Sat, 06 May 2023

Package ORKM updated to version 0.6.0.0 with previous version 0.4.0.0 dated 2022-07-19

Title: The Online Regularized K-Means Clustering Algorithm
Description: Algorithm of online regularized k-means to deal with online multi(single) view data. The philosophy of the package is described in Guo G. (2020) <doi:10.1080/02331888.2020.1823979>.
Author: Guangbao Guo [aut, cre] , Miao Yu [aut], Haoyue Song [aut], Ruiling Niu [aut]
Maintainer: Guangbao Guo <ggb11111111@163.com>

Diff between ORKM versions 0.4.0.0 dated 2022-07-19 and 0.6.0.0 dated 2023-05-06

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Package hypervolume updated to version 3.1.1 with previous version 3.1.0 dated 2022-11-15

Title: High Dimensional Geometry, Set Operations, Projection, and Inference Using Kernel Density Estimation, Support Vector Machines, and Convex Hulls
Description: Estimates the shape and volume of high-dimensional datasets and performs set operations: intersection / overlap, union, unique components, inclusion test, and hole detection. Uses stochastic geometry approach to high-dimensional kernel density estimation, support vector machine delineation, and convex hull generation. Applications include modeling trait and niche hypervolumes and species distribution modeling.
Author: Benjamin Blonder, with contributions from Cecina Babich Morrow, David J. Harris, Stuart Brown, Gregoire Butruille, Alex Laini, and Dan Chen
Maintainer: Benjamin Blonder <benjamin.blonder@berkeley.edu>

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Package wk updated to version 0.7.3 with previous version 0.7.2 dated 2023-03-17

Title: Lightweight Well-Known Geometry Parsing
Description: Provides a minimal R and C++ API for parsing well-known binary and well-known text representation of geometries to and from R-native formats. Well-known binary is compact and fast to parse; well-known text is human-readable and is useful for writing tests. These formats are useful in R only if the information they contain can be accessed in R, for which high-performance functions are provided here.
Author: Dewey Dunnington [aut, cre] , Edzer Pebesma [aut]
Maintainer: Dewey Dunnington <dewey@fishandwhistle.net>

Diff between wk versions 0.7.2 dated 2023-03-17 and 0.7.3 dated 2023-05-06

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Package nanonext updated to version 0.8.3 with previous version 0.8.2 dated 2023-04-14

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 rpostgis updated to version 1.4.4 with previous version 1.4.3 dated 2019-11-20

Title: R Interface to a 'PostGIS' Database
Description: Provides an interface between R and 'PostGIS'-enabled 'PostgreSQL' databases to transparently transfer spatial data. Both vector (points, lines, polygons) and raster data are supported in read and write modes. Also provides convenience functions to execute common procedures in 'PostgreSQL/PostGIS'.
Author: Mathieu Basille [aut] , David Bucklin [aut, cre]
Maintainer: David Bucklin <david.bucklin@gmail.com>

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Package mark updated to version 0.6.0 with previous version 0.5.3 dated 2022-10-16

Title: Miscellaneous, Analytic R Kernels
Description: Miscellaneous functions and wrappers for development in other packages created, maintained by Jordan Mark Barbone.
Author: Jordan Mark Barbone [aut, cph, cre]
Maintainer: Jordan Mark Barbone <jmbarbone@gmail.com>

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Package RobLoxBioC updated to version 1.2.1 with previous version 1.2.0 dated 2019-04-11

Title: Infinitesimally Robust Estimators for Preprocessing -Omics Data
Description: Functions for the determination of optimally robust influence curves and estimators for preprocessing omics data, in particular gene expression data.
Author: Matthias Kohl [aut, cre, cph]
Maintainer: Matthias Kohl <Matthias.Kohl@stamats.de>

Diff between RobLoxBioC versions 1.2.0 dated 2019-04-11 and 1.2.1 dated 2023-05-06

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Package jmvReadWrite updated to version 0.3.4 with previous version 0.3.3 dated 2022-08-09

Title: Read and Write 'jamovi' Files ('.omv')
Description: The free and open a statistical spreadsheet 'jamovi' (<https://www.jamovi.org>) aims to make statistical analyses easy and intuitive. 'jamovi' produces syntax that can directly be used in R (in connection with the R-package 'jmv'). Having import / export routines for the data files 'jamovi' produces ('.omv') permits an easy transfer of analyses between 'jamovi' and R.
Author: Sebastian Jentschke [aut, cre]
Maintainer: Sebastian Jentschke <sebastian.jentschke@uib.no>

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Package visvow updated to version 1.3.9 with previous version 1.3.8 dated 2023-04-19

Title: Visible Vowels: Visualization of Vowel Variation
Description: Visualizes vowel variation in f0, F1, F2, F3 and duration.
Author: Wilbert Heeringa [aut, cre], Hans Van de Velde [aut]
Maintainer: Wilbert Heeringa <wheeringa@fryske-akademy.nl>

