Sun, 28 May 2023

Package varTestnlme updated to version 1.3.4 with previous version 1.3.3 dated 2023-05-23

Title: Variance Components Testing for Linear and Nonlinear Mixed Effects Models
Description: An implementation of the Likelihood ratio Test (LRT) for testing that, in a (non)linear mixed effects model, the variances of a subset of the random effects are equal to zero. There is no restriction on the subset of variances that can be tested: for example, it is possible to test that all the variances are equal to zero. Note that the implemented test is asymptotic. This package should be used on model fits from packages 'nlme', 'lmer', and 'saemix'. Charlotte Baey, Paul-Henry Cournède and Estelle Kuhn (2019) <doi:10.1016/j.csda.2019.01.014>.
Author: Charlotte Baey [aut, cre] , Estelle Kuhn [aut]
Maintainer: Charlotte Baey <charlotte.baey@univ-lille.fr>

Diff between varTestnlme versions 1.3.3 dated 2023-05-23 and 1.3.4 dated 2023-05-28

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Package maptools updated to version 1.1-7 with previous version 1.1-6 dated 2022-12-14

Title: Tools for Handling Spatial Objects
Description: Please note that 'maptools' will be retired during October 2023, plan transition at your earliest convenience (see <https://r-spatial.org/r/2023/05/15/evolution4.html> and earlier blogs for guidance); some functionality will be moved to 'sp'. Set of tools for manipulating geographic data. The package also provides interface wrappers for exchanging spatial objects with packages such as 'PBSmapping', 'spatstat.geom', 'maps', and others.
Author: Roger Bivand [cre, aut] , Nicholas Lewin-Koh [aut], Edzer Pebesma [ctb], Eric Archer [ctb], Adrian Baddeley [ctb], Nick Bearman [ctb], Hans-Joerg Bibiko [ctb], Steven Brey [ctb], Jonathan Callahan [ctb], German Carrillo [ctb], Stephane Dray [ctb], Dav [...truncated...]
Maintainer: Roger Bivand <Roger.Bivand@nhh.no>

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Package ucminf updated to version 1.2.0 with previous version 1.1-4.3 dated 2023-05-18

Title: General-Purpose Unconstrained Non-Linear Optimization
Description: An algorithm for general-purpose unconstrained non-linear optimization. The algorithm is of quasi-Newton type with BFGS updating of the inverse Hessian and soft line search with a trust region type monitoring of the input to the line search algorithm. The interface of 'ucminf' is designed for easy interchange with 'optim'.
Author: K Herve Dakpo [ctb, cre], Hans Bruun Nielsen [aut], Stig Bousgaard Mortensen [aut]
Maintainer: K Herve Dakpo <k-herve.dakpo@inrae.fr>

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Package nanonext updated to version 0.9.0 with previous version 0.8.3 dated 2023-05-06

Title: NNG (Nanomsg Next Gen) Lightweight Messaging Library
Description: R binding for NNG (Nanomsg Next Gen), a successor to ZeroMQ. NNG is a socket library providing high-performance scalability protocols, a cross-platform standard for messaging and communications. Serves as a concurrency framework for building distributed applications, utilising 'aio' objects which resolve automatically upon completion of asynchronous operations. Implements synchronisation primitives, allowing R to wait upon events being signalled by concurrent messaging threads.
Author: Charlie Gao [aut, cre] , Hibiki AI Limited [cph]
Maintainer: Charlie Gao <charlie.gao@shikokuchuo.net>

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Package lingtypology updated to version 1.1.14 with previous version 1.1.13 dated 2023-04-21

