Wed, 01 Jul 2026

Package vectra updated to version 0.9.8 with previous version 0.9.1 dated 2026-06-29

Title: Columnar Query Engine for Larger-than-RAM Data
Description: A minimal columnar query engine with lazy execution on datasets larger than RAM. Provides 'dplyr'-like verbs (filter(), select(), mutate(), group_by(), summarise(), joins, window functions) and common aggregations (n(), sum(), mean(), min(), max(), sd(), first(), last()) backed by a pure C11 pull-based execution engine and a custom on-disk format ('.vtr'). Reads and writes 'GeoTIFF' (including tiled and 'BigTIFF' layouts) and a tiled raster format ('.vec') with overview pyramids and time cubes for larger-than-RAM raster data. Streams vector operations (spatial transforms, point-in-polygon and nearest-feature joins including a two-sided grid-partitioned join, select-by-location, clip, erase, dissolve, 'rasterization', 'polygonization', and contouring) through 'sf', and runs raster operations (zonal statistics, focal windows, terrain derivatives, resample or 'reproject' warp, polygon masking, map algebra, and 'mosaicking') in native C or over the tiled '.vec' format, one batch or tile at [...truncated...]
Author: Gilles Colling [aut, cre, cph]
Maintainer: Gilles Colling <gilles.colling051@gmail.com>

Diff between vectra versions 0.9.1 dated 2026-06-29 and 0.9.8 dated 2026-07-01

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New package trackclean with initial version 0.1.0
Package: trackclean
Title: Tools for Cleaning High-Frequency Real-Time Location Tracking Data
Version: 0.1.0
Description: Provides data cleaning and preprocessing tools for high-frequency positional data from real-time location tracking systems (UWB, RFID, and similar technologies), with functions for ID mapping, time period marking, data standardization, and two-phase conditional gap interpolation. See Bilevicius (2026) <doi:10.5281/zenodo.20783488>.
License: CC BY 4.0
URL: https://github.com/tomasbil/trackclean
BugReports: https://github.com/tomasbil/trackclean/issues
Encoding: UTF-8
Language: en-US
Imports: dplyr, lubridate, magrittr, readr, rlang, tibble
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-06-26 08:09:33 UTC; tomas
Author: Tomas Bilevicius [aut, cre]
Maintainer: Tomas Bilevicius <Tomas.Bilevicius@vub.be>
Repository: CRAN
Date/Publication: 2026-07-01 09:40:02 UTC

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Package structenforcement updated to version 0.3.1 with previous version 0.3.0 dated 2026-06-30

Title: Struct-Like Data Type Checking and Enforcement
Description: Enforcement of field types in lists. A drop-in tool to allow for dynamic input data that might be questionably parsed or cast to be coerced into the specific desired format in a reasonably performant manner.
Author: Samuel Sapire [aut, cre, cph], Sean Barrett [ctb]
Maintainer: Samuel Sapire <sapires@protonmail.com>

Diff between structenforcement versions 0.3.0 dated 2026-06-30 and 0.3.1 dated 2026-07-01

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New package saeHB.Spatial.Beta with initial version 0.1.0
Package: saeHB.Spatial.Beta
Title: Small Area Estimation Hierarchical Bayes for Spatial Beta Model
Version: 0.1.0
Description: Provides several functions and datasets for area-level Small Area Estimation using the Hierarchical Bayesian (HB) method. Model-based estimators are designed for variables of interest that follow a Beta distribution. The package supports spatial structures under the Simultaneous Autoregressive (SAR) and Leroux Conditional Autoregressive (CAR) models, accommodating survey design effect (DEFF) adjustments. The 'rjags' package is employed to obtain parameter estimates via Gibbs Sampling. For references, see Rao and Molina (2015) <doi:10.1002/9781118735855>, Kubacki and Jedrzejczak (2016) <doi:10.59170/stattrans-2016-022>, Leroux et al. (2000) <doi:10.1007/978-1-4612-1284-3_4>, and Chung and Datta (2020) <https://www.census.gov/content/dam/Census/library/working-papers/2020/adrm/RRS2020-07.pdf>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1.0)
Imports: rjags, coda, stats, grDevices, graphics, sf, spdep
SystemRequirements: JAGS (http://mcmc-jags.sourceforge.net)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), ggplot2
VignetteBuilder: knitr
URL: https://github.com/BobyIwan/saeHB.Spatial.Beta
BugReports: https://github.com/BobyIwan/saeHB.Spatial.Beta/issues
NeedsCompilation: no
Packaged: 2026-06-14 06:01:44 UTC; diann
Author: Boby Iwan [aut, cre], Cucu Sumarni [aut]
Maintainer: Boby Iwan <bobyiwanboby2122@gmail.com>
Repository: CRAN
Date/Publication: 2026-07-01 09:30:07 UTC

