTF-8
Imports: DT, httr, magrittr, dplyr, ggplot2, osmdata, sf, htmltools, leaflet, shiny, tibble, SuperpixelImageSegmentation, OpenImageR, osrm, spatstat.geom, stats, units, duckdb, DBI, data.table, RColorBrewer, htmlwidgets, viridisLite, rstudioapi, jsonlite
Suggests: knitr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-06-26 14:29:23 UTC; smahajan
Author: Sachit Mahajan [aut, cre]
Maintainer: Sachit Mahajan <sachitmahajan90@gmail.com>
Repository: CRAN
Date/Publication: 2024-06-27 14:40:08 UTC

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New package frailtypack with initial version 3.6.1
Package: frailtypack
Version: 3.6.1
Date: 2024-06-25
Title: Shared, Joint (Generalized) Frailty Models; Surrogate Endpoints
Depends: R (>= 3.5.0), survival, boot, MASS, survC1, doBy
Imports: statmod, nlme, shiny, rootSolve, splines
LazyLoad: no
Description: The following several classes of frailty models using a penalized likelihood estimation on the hazard function but also a parametric estimation can be fit using this R package: 1) A shared frailty model (with gamma or log-normal frailty distribution) and Cox proportional hazard model. Clustered and recurrent survival times can be studied. 2) Additive frailty models for proportional hazard models with two correlated random effects (intercept random effect with random slope). 3) Nested frailty models for hierarchically clustered data (with 2 levels of clustering) by including two iid gamma random effects. 4) Joint frailty models in the context of the joint modelling for recurrent events with terminal event for clustered data or not. A joint frailty model for two semi-competing risks and clustered data is also proposed. 5) Joint general frailty models in the context of the joint modelling for recurrent events with terminal event data with two independent frailty terms. 6) Joint Nested fra [...truncated...]
License: GPL (>= 2.0)
URL: https://virginie1rondeau.wixsite.com/virginierondeau/software-frailtypack https://frailtypack-pkg.shinyapps.io/shiny_frailtypack/
Suggests: knitr, testthat, rmarkdown, markdown
VignetteBuilder: knitr
Repository: CRAN
Date/Publication: 2024-06-27 14:40:11 UTC
Packaged: 2024-06-25 12:17:58 UTC; Quent
NeedsCompilation: yes
Author: Virginie Rondeau [aut, cre] , Juan R. Gonzalez [aut], Yassin Mazroui [aut], Audrey Mauguen [aut], Amadou Diakite [aut], Alexandre Laurent [aut], Myriam Lopez [aut], Agnieszka Krol [aut], Casimir L. Sofeu [aut], Julien Dumerc [aut], Denis Rustand [aut [...truncated...]
Maintainer: Virginie Rondeau <virginie.rondeau@u-bordeaux.fr>

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Package EdSurvey updated to version 4.0.7 with previous version 4.0.6 dated 2024-05-21

Title: Analysis of NCES Education Survey and Assessment Data
Description: Read in and analyze functions for education survey and assessment data from the National Center for Education Statistics (NCES) <https://nces.ed.gov/>, including National Assessment of Educational Progress (NAEP) data <https://nces.ed.gov/nationsreportcard/> and data from the International Assessment Database: Organisation for Economic Co-operation and Development (OECD) <https://www.oecd.org/>, including Programme for International Student Assessment (PISA), Teaching and Learning International Survey (TALIS), Programme for the International Assessment of Adult Competencies (PIAAC), and International Association for the Evaluation of Educational Achievement (IEA) <https://www.iea.nl/>, including Trends in International Mathematics and Science Study (TIMSS), TIMSS Advanced, Progress in International Reading Literacy Study (PIRLS), International Civic and Citizenship Study (ICCS), International Computer and Information Literacy Study (ICILS), and Civic Education S [...truncated...]
Author: Paul Bailey [aut, cre] , Ahmad Emad [aut], Huade Huo [aut] , Michael Lee [aut] , Yuqi Liao [aut] , Alex Lishinski [aut] , Trang Nguyen [aut] , Qingshu Xie [aut], Jiao Yu [aut], Ting Zhang [aut] , Eric Buehler [aut] , Sun-joo Lee [aut], Blue Webb [aut [...truncated...]
Maintainer: Paul Bailey <pbailey@air.org>