Title: Linguistic Typology and Mapping
Description: Provides R with the Glottolog database <https://glottolog.org/> and some more abilities for purposes of linguistic mapping. The Glottolog database contains the catalogue of languages of the world. This package helps researchers to make a linguistic maps, using philosophy of the Cross-Linguistic Linked Data project <https://clld.org/>, which allows for while at the same time facilitating uniform access to the data across publications. A tutorial for this package is available on GitHub pages <https://docs.ropensci.org/lingtypology/> and package vignette. Maps created by this package can be used both for the investigation and linguistic teaching. In addition, package provides an ability to download data from typological databases such as WALS, AUTOTYP and some others and to create your own database website.
Author: George Moroz [aut, cre] , Kirill Koncha [ctb] , Mikhail Leonov [ctb], Anna Smirnova [ctb], Ekaterina Zalivina [ctb]
Maintainer: George Moroz <agricolamz@gmail.com>

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Package httptest updated to version 4.2.0 with previous version 4.1.0 dated 2021-09-22

Title: A Test Environment for HTTP Requests
Description: Testing and documenting code that communicates with remote servers can be painful. Dealing with authentication, server state, and other complications can make testing seem too costly to bother with. But it doesn't need to be that hard. This package enables one to test all of the logic on the R sides of the API in your package without requiring access to the remote service. Importantly, it provides three contexts that mock the network connection in different ways, as well as testing functions to assert that HTTP requests were---or were not---made. It also allows one to safely record real API responses to use as test fixtures. The ability to save responses and load them offline also enables one to write vignettes and other dynamic documents that can be distributed without access to a live server.
Author: Neal Richardson [aut, cre] , Jonathan Keane [ctb], Maelle Salmon [ctb]
Maintainer: Neal Richardson <neal.p.richardson@gmail.com>

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Package ggdag updated to version 0.2.10 with previous version 0.2.9 dated 2023-05-22

Title: Analyze and Create Elegant Directed Acyclic Graphs
Description: Tidy, analyze, and plot directed acyclic graphs (DAGs). 'ggdag' is built on top of 'dagitty', an R package that uses the 'DAGitty' web tool (<http://dagitty.net>) for creating and analyzing DAGs. 'ggdag' makes it easy to tidy and plot 'dagitty' objects using 'ggplot2' and 'ggraph', as well as common analytic and graphical functions, such as determining adjustment sets and node relationships.
Author: Malcolm Barrett [aut, cre]
Maintainer: Malcolm Barrett <malcolmbarrett@gmail.com>

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Package gdalraster updated to version 1.2.0 with previous version 1.1.1 dated 2023-05-24

Title: Bindings to the 'Geospatial Data Abstraction Library' Raster API
Description: Interface to the raster API of the 'Geospatial Data Abstraction Library' ('GDAL') supporting manual creation of uninitialized datasets, creation from existing raster as template, low level I/O, configuration of virtual raster (VRT), coordinate transformation, and access to 'gdalwarp' for reprojection. Convenience functions facilitate working with spatial reference systems. Calling signatures resemble the native C, C++ and Python APIs provided by the 'GDAL' project (<https://gdal.org>). Bindings to 'GDAL' are implemented in class 'GDALRaster' along with several stand-alone functions. Additional functionality includes: class 'RunningStats' for efficient summary statistics on large data streams; class 'CmbTable' for counting unique combinations of integer values with a hash table; a raster overlay utility to identify and count unique combinations across multiple inputs; and a calculation utility for evaluating an R expression on raster layers with pixel coordinates available as vari [...truncated...]
Author: Chris Toney [aut, cre], Frank Warmerdam [ctb, cph] , Even Rouault [ctb, cph] , Marius Appel [ctb, cph] , Daniel James [ctb, cph] , Peter Dimov [ctb, cph]
Maintainer: Chris Toney <chris.toney@usda.gov>

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Package echarty updated to version 1.5.4 with previous version 1.5.0 dated 2022-11-24

Title: Minimal R/Shiny Interface to JavaScript Library 'ECharts'
Description: Deliver the full functionality of 'ECharts' with minimal overhead. 'echarty' users build R lists for 'ECharts' API. Lean set of powerful commands.
Author: Larry Helgason, with initial code from John Coene's library echarts4r
Maintainer: Larry Helgason <larry@helgasoft.com>