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New package rtransparency with initial version 1.0.0
Package: rtransparency
Title: Identifies Indicators of Transparency
Version: 1.0.0
Description: Use this package to identify indicators of transparency within the published literature. It can identify and extract text related to indicators of transparency from specifically formatted TXT files and from PMC XML files (i.e. XML files downloaded from the PubMed Central). It builds on the original 'rtransparent' tool of Serghiou et al. (2021) <doi:10.1371/journal.pbio.3001107>.
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/choxos/rtransparency, https://choxos.github.io/rtransparency/
BugReports: https://github.com/choxos/rtransparency/issues
Depends: R (>= 3.5.0)
Imports: dplyr, magrittr, purrr, readr, rlang, stringr, tibble, tidyselect, utf8, xml2
Suggests: furrr, future, ggplot2, knitr, readxl, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-06-25 11:35:18 UTC; choxos
Author: Stylianos Serghiou [aut], Ahmad Sofi-Mahmudi [cre, aut]
Maintainer: Ahmad Sofi-Mahmudi <a.sofimahmudi@gmail.com>
Repository: CRAN
Date/Publication: 2026-07-01 09:00:02 UTC

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New package rfair with initial version 0.1.0
Package: rfair
Title: Assess the FAIRness of Research Data Objects and Software
Version: 0.1.0
Description: A native R implementation of the F-UJI (FAIRsFAIR Research Data Object Assessment) and FRSM (FAIR for Research Software) metrics for evaluating how well a research data object or piece of research software satisfies the FAIR principles (Findable, Accessible, Interoperable, Reusable). The software metrics operationalize the FAIR Principles for Research Software (FAIR4RS) of Chue Hong et al. (2022) <doi:10.15497/RDA00068>. Given a persistent identifier, URL, or code repository, 'rfair' resolves it, harvests metadata from landing pages and registries, and scores it against the FAIRsFAIR metrics of Devaraju and Huber (2020) <doi:10.5281/zenodo.3775793> entirely in R, without requiring an external assessment server. 'rfair' began as a fork of the 'rfuji' F-UJI API client and reimplements the assessment engine natively.
License: GPL-3
URL: https://github.com/choxos/rfair, https://choxos.github.io/rfair/
BugReports: https://github.com/choxos/rfair/issues
Depends: R (>= 4.1)
Imports: digest, httr2, jsonlite, mime, rvest, stats, stringdist, utils, xml2, yaml
Suggests: bslib, chromote, covr, DT, httptest2, jqr, knitr, plumber, rdflib, rmarkdown, shiny, testthat (>= 3.0.0), wand
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2026-06-25 11:44:53 UTC; choxos
Author: Ahmad Sofi-Mahmudi [aut, cre] , Steffen Neumann [ctb] , PANGAEA [cph]
Maintainer: Ahmad Sofi-Mahmudi <a.sofimahmudi@gmail.com>
Repository: CRAN
Date/Publication: 2026-07-01 09:10:02 UTC

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New package palsr with initial version 0.1.0
Package: palsr
Title: Projected Actor Locations for Spatial Interaction Modeling
Version: 0.1.0
Description: Implements the Projected Actor Locations (PALS) method for spatial modeling of dyadic interactions between geographically mobile actors, as described in Kim, Liu and Desmarais (2023) <doi:10.1017/psrm.2022.6>. PALS applies exponential-smoothing weights to the spatiotemporal histories of a focal actor and its interaction partners ("alters") to project the location of future interactions. The package provides projection, maximum-similarity parameter estimation by minimizing great-circle (Haversine) prediction error, nonparametric bootstrap with multiple-imputation (Rubin's Rules) pooling, dyadic distance covariate construction, visualization, and a simulated example dataset of subnational conflict.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1.0)
Imports: Rcpp, stats
LinkingTo: Rcpp
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, mice, ggplot2
URL: https://github.com/bdesmarais/palsr
BugReports: https://github.com/bdesmarais/palsr/issues
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-06-25 11:47:24 UTC; bbd5087
Author: Bruce A. Desmarais [aut, cre], Sangyeon Kim [aut], Howard Liu [aut]
Maintainer: Bruce A. Desmarais <bruce.desmarais@gmail.com>
Repository: CRAN
Date/Publication: 2026-07-01 10:00:13 UTC

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Package doBy updated to version 4.7.2 with previous version 4.7.1 dated 2025-12-02