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Package lifecontingencies updated to version 1.3.10 with previous version 1.3.9 dated 2022-06-10

Title: Financial and Actuarial Mathematics for Life Contingencies
Description: Classes and methods that allow the user to manage life table, actuarial tables (also multiple decrements tables). Moreover, functions to easily perform demographic, financial and actuarial mathematics on life contingencies insurances calculations are contained therein. See Spedicato (2013) <doi:10.18637/jss.v055.i10>.
Author: Giorgio Alfredo Spedicato [aut, cre] , Christophe Dutang [ctb] , Reinhold Kainhofer [ctb] , Kevin J Owens [ctb], Ernesto Schirmacher [ctb], Gian Paolo Clemente [ctb] , Ivan Williams [ctb]
Maintainer: Giorgio Alfredo Spedicato <spedicato_giorgio@yahoo.it>

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Package sasLM updated to version 0.9.8 with previous version 0.9.7 dated 2023-04-05

Title: 'SAS' Linear Model
Description: This is a core implementation of 'SAS' procedures for linear models - GLM, REG, ANOVA, FREQ, and UNIVARIATE. Some R packages provide type II and type III SS. However, the results of nested and complex designs are often different from those of 'SAS.' Different results does not necessarily mean incorrectness. However, many wants the same results to SAS. This package aims to achieve that. Reference: Littell RC, Stroup WW, Freund RJ (2002, ISBN:0-471-22174-0).
Author: Kyun-Seop Bae [aut]
Maintainer: Kyun-Seop Bae <k@acr.kr>

Diff between sasLM versions 0.9.7 dated 2023-04-05 and 0.9.8 dated 2023-05-06

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New package speedglm with initial version 0.3-5
Package: speedglm
Title: Fitting Linear and Generalized Linear Models to Large Data Sets
Version: 0.3-5
Date: 2023-04-20
Author: Marco Enea [aut, cre], Ronen Meiri [ctb] , Tomer Kalimi [ctb]
Maintainer: Marco Enea <marco.enea@unipa.it>
Depends: Matrix, MASS, biglm
Imports: methods, stats
Description: Fitting linear models and generalized linear models to large data sets by updating algorithms, according to the method described in Enea (2009, ISBN: 9788861294257).
License: GPL
LazyLoad: yes
NeedsCompilation: no
Packaged: 2023-04-20 14:31:45 UTC; Marco Enea
Repository: CRAN
Date/Publication: 2023-05-06 10:10:02 UTC

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Package netmeta updated to version 2.8-2 with previous version 2.8-1 dated 2023-03-16

Title: Network Meta-Analysis using Frequentist Methods
Description: A comprehensive set of functions providing frequentist methods for network meta-analysis (Balduzzi et al., 2023) <doi:10.18637/jss.v106.i02> and supporting Schwarzer et al. (2015) <doi:10.1007/978-3-319-21416-0>, Chapter 8 "Network Meta-Analysis": - frequentist network meta-analysis following Rücker (2012) <doi:10.1002/jrsm.1058>; - additive network meta-analysis for combinations of treatments (Rücker et al., 2020) <doi:10.1002/bimj.201800167>; - network meta-analysis of binary data using the Mantel-Haenszel or non-central hypergeometric distribution method (Efthimiou et al., 2019) <doi:10.1002/sim.8158>; - rankograms and ranking of treatments by the Surface under the cumulative ranking curve (SUCRA) (Salanti et al., 2013) <doi:10.1016/j.jclinepi.2010.03.016>; - ranking of treatments using P-scores (frequentist analogue of SUCRAs without resampling) according to Rücker & Schwarzer (2015) <doi:10.1186/s12874-015-0060-8>; - split direct and i [...truncated...]
Author: Gerta Ruecker [aut] , Ulrike Krahn [aut], Jochem Koenig [aut] , Orestis Efthimiou [aut] , Annabel Davies [aut] , Theodoros Papakonstantinou [aut] , Guido Schwarzer [aut, cre]
Maintainer: Guido Schwarzer <guido.schwarzer@uniklinik-freiburg.de>

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Package eurodata updated to version 1.7.0 with previous version 1.6.1 dated 2023-01-23

Title: Fast and Easy Eurostat Data Import and Search
Description: Interface to Eurostat’s API (SDMX 2.1) with fast data.table-based import of data, labels, and metadata. On top of the core functionality, data search and data description/comparison functions are also provided. Use <https://github.com/alekrutkowski/eurodata_codegen> — a point-and-click app for rapid and easy generation of richly-commented R code — to import a Eurostat dataset or its subset (based on the eurodata::importData() function).
Author: Aleksander Rutkowski [aut, cre]
Maintainer: Aleksander Rutkowski <alek.rutkowski@gmail.com>

Diff between eurodata versions 1.6.1 dated 2023-01-23 and 1.7.0 dated 2023-05-06

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Package bda (with last version 15.2.5) was removed from CRAN