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Package datagovsgR updated to version 1.0.1 with previous version 1.0.0 dated 2023-01-15

Title: Call Real Time APIs from Data Gov Singapore
Description: A wrapper for the Data.gov.sg developer resources, which provide real time and historical information, ranging from carpark availability to weather forecasts. The functions makes the API calls for a given date and time, before returning the relevant information in a data frame. All APIs are supported, less the IPOS one which is not returning any data. Relevant information can be found here <https://data.gov.sg/developer>.
Author: Clinton Wong <cwxy.clinton@gmail.com>
Maintainer: Clinton Wong <cwxy.clinton@gmail.com>

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New package bayesCureRateModel with initial version 1.0
Package: bayesCureRateModel
Title: Bayesian Cure Rate Modeling for Time-to-Event Data
Version: 1.0
Date: 2024-06-26
Maintainer: Panagiotis Papastamoulis <papapast@yahoo.gr>
Description: A fully Bayesian approach in order to estimate a general family of cure rate models under the presence of covariates, see Papastamoulis and Milienos (2023) <doi:10.48550/arXiv.2310.06926>. The promotion time can be modelled (a) parametrically using typical distributional assumptions for time to event data (including the Weibull, Exponential, Gompertz, log-Logistic distributions), or (b) semiparametrically using finite mixtures of Gamma distributions. Posterior inference is carried out by constructing a Metropolis-coupled Markov chain Monte Carlo (MCMC) sampler, which combines Gibbs sampling for the latent cure indicators and Metropolis-Hastings steps with Langevin diffusion dynamics for parameter updates. The main MCMC algorithm is embedded within a parallel tempering scheme by considering heated versions of the target posterior distribution.
License: GPL-2
URL: https://github.com/mqbssppe/Bayesian_cure_rate_model
Imports: Rcpp (>= 1.0.12),doParallel, foreach, mclust, coda, HDInterval, VGAM, calculus, flexsurv
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Packaged: 2024-06-26 11:12:12 UTC; panagiotis
Author: Panagiotis Papastamoulis [aut, cre] , Fotios Milienos [aut]
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2024-06-27 14:20:06 UTC

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Package antaresViz updated to version 0.18.2 with previous version 0.18.1 dated 2024-06-26

Title: Antares Visualizations
Description: Visualize results generated by Antares, a powerful open source software developed by RTE to simulate and study electric power systems (more information about 'Antares' here: <https://github.com/AntaresSimulatorTeam/Antares_Simulator>). This package provides functions that create interactive charts to help 'Antares' users visually explore the results of their simulations.
Author: Tatiana Vargas [aut, cre], Jalal-Edine Zawam [aut], Francois Guillem [aut], Benoit Thieurmel [aut], Titouan Robert [aut], Paul Plessiez [aut], Baptiste Seguinot [ctb], RTE [cph]
Maintainer: Tatiana Vargas <tatiana.vargas@rte-france.com>

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Package tsibble updated to version 1.1.5 with previous version 1.1.4 dated 2024-01-29

Title: Tidy Temporal Data Frames and Tools
Description: Provides a 'tbl_ts' class (the 'tsibble') for temporal data in an data- and model-oriented format. The 'tsibble' provides tools to easily manipulate and analyse temporal data, such as filling in time gaps and aggregating over calendar periods.
Author: Earo Wang [aut, cre] , Di Cook [aut, ths] , Rob Hyndman [aut, ths] , Mitchell O'Hara-Wild [aut] , Tyler Smith [ctb], Wil Davis [ctb]
Maintainer: Earo Wang <earo.wang@gmail.com>

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Package RiskScorescvd updated to version 0.2.0 with previous version 0.1.0 dated 2023-06-28