Diff between echarty versions 1.5.0 dated 2022-11-24 and 1.5.4 dated 2023-05-28

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New package crosstable with initial version 0.6.2
Package: crosstable
Title: Crosstables for Descriptive Analyses
Version: 0.6.2
Description: Create descriptive tables for continuous and categorical variables. Apply summary statistics and counting function, with or without a grouping variable, and create beautiful reports using 'rmarkdown' or 'officer'. You can also compute effect sizes and statistical tests if needed.
License: GPL-3
URL: https://danchaltiel.github.io/crosstable/, https://github.com/DanChaltiel/crosstable/
BugReports: https://github.com/DanChaltiel/crosstable/issues/
Depends: R (>= 3.1.0)
Imports: checkmate (>= 1.9.0), cli (>= 3.0.0), dplyr (>= 1.1.0), flextable (>= 0.5.1), forcats (>= 1.0.0), glue (>= 1.3.0), lifecycle (>= 0.2.0), methods, officer (>= 0.4.0), purrr (>= 0.2.3), rlang (>= 1.0.0), stats, stringr (>= 1.4.0), tibble (>= 1.1), tidyr (>= 1.0.0), utils,
Suggests: callr, covr, crayon, xml2, digest, gt, expss, ggplot2, gmodels, Hmisc, jsonlite, knitr, openxlsx, rmarkdown, sloop, stringi, survival, systemfonts, tidyselect, testthat (>= 3.0.0), withr, waldo
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2023-05-27 08:29:22 UTC; Dan
Author: Dan Chaltiel [aut, cre] , David Hajage [ccp]
Maintainer: Dan Chaltiel <dan.chaltiel@gmail.com>
Repository: CRAN
Date/Publication: 2023-05-28 23:50:02 UTC

More information about crosstable at CRAN
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Package hpfilter updated to version 1.0.2 with previous version 1.0.1 dated 2023-02-25

Title: The One- And Two-Sided Hodrick-Prescott Filter
Description: Provides two functions that implement the one-sided and two-sided versions of the Hodrick-Prescott filter. The one-sided version is a Kalman filter-based implementation, whereas the two- sided version uses sparse matrices for improved efficiency. References: Hodrick, R. J., and Prescott, E. C. (1997) <doi:10.2307/2953682> Mcelroy, T. (2008) <doi:10.1111/j.1368-423X.2008.00230.x> Meyer-Gohde, A. (2010) <https://ideas.repec.org/c/dge/qmrbcd/181.html> For more references, see the vignette.
Author: Alexandru Monahov
Maintainer: Alexandru Monahov <alexandru.monahov@proton.me>

Diff between hpfilter versions 1.0.1 dated 2023-02-25 and 1.0.2 dated 2023-05-28

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Package dogesr updated to version 0.3.0 with previous version 0.2.0 dated 2023-02-21

Title: Work with the Doges/Dogaresse Dataset
Description: Work with data on Venetian doges and dogaresse and the noble families of the Republic of Venice, and use it for social network analysis, as used in Merelo (2022) <arXiv:2209.07334>.
Author: Juan Julian Merelo-Guervos
Maintainer: Juan Julian Merelo-Guervos <jjmerelo@gmail.com>

Diff between dogesr versions 0.2.0 dated 2023-02-21 and 0.3.0 dated 2023-05-28

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Package sentopics updated to version 0.7.2 with previous version 0.7.1 dated 2022-05-18