Title: Groupwise Statistics, LSmeans, Linear Estimates, Utilities
Description: Utility package containing: Main categories: Working with grouped data: 'do' something to data when stratified 'by' some variables. General linear estimates. Data handling utilities. Functional programming, in particular restrict functions to a smaller domain. Miscellaneous functions for data handling. Model stability in connection with model selection. Miscellaneous other tools.
Author: Ulrich Halekoh [aut, cph], Soeren Hoejsgaard [aut, cre, cph]
Maintainer: Soeren Hoejsgaard <sorenh@math.aau.dk>

Diff between doBy versions 4.7.1 dated 2025-12-02 and 4.7.2 dated 2026-07-01

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New package axprism with initial version 0.2.0
Package: axprism
Title: Client for the 'AxPrism' Institutional XBRL and Shariah Compliance API
Version: 0.2.0
Description: Provides an R client for the 'AxPrism' Application Programming Interface (API) (<https://axprism.com>), which serves institutional financial data in the eXtensible Business Reporting Language (XBRL) format together with Shariah compliance screening. Supported compliance rulesets include those of the Accounting and Auditing Organization for Islamic Financial Institutions (AAOIFI), the Morgan Stanley Capital International (MSCI) Islamic methodology, the Dow Jones Islamic Market (DJIM), the Financial Times Stock Exchange (FTSE) and the Saudi Capital Market Authority (CMA). Convenience functions wrap company fundamentals, compliance verdicts and portfolio screening, company profiles, equity screeners, regulatory disclosures and filing text search, and the Tadawul (Saudi Exchange), Bursa Malaysia and Indonesia Stock Exchange (IDX) markets, as well as webhooks and bulk data export. Requests use 'X-API-Key' header authentication, automatic retries with exponential backoff, and a generic [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://axprism.com, https://axprism.com/api-reference
BugReports: https://axprism.com/contact
Imports: httr, jsonlite
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-06-26 01:30:20 UTC; code
Author: Marco Corleone [aut, cre]
Maintainer: Marco Corleone <dev@axprism.com>
Repository: CRAN
Date/Publication: 2026-07-01 09:20:02 UTC

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Package teal.modules.general updated to version 0.7.0 with previous version 0.6.0 dated 2025-12-03

Title: General Modules for 'teal' Applications
Description: Prebuilt 'shiny' modules containing tools for viewing data, visualizing data, understanding missing and outlier values within your data and performing simple data analysis. This extends 'teal' framework that supports reproducible research and analysis.
Author: Dony Unardi [aut, cre], Dawid Kaledkowski [aut], Pawel Rucki [aut], Mahmoud Hallal [aut], Ondrej Slama [ctb], Maciej Nasinski [aut], Konrad Pagacz [aut], Nikolas Burkoff [aut], F. Hoffmann-La Roche AG [cph, fnd]
Maintainer: Dony Unardi <unardid@gene.com>

Diff between teal.modules.general versions 0.6.0 dated 2025-12-03 and 0.7.0 dated 2026-07-01

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Package surveillance updated to version 1.26.0 with previous version 1.25.0 dated 2025-06-25

Title: Temporal and Spatio-Temporal Modeling and Monitoring of Epidemic Phenomena
Description: Statistical methods for the modeling and monitoring of time series of counts, proportions and categorical data, as well as for the modeling of continuous-time point processes of epidemic phenomena. The monitoring methods focus on aberration detection in count data time series from public health surveillance of communicable diseases, but applications could just as well originate from environmetrics, reliability engineering, econometrics, or social sciences. The package implements many typical outbreak detection procedures such as the (improved) Farrington algorithm, or the negative binomial GLR-CUSUM method of Hoehle and Paul (2008) <doi:10.1016/j.csda.2008.02.015>. A novel CUSUM approach combining logistic and multinomial logistic modeling is also included. The package contains several real-world data sets, the ability to simulate outbreak data, and to visualize the results of the monitoring in a temporal, spatial or spatio-temporal fashion. A recent overview of the available mon [...truncated...]
Author: Michael Hoehle [aut, ths] , Sebastian Meyer [aut, cre] , Michaela Paul [aut], Leonhard Held [ctb, ths] , Howard Burkom [ctb], Thais Correa [ctb], Mathias Hofmann [ctb], Christian Lang [ctb], Juliane Manitz [ctb], Sophie Reichert [ctb], Andrea Riebler [...truncated...]
Maintainer: Sebastian Meyer <seb.meyer@fau.de>

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Package statgenHTP updated to version 1.0.9.3 with previous version 1.0.9.2 dated 2026-05-21