Title: Cardiovascular Risk Scores Calculator
Description: A tool to calculate Cardiovascular Risk Scores in large data frames. Cardiovascular risk scores are statistical tools used to assess an individual's likelihood of developing a cardiovascular disease based on various risk factors, such as age, gender, blood pressure, cholesterol levels, and smoking. Here we bring together the six most commonly used in the emergency department. Using 'RiskScorescvd', you can calculate all the risk scores in an extended dataset in seconds. PCE (ASCVD) described in Goff, et al (2013) <doi:10.1161/01.cir.0000437741.48606.98>. EDACS described in Mark DG, et al (2016) <doi:10.1016/j.jacc.2017.11.064>. GRACE described in Fox KA, et al (2006) <doi:10.1136/bmj.38985.646481.55>. HEART is described in Mahler SA, et al (2017) <doi:10.1016/j.clinbiochem.2017.01.003>. SCORE2/OP described in SCORE2 working group and ESC Cardiovascular risk collaboration (2021) <doi:10.1093/eurheartj/ehab309>. TIMI described in Antman EM, et al (2000) < [...truncated...]
Author: Daniel Perez-Vicencio [aut, cre] , Dimitrios Doudesis [aut], Alexander JF Thurston [aut], Jeremy Selva [aut]
Maintainer: Daniel Perez-Vicencio <dvicencio947@gmail.com>

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Package UComp updated to version 5.0.0 with previous version 4.0.2 dated 2023-05-20

Title: Automatic Univariate Time Series Modelling of many Kinds
Description: Comprehensive analysis and forecasting of univariate time series using automatic time series models of many kinds. Harvey AC (1989) <doi:10.1017/CBO9781107049994>. Pedregal DJ and Young PC (2002) <doi:10.1002/9780470996430>. Durbin J and Koopman SJ (2012) <doi:10.1093/acprof:oso/9780199641178.001.0001>. Hyndman RJ, Koehler AB, Ord JK, and Snyder RD (2008) <doi:10.1007/978-3-540-71918-2>. Gómez V, Maravall A (2000) <doi:10.1002/9781118032978>. Pedregal DJ, Trapero JR and Holgado E (2024) <doi:10.1016/j.ijforecast.2023.09.004>.
Author: Diego J. Pedregal [aut, cre]
Maintainer: Diego J. Pedregal <Diego.Pedregal@uclm.es>

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Package tfevents updated to version 0.0.4 with previous version 0.0.3 dated 2024-05-06

Title: Write Events for 'TensorBoard'
Description: Provides a convenient way to log scalars, images, audio, and histograms in the 'tfevent' record file format. Logged data can be visualized on the fly using 'TensorBoard', a web based tool that focuses on visualizing the training progress of machine learning models.
Author: Daniel Falbel [aut, cre, cph], Posit, PBC [cph], The tl::optional authors [cph] , Mark Adler [cph]
Maintainer: Daniel Falbel <daniel@posit.co>

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Package nphRCT updated to version 0.1.1 with previous version 0.1.0 dated 2022-09-01

Title: Non-Proportional Hazards in Randomized Controlled Trials
Description: Perform a stratified weighted log-rank test in a randomized controlled trial. Tests can be visualized as a difference in average score on the two treatment arms. These methods are described in Magirr and Burman (2018) <doi:10.48550/arXiv.1807.11097>, Magirr (2020) <doi:10.48550/arXiv.2007.04767>, and Magirr and Jimenez (2022) <doi:10.48550/arXiv.2201.10445>.
Author: Dominic Magirr [aut, cre], Isobel Barrott [aut], Jose Jimenez [ctb]
Maintainer: Dominic Magirr <d.magirr@gmail.com>

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Package dacc updated to version 0.0-4 with previous version 0.0-3 dated 2024-01-09

Title: Detection and Attribution Analysis of Climate Change
Description: Conduct detection and attribution of climate change using methods including optimal fingerprinting via generalized total least squares or estimating equation approach from Ma et al. (2023) <doi:10.1175/JCLI-D-22-0681.1>. Provide shrinkage estimators for covariance matrix from Ledoit and Wolf (2004) <doi:10.1016/S0047-259X(03)00096-4>, and Ledoit and Wolf (2017) <doi:10.2139/ssrn.2383361>.
Author: Yan Li [aut, cre], Kun Chen [aut], Jun Yan [aut]
Maintainer: Yan Li <yan.4.li@uconn.edu>

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Package tok updated to version 0.1.2 with previous version 0.1.1 dated 2023-08-17

Title: Fast Text Tokenization
Description: Interfaces with the 'Hugging Face' tokenizers library to provide implementations of today's most used tokenizers such as the 'Byte-Pair Encoding' algorithm <https://huggingface.co/docs/tokenizers/index>. It's extremely fast for both training new vocabularies and tokenizing texts.
Author: Daniel Falbel [aut, cre], Posit [cph]
Maintainer: Daniel Falbel <daniel@posit.co>