Title: Tools for Joint Sentiment and Topic Analysis of Textual Data
Description: A framework that joins topic modeling and sentiment analysis of textual data. The package implements a fast Gibbs sampling estimation of Latent Dirichlet Allocation (Griffiths and Steyvers (2004) <doi:10.1073/pnas.0307752101>) and Joint Sentiment/Topic Model (Lin, He, Everson and Ruger (2012) <doi:10.1109/TKDE.2011.48>). It offers a variety of helpers and visualizations to analyze the result of topic modeling. The framework also allows enriching topic models with dates and externally computed sentiment measures. A flexible aggregation scheme enables the creation of time series of sentiment or topical proportions from the enriched topic models. Moreover, a novel method jointly aggregates topic proportions and sentiment measures to derive time series of topical sentiment.
Author: Olivier Delmarcelle [aut, cre] , Samuel Borms [ctb] , Chengua Lin [cph] , Yulan He [cph] , Jose Bernardo [cph] , David Robinson [cph] ), Julia Silge [cph] , <https://orcid.org/0000-0002-3671-836X>)
Maintainer: Olivier Delmarcelle <delmarcelle.olivier@gmail.com>

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Package ergm updated to version 4.5.0 with previous version 4.4.0 dated 2023-01-27

Title: Fit, Simulate and Diagnose Exponential-Family Models for Networks
Description: An integrated set of tools to analyze and simulate networks based on exponential-family random graph models (ERGMs). 'ergm' is a part of the Statnet suite of packages for network analysis. See Hunter, Handcock, Butts, Goodreau, and Morris (2008) <doi:10.18637/jss.v024.i03> and Krivitsky, Hunter, Morris, and Klumb (2023) <doi:10.18637/jss.v105.i06>.
Author: Mark S. Handcock [aut], David R. Hunter [aut], Carter T. Butts [aut], Steven M. Goodreau [aut], Pavel N. Krivitsky [aut, cre] , Martina Morris [aut], Li Wang [ctb], Kirk Li [ctb], Skye Bender-deMoll [ctb], Chad Klumb [ctb], Michal Bojanowski [ctb] , [...truncated...]
Maintainer: Pavel N. Krivitsky <pavel@statnet.org>

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Package collapse updated to version 1.9.6 with previous version 1.9.5 dated 2023-04-07

Title: Advanced and Fast Data Transformation
Description: A C/C++ based package for advanced data transformation and statistical computing in R that is extremely fast, class-agnostic, and programmer friendly through a flexible and robust API. Core functionality includes a rich set of S3 generic grouped and weighted statistical functions for vectors, matrices and data frames, which provide efficient low-level vectorizations, OpenMP multithreading, and skip missing values by default. These are integrated with fast grouping and ordering algorithms (also callable from C), and efficient data manipulation functions. The package also provides a flexible and rigorous approach to time series and panel data in R. It further includes fast functions for common statistical procedures, detailed (grouped, weighted) summary statistics, powerful tools to work with nested data, fast data object conversions, functions for memory efficient R programming, and helpers to effectively deal with variable labels, attributes, and missing data. It is well integrated wit [...truncated...]
Author: Sebastian Krantz [aut, cre], Matt Dowle [ctb], Arun Srinivasan [ctb], Morgan Jacob [ctb], Dirk Eddelbuettel [ctb], Laurent Berge [ctb], Kevin Tappe [ctb], R Core Team and contributors worldwide [ctb], Martyn Plummer [cph], 1999-2016 The R Core Team [ [...truncated...]
Maintainer: Sebastian Krantz <sebastian.krantz@graduateinstitute.ch>

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Package RcmdrPlugin.WorldFlora updated to version 1.3 with previous version 1.2 dated 2022-09-07

Title: R Commander Plug-in for the 'WorldFlora' Package
Description: An R Commander plug-in for the 'WorldFlora' package. It was mainly developed to show work flows and scripts for first-time users.
Author: Roeland Kindt [cre, aut]
Maintainer: Roeland Kindt <RoelandCEKindt@gmail.com>

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Package glmnetr (with last version 0.2-0) was removed from CRAN

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

2023-05-10 0.2-0
2023-02-18 0.1-2
2022-12-14 0.1-1

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Package eiCompare (with last version 3.0.1) was removed from CRAN