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

2021-08-19 15.2.5
2021-01-19 15.2.2
2020-09-30 15.1.7
2020-07-27 15.0.2
2020-03-30 14.3.19
2020-02-06 14.1.4

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Package oops (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:

2022-03-02 0.2.0
2021-12-22 0.1.0

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Package excel.link (with last version 0.9.10) was removed from CRAN

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

2021-11-02 0.9.10
2021-03-21 0.9.9
2018-05-23 0.9.8-1
2017-05-01 0.9.7
2016-09-24 0.9.5
2016-04-15 0.9.4
2015-12-06 0.9.3
2015-07-14 0.9.1
2015-05-06 0.8.1
2013-09-05 0.6
2013-04-15 0.5.4
2012-08-23 0.5.2

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Package snapKrig updated to version 0.0.2 with previous version 0.0.1 dated 2023-01-09

Title: Fast Kriging and Geostatistics on Grids with Kronecker Covariance
Description: Geostatistical modeling and kriging with gridded data using spatially separable covariance functions (Kronecker covariances). Kronecker products in these models provide shortcuts for solving large matrix problems in likelihood and conditional mean, making 'snapKrig' computationally efficient with large grids. The package supplies its own S3 grid object class, and a host of methods including plot, print, Ops, square bracket replace/assign, and more. Our computational methods are described in Koch, Lele, Lewis (2020) <doi:10.7939/r3-g6qb-bq70>.
Author: Dean Koch [aut, cre, cph]
Maintainer: Dean Koch <dkoch@ualberta.ca>

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Package pathfindR updated to version 2.0.0 with previous version 1.6.4 dated 2022-08-25

Title: Enrichment Analysis Utilizing Active Subnetworks
Description: Enrichment analysis enables researchers to uncover mechanisms underlying a phenotype. However, conventional methods for enrichment analysis do not take into account protein-protein interaction information, resulting in incomplete conclusions. pathfindR is a tool for enrichment analysis utilizing active subnetworks. The main function identifies active subnetworks in a protein-protein interaction network using a user-provided list of genes and associated p values. It then performs enrichment analyses on the identified subnetworks, identifying enriched terms (i.e. pathways or, more broadly, gene sets) that possibly underlie the phenotype of interest. pathfindR also offers functionalities to cluster the enriched terms and identify representative terms in each cluster, to score the enriched terms per sample and to visualize analysis results. The enrichment, clustering and other methods implemented in pathfindR are described in detail in Ulgen E, Ozisik O, Sezerman OU. 2019. pathfindR: An R [...truncated...]
Author: Ege Ulgen [cre, cph] , Ozan Ozisik [aut]
Maintainer: Ege Ulgen <egeulgen@gmail.com>

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Package ijtiff updated to version 2.3.1 with previous version 2.3.0 dated 2023-01-16

Title: Comprehensive TIFF I/O with Full Support for 'ImageJ' TIFF Files
Description: General purpose TIFF file I/O for R users. Currently the only such package with read and write support for TIFF files with floating point (real-numbered) pixels, and the only package that can correctly import TIFF files that were saved from 'ImageJ' and write TIFF files than can be correctly read by 'ImageJ' <https://imagej.nih.gov/ij/>. Also supports text image I/O.
Author: Rory Nolan [aut, cre] , Kent Johnson [aut], Simon Urbanek [ctb], Sergi Padilla-Parra [ths] , Jeroen Ooms [rev, ctb] , Jon Clayden [rev]
Maintainer: Rory Nolan <rorynoolan@gmail.com>

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Package bqror updated to version 1.6.1 with previous version 1.6.0 dated 2023-03-25

Title: Bayesian Quantile Regression for Ordinal Models
Description: Package provides functions for estimation and inference in Bayesian quantile regression with ordinal outcomes. An ordinal model with 3 or more outcomes (labeled OR1 model) is estimated by a combination of Gibbs sampling and Metropolis-Hastings (MH) algorithm. Whereas an ordinal model with exactly 3 outcomes (labeled OR2 model) is estimated using a Gibbs sampling algorithm. The summary output presents the posterior mean, posterior standard deviation, 95% credible intervals, and the inefficiency factors along with the two model comparison measures – logarithm of marginal likelihood and the deviance information criterion (DIC). The package also provides functions for computing the covariate effects and other functions that aids either the estimation or inference in quantile ordinal models. Rahman, M. A. (2016).“Bayesian Quantile Regression for Ordinal Models.” Bayesian Analysis, 11(1): 1-24 <doi: 10.1214/15-BA939>. Yu, K., and Moyeed, R. A. (2001). “Bayesian Quantile Regression.” St [...truncated...]
Author: Mohammad Arshad Rahman Developer [aut], Prajual Maheshwari [cre]
Maintainer: Prajual Maheshwari <prajual1391@gmail.com>

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