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More information about tok at CRAN
Permanent link

Package pamr updated to version 1.56.2.1 with previous version 1.56.2 dated 2024-04-20

Title: Pam: Prediction Analysis for Microarrays
Description: Some functions for sample classification in microarrays.
Author: T. Hastie, R. Tibshirani, Balasubramanian Narasimhan, Gil Chu
Maintainer: ORPHANED

Diff between pamr versions 1.56.2 dated 2024-04-20 and 1.56.2.1 dated 2024-06-27

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More information about pamr at CRAN
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New package geohabnet with initial version 2.1.3
Package: geohabnet
Title: Geographical Risk Analysis Based on Habitat Connectivity
Version: 2.1.3
Date: 2024-06-26
Description: The geohabnet package is designed to perform a geographically or spatially explicit risk analysis of habitat connectivity. Xing et al (2021) <doi:10.1093/biosci/biaa067> proposed the concept of cropland connectivity as a risk factor for plant pathogen or pest invasions. As the functions in geohabnet were initially developed thinking on cropland connectivity, users are recommended to first be familiar with the concept by looking at the Xing et al paper. In a nutshell, a habitat connectivity analysis combines information from maps of host density, estimates the relative likelihood of pathogen movement between habitat locations in the area of interest, and applies network analysis to calculate the connectivity of habitat locations. The functions of geohabnet are built to conduct a habitat connectivity analysis relying on geographic parameters (spatial resolution and spatial extent), dispersal parameters (in two commonly used dispersal kernels: inverse power law and negative exponent [...truncated...]
License: GPL-3
Encoding: UTF-8
Imports: config (>= 0.3.1), geodata (>= 0.6.2), geosphere (>= 1.5.18), igraph (>= 2.0.3), terra (>= 1.7.29), easycsv (>= 1.0.8), yaml (>= 2.3.7), stats, stringr (>= 1.5.0), memoise (>= 2.0.1), graphics, rlang (>= 1.1.1), viridisLite (>= 0.4.2), beepr (>= 1.3), rnaturalearth (>= 0.3.3), tools, methods, future.apply (>= 1.11.0), future (>= 1.33.0), magrittr (>= 2.0.3), ggplot2 (>= 3.5.1), patchwork (>= 1.2.0)
Suggests: devtools, knitr, lintr (>= 3.0.2), mockthat (>= 0.2.8), pkgdown, rmarkdown, testthat (>= 3.1.7)
URL: https://garrettlab.github.io/HabitatConnectivity/, https://CRAN.R-project.org/package=geohabnet/, https://github.com/GarrettLab/HabitatConnectivity/tree/main/geohabnet/, https://www.garrettlab.com/
BugReports: https://github.com/GarrettLab/HabitatConnectivity/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-06-26 19:05:04 UTC; kkeshav
Author: Krishna Keshav [aut, cre], Aaron Plex [aut] , Garrett Lab [ctb] , Karen Garrett [aut] , University of Florida [cph, fnd]
Maintainer: Krishna Keshav <kkeshav@ufl.edu>
Repository: CRAN
Date/Publication: 2024-06-27 11:50:02 UTC

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Package escalation updated to version 0.1.10 with previous version 0.1.9 dated 2024-05-22

Title: A Modular Approach to Dose-Finding Clinical Trials
Description: Methods for working with dose-finding clinical trials. We provide implementations of many dose-finding clinical trial designs, including the continual reassessment method (CRM) by O'Quigley et al. (1990) <doi:10.2307/2531628>, the toxicity probability interval (TPI) design by Ji et al. (2007) <doi:10.1177/1740774507079442>, the modified TPI (mTPI) design by Ji et al. (2010) <doi:10.1177/1740774510382799>, the Bayesian optimal interval design (BOIN) by Liu & Yuan (2015) <doi:10.1111/rssc.12089>, EffTox by Thall & Cook (2004) <doi:10.1111/j.0006-341X.2004.00218.x>; the design of Wages & Tait (2015) <doi:10.1080/10543406.2014.920873>, and the 3+3 described by Korn et al. (1994) <doi:10.1002/sim.4780131802>. All designs are implemented with a common interface. We also offer optional additional classes to tailor the behaviour of all designs, including avoiding skipping doses, stopping after n patients have been treated at the recommended [...truncated...]
Author: Kristian Brock [aut, cre] , Daniel Slade [aut] , Michael Sweeting [aut]
Maintainer: Kristian Brock <kristian.brock@gmail.com>