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

2023-03-28 3.0.1

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Package censusxy (with last version 1.1.1) was removed from CRAN

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

2022-12-06 1.1.1
2022-05-30 1.1.0
2021-02-18 1.0.1
2020-05-28 1.0.0
2019-08-09 0.1.2

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Package dynamite (with last version 1.4.2) was removed from CRAN

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

2023-05-18 1.4.2
2023-05-10 1.4.1
2023-04-18 1.3.3
2023-03-31 1.3.1
2023-02-03 1.1.1
2022-12-23 1.0.1

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Package augmentedRCBD updated to version 0.1.6 with previous version 0.1.5 dated 2021-06-12

Title: Analysis of Augmented Randomised Complete Block Designs
Description: Functions for analysis of data generated from experiments in augmented randomised complete block design according to Federer, W.T. (1961) <doi:10.2307/2527837>. Computes analysis of variance, adjusted means, descriptive statistics, genetic variability statistics etc. Further includes data visualization and report generation functions.
Author: J. Aravind [aut, cre] , S. Mukesh Sankar [aut], Dhammaprakash Pandhari Wankhede [aut] , Vikender Kaur [aut], ICAR-NBGPR [cph]
Maintainer: J. Aravind <j.aravind@icar.gov.in>

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More information about augmentedRCBD at CRAN
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Package ODRF updated to version 0.0.4 with previous version 0.0.3 dated 2023-03-16

Title: Oblique Decision Random Forest for Classification and Regression
Description: The oblique decision tree (ODT) uses linear combinations of predictors as partitioning variables in a decision tree. Oblique Decision Random Forest (ODRF) is an ensemble of multiple ODTs generated by feature bagging. Both can be used for classification and regression as supplements to the classical CART of Breiman (1984) <DOI:10.1201/9781315139470> and Random Forest of Breiman (2001) <DOI:10.1023/A:1010933404324> respectively.
Author: Yu Liu [aut, cre, cph], Yingcun Xia [aut]
Maintainer: Yu Liu <liuyuchina123@gmail.com>

Diff between ODRF versions 0.0.3 dated 2023-03-16 and 0.0.4 dated 2023-05-28

 DESCRIPTION                                  |   11 
 MD5                                          |   69 +++---
 NEWS.md                                      |   10 
 R/Accuracy.R                                 |   34 +--
 R/ODRF.R                                     |  110 ++++-----
 R/ODT.R                                      |   96 ++++++--
 R/RotMat.R                                   |    4 
 R/VarImp.R                                   |  298 ++++++++++++++++-----------
 R/as_party_ODT.R                             |   36 +--
 R/best_cut_node.R                            |    4 
 R/defaults.R                                 |    9 
 R/online_ODRF.R                              |  109 +++++----
 R/online_ODT.R                               |  100 ++++++---
 R/plot_ODT.R                                 |    2 
 R/predictTree.R                              |only
 R/predict_ODRF.R                             |   82 ++++---
 R/predict_ODT.R                              |  124 ++++-------
 R/print_ODRF.R                               |    2 
 R/prune_ODRF.R                               |  110 +++++----
 R/prune_ODT.R                                |   92 +++-----
 inst/WORDLIST                                |    4 
 inst/doc/Oblique-Decision-Random-Forest.html |   79 +++----
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 man/VarImp.Rd                                |   36 ++-
 man/best.cut.node.Rd                         |    4 
 man/online.ODRF.Rd                           |    4 
 man/online.ODT.Rd                            |    4 
 man/predict.ODRF.Rd                          |    5 
 src/gini_split.cpp                           |   11 
 src/infogain_split.cpp                       |   12 -
 src/mse_split.cpp                            |   12 -
 tests/testthat/test-ODRF.R                   |    4 
 tests/testthat/test-ODT.R                    |   13 -
 tests/testthat/test-predict_ODRF.R           |    4 
 tests/testthat/test-predict_ODT.R            |    6 
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