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Package dipsaus updated to version 0.2.9 with previous version 0.2.8 dated 2023-07-03

Title: A Dipping Sauce for Data Analysis and Visualizations
Description: Works as an "add-on" to packages like 'shiny', 'future', as well as 'rlang', and provides utility functions. Just like dipping sauce adding flavors to potato chips or pita bread, 'dipsaus' for data analysis and visualizations adds handy functions and enhancements to popular packages. The goal is to provide simple solutions that are frequently asked for online, such as how to synchronize 'shiny' inputs without freezing the app, or how to get memory size on 'Linux' or 'MacOS' system. The enhancements roughly fall into these four categories: 1. 'shiny' input widgets; 2. high-performance computing using the 'future' package; 3. modify R calls and convert among numbers, strings, and other objects. 4. utility functions to get system information such like CPU chip-set, memory limit, etc.
Author: Zhengjia Wang [aut, cre], John Magnotti [ctb] , Xiang Zhang [ctb]
Maintainer: Zhengjia Wang <dipterix.wang@gmail.com>

Diff between dipsaus versions 0.2.8 dated 2023-07-03 and 0.2.9 dated 2024-06-27

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Package CVXR updated to version 1.0-14 with previous version 1.0-13 dated 2024-06-01

Title: Disciplined Convex Optimization
Description: An object-oriented modeling language for disciplined convex programming (DCP) as described in Fu, Narasimhan, and Boyd (2020, <doi:10.18637/jss.v094.i14>). It allows the user to formulate convex optimization problems in a natural way following mathematical convention and DCP rules. The system analyzes the problem, verifies its convexity, converts it into a canonical form, and hands it off to an appropriate solver to obtain the solution. Interfaces to solvers on CRAN and elsewhere are provided, both commercial and open source.
Author: Anqi Fu [aut, cre], Balasubramanian Narasimhan [aut], David W Kang [aut], Steven Diamond [aut], John Miller [aut], Stephen Boyd [ctb], Paul Kunsberg Rosenfield [ctb]
Maintainer: Anqi Fu <anqif@alumni.stanford.edu>

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Package cops updated to version 1.11-3 with previous version 1.3-1 dated 2023-01-19

Title: Cluster Optimized Proximity Scaling
Description: Multidimensional scaling (MDS) methods that aim at pronouncing the clustered appearance of the configuration (Rusch, Mair & Hornik, 2021, <doi:10.1080/10618600.2020.1869027>). They achieve this by transforming proximities/distances with explicit power functions and penalizing the fitting criterion with a clusteredness index, the OPTICS Cordillera (Rusch, Hornik & Mair, 2018, <doi:10.1080/10618600.2017.1349664>). There are two variants: One for finding the configuration directly (COPS-C) with given explicit power transformations and implicit ratio, interval and non-metric optimal scaling transformations (Borg & Groenen, 2005, ISBN:978-0-387-28981-6), and one for using the augmented fitting criterion to find optimal hyperparameters for the explicit transformations (P-COPS). The package contains various functions, wrappers, methods and classes for fitting, plotting and displaying a large number of different MDS models (most of the functionality in smacofx) in the C [...truncated...]
Author: Thomas Rusch [aut, cre] , Patrick Mair [aut] , Kurt Hornik [ctb]
Maintainer: Thomas Rusch <thomas.rusch@wu.ac.at>

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Package Rvcg updated to version 0.23 with previous version 0.22.2 dated 2023-12-06

Title: Manipulations of Triangular Meshes Based on the 'VCGLIB' API
Description: Operations on triangular meshes based on 'VCGLIB'. This package integrates nicely with the R-package 'rgl' to render the meshes processed by 'Rvcg'. The Visualization and Computer Graphics Library (VCG for short) is an open source portable C++ templated library for manipulation, processing and displaying with OpenGL of triangle and tetrahedral meshes. The library, composed by more than 100k lines of code, is released under the GPL license, and it is the base of most of the software tools of the Visual Computing Lab of the Italian National Research Council Institute ISTI <https://vcg.isti.cnr.it/>, like 'metro' and 'MeshLab'. The 'VCGLIB' source is pulled from trunk <https://github.com/cnr-isti-vclab/vcglib> and patched to work with options determined by the configure script as well as to work with the header files included by 'RcppEigen'.
Author: Stefan Schlager [aut, cre, cph], Girinon Francois [ctb], Tim Schaefer [ctb], Zhengjia Wang [ctb]
Maintainer: Stefan Schlager <zarquon42@gmail.com>

Diff between Rvcg versions 0.22.2 dated 2023-12-06 and 0.23 dated 2024-06-27

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Package psych updated to version 2.4.6.26 with previous version 2.4.3 dated 2024-03-18

Title: Procedures for Psychological, Psychometric, and Personality Research
Description: A general purpose toolbox developed originally for personality, psychometric theory and experimental psychology. Functions are primarily for multivariate analysis and scale construction using factor analysis, principal component analysis, cluster analysis and reliability analysis, although others provide basic descriptive statistics. Item Response Theory is done using factor analysis of tetrachoric and polychoric correlations. Functions for analyzing data at multiple levels include within and between group statistics, including correlations and factor analysis. Validation and cross validation of scales developed using basic machine learning algorithms are provided, as are functions for simulating and testing particular item and test structures. Several functions serve as a useful front end for structural equation modeling. Graphical displays of path diagrams, including mediation models, factor analysis and structural equation models are created using basic graphics. Some of the fu [...truncated...]
Author: William Revelle [aut, cre]
Maintainer: William Revelle <revelle@northwestern.edu>

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Package nimbleEcology updated to version 0.5.0 with previous version 0.4.1 dated 2021-11-01

Title: Distributions for Ecological Models in 'nimble'
Description: Common ecological distributions for 'nimble' models in the form of nimbleFunction objects. Includes Cormack-Jolly-Seber, occupancy, dynamic occupancy, hidden Markov, dynamic hidden Markov, and N-mixture models. (Jolly (1965) <DOI: 10.2307/2333826>, Seber (1965) <DOI: 10.2307/2333827>, Turek et al. (2016) <doi:10.1007/s10651-016-0353-z>).
Author: Benjamin R. Goldstein [aut, cre], Daniel Turek [aut], Lauren Ponisio [aut], Wei Zhang [ctb], Perry de Valpine [aut]
Maintainer: Benjamin R. Goldstein <bgoldst2@ncsu.edu>

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Package mergen updated to version 0.2.1 with previous version 0.1.0 dated 2023-12-08

Title: AI-Driven Code Generation, Explanation and Execution for Data Analysis
Description: Employing artificial intelligence to convert data analysis questions into executable code, explanations, and algorithms. The self-correction feature ensures the generated code is optimized for performance and accuracy. 'mergen' features a user-friendly chat interface, enabling users to interact with the AI agent and extract valuable insights from their data effortlessly.
Author: Altuna Akalin [aut, cre] , Jacqueline Anne Jansen [aut]
Maintainer: Altuna Akalin <aakalin@gmail.com>

Diff between mergen versions 0.1.0 dated 2023-12-08 and 0.2.1 dated 2024-06-27

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Package GaSP updated to version 1.0.6 with previous version 1.0.5 dated 2023-12-08

Title: Train and Apply a Gaussian Stochastic Process Model
Description: Train a Gaussian stochastic process model of an unknown function, possibly observed with error, via maximum likelihood or maximum a posteriori (MAP) estimation, run model diagnostics, and make predictions, following Sacks, J., Welch, W.J., Mitchell, T.J., and Wynn, H.P. (1989) "Design and Analysis of Computer Experiments", Statistical Science, <doi:10.1214/ss/1177012413>. Perform sensitivity analysis and visualize low-order effects, following Schonlau, M. and Welch, W.J. (2006), "Screening the Input Variables to a Computer Model Via Analysis of Variance and Visualization", <doi:10.1007/0-387-28014-6_14>.
Author: William J. Welch [aut, cre, cph] , Yilin Yang [aut]
Maintainer: William J. Welch <will@stat.ubc.ca>

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Package synthesis (with last version 1.2.4) was removed from CRAN

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

2023-11-01 1.2.4
2021-11-27 1.2.3
2021-05-03 1.2.2
2021-04-02 1.2.1
2020-11-05 1.2.0

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Package MPCR (with last version 1.1.2) was removed from CRAN

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

2024-05-28 1.1.2
2024-05-21 1.1.1

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Package phoenics updated to version 0.2 with previous version 0.1 dated 2024-05-22

Title: Pathways Longitudinal and Differential Analysis in Metabolomics
Description: Perform a differential analysis at pathway level based on metabolite quantifications and information on pathway metabolite composition. The method is based on a Principal Component Analysis step and on a linear mixed model. Automatic query of metabolic pathways is also implemented.
Author: Camille Guilmineau [aut, cre], Remi Servien [aut] , Nathalie Vialaneix [aut]
Maintainer: Camille Guilmineau <camille.guilmineau@inrae.fr>

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Package lpme (with last version 1.1.3) was removed from CRAN

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

2022-05-10 1.1.3
2021-07-13 1.1.2
2017-10-31 1.1.1
2017-03-24 1.1.0
2014-12-19 1.0.1
2014-11-05 1.0.0

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Package decon (with last version 1.3-4) was removed from CRAN

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

2021-10-20 1.3-4
2013-04-17 1.2-4
2011-02-28 1.2-2
2010-10-21 1.2-1
2010-10-08 1.2
2010-03-23 1.1-1

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Package Robyn updated to version 3.11.1 with previous version 3.11.0 dated 2024-06-19

Title: Semi-Automated Marketing Mix Modeling (MMM) from Meta Marketing Science
Description: Semi-Automated Marketing Mix Modeling (MMM) aiming to reduce human bias by means of ridge regression and evolutionary algorithms, enables actionable decision making providing a budget allocation and diminishing returns curves and allows ground-truth calibration to account for causation.
Author: Gufeng Zhou [aut], Bernardo Lares [cre, aut], Leonel Sentana [aut], Igor Skokan [aut], Meta Platforms, Inc. [cph, fnd]
Maintainer: Bernardo Lares <laresbernardo@gmail.com>

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Package rtables updated to version 0.6.9 with previous version 0.6.8 dated 2024-06-20

Title: Reporting Tables
Description: Reporting tables often have structure that goes beyond simple rectangular data. The 'rtables' package provides a framework for declaring complex multi-level tabulations and then applying them to data. This framework models both tabulation and the resulting tables as hierarchical, tree-like objects which support sibling sub-tables, arbitrary splitting or grouping of data in row and column dimensions, cells containing multiple values, and the concept of contextual summary computations. A convenient pipe-able interface is provided for declaring table layouts and the corresponding computations, and then applying them to data.
Author: Gabriel Becker [aut] , Adrian Waddell [aut], Daniel Sabanes Bove [ctb], Maximilian Mordig [ctb], Davide Garolini [ctb], Emily de la Rua [ctb], Abinaya Yogasekaram [ctb], Joe Zhu [ctb, cre], F. Hoffmann-La Roche AG [cph, fnd]
Maintainer: Joe Zhu <joe.zhu@roche.com>

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Package geommc updated to version 0.0.1 with previous version 0.0.0 dated 2024-06-17

Title: Geometric Markov Chain Sampling
Description: Simulates from discrete and continuous target distributions using geometric Metropolis-Hastings (MH) algorithms. Users specify the target distribution by an R function that evaluates the log un-normalized pdf or pmf. The package also contains a function implementing a specific geometric MH algorithm for performing high dimensional Bayesian variable selection.
Author: Vivekananda Roy [aut, cre]
Maintainer: Vivekananda Roy <vroy@iastate.edu>

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Package Mhorseshoe updated to version 0.1.3 with previous version 0.1.2 dated 2023-11-24

Title: Approximate Algorithm for Horseshoe Prior
Description: Provides exact and approximate algorithms for the horseshoe prior in linear regression models, which were proposed by Johndrow et al. (2020) <https://www.jmlr.org/papers/v21/19-536.html>.
Author: Kang Mingi [aut, cre], Lee Kyoungjae [aut]
Maintainer: Kang Mingi <leehuimin115@g.skku.edu>

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