Title: High Throughput Phenotyping (HTP) Data Analysis
Description: Phenotypic analysis of data coming from high throughput phenotyping (HTP) platforms, including different types of outlier detection, spatial analysis, and parameter estimation. The package is being developed within the EPPN2020 project (<https://cordis.europa.eu/project/id/731013>). Some functions have been created to be used in conjunction with the R package 'asreml' for the 'ASReml' software, which can be obtained upon purchase from 'VSN' international (<https://vsni.co.uk/software/asreml-r/>).
Author: Emilie J Millet [aut] , Maria Xose Rodriguez Alvarez [aut] , Diana Marcela Perez Valencia [aut] , Isabelle Sanchez [aut], Nadine Hilgert [aut], Bart-Jan van Rossum [aut, cre] , Fred van Eeuwijk [aut] , Martin Boer [aut]
Maintainer: Bart-Jan van Rossum <bart-jan.vanrossum@wur.nl>

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Package PRISMA2020 updated to version 1.1.4 with previous version 1.1.1 dated 2023-02-09

Title: Make Interactive 'PRISMA' Flow Diagrams
Description: Systematic reviews should be described in a high degree of methodological detail. The 'PRISMA' Statement calls for a high level of reporting detail in systematic reviews and meta-analyses. An integral part of the methodological description of a review is a flow diagram. This package produces an interactive flow diagram that conforms to the 'PRISMA2020' preprint. When made interactive, the reader/user can click on each box and be directed to another website or file online (e.g. a detailed description of the screening methods, or a list of excluded full texts), with a mouse-over tool tip that describes the information linked to in more detail. Interactive versions can be saved as HTML files, whilst static versions for inclusion in manuscripts can be saved as HTML, PDF, PNG, SVG, PS or WEBP files.
Author: Neal Haddaway [aut] , Luke McGuinness [aut] , Chris Pritchard [aut, cre] , Brennan Chapman [ctb], Hossam Hammady [ctb], Anders Kolstad [ctb] , Shreya Dimri [ctb] , Matt Lloyd Jones [ctb] , John-o Kulas [ctb]
Maintainer: Chris Pritchard <chris@christopherpritchard.co.uk>

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Package s20x updated to version 3.3.0 with previous version 3.2.2 dated 2026-01-14

Title: Functions for University of Auckland Course STATS 201/208 Data Analysis
Description: A set of functions used in teaching STATS 201/208 Data Analysis at the University of Auckland. The functions are designed to make parts of R more accessible to a large undergraduate population who are mostly not statistics majors.
Author: Brant Deppa [aut] , James Curran [aut, cre] , Hannah Yun [ctb], Rachel Fewster [ctb], Russell Millar [ctb], Ben Stevenson [ctb], Andrew Balemi [ctb], Chris Wild [ctb], Sophie Jones [ctb], Dineika Chandra [ctb], Brendan McArdle [ctb]
Maintainer: James Curran <j.curran@auckland.ac.nz>

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 inst/case_studies/CS6_4.Rmd           |    2 
 inst/case_studies/CS8_3.Rmd           |    2 
 inst/case_studies/CS9_6.Rmd           |    2 
 inst/extdata/Galton3.csv              |  396 +++++++-------
 man/anova.tslm.Rd                     |only
 man/apples.df.Rd                      |   26 
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 man/autocorPlot.Rd                    |    4 
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 man/books.df.Rd                       |   10 
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 man/bursary.df.Rd                     |    4 
 man/butterfat.df.Rd                   |    6 
 man/camplake.df.Rd                    |    6 
 man/captureOptionalName.Rd            |only
 man/casestudy.Rd                      |   16 
 man/chalk.df.Rd                       |    6 
 man/ciReg.Rd                          |    2 
 man/computer.df.Rd                    |    4 
 man/cooks20x.Rd                       |    4 
 man/course.df.Rd                      |   30 -
 man/course2way.df.Rd                  |    6 
 man/crosstabs.Rd                      |   17 
 man/diamonds.df.Rd                    |    4 
 man/displayPairs.Rd                   |   20 
 man/drawPlot.Rd                       |only
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 man/lakemary.df.Rd                    |    4 
 man/layout20x.Rd                      |   19 
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 man/matchPlottingEngine.Rd            |only
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 man/mazda.df.Rd                       |    4 
 man/mening.df.Rd                      |    7 
 man/mergers.df.Rd                     |    5 
 man/modcheck.Rd                       |   68 --
 man/modelcheck.Rd                     |   82 ++-
 man/mozart.df.Rd                      |    6 
 man/multipleComp.Rd                   |   15 
 man/nail.df.Rd                        |    4 
 man/normcheck.Rd                      |  122 +++-
 man/nzalc.df.Rd                       |only
 man/nzarrivals.df.Rd                  |only
 man/openCaseStudy.Rd                  |   18 
 man/oysters.df.Rd                     |    8 
 man/pairs20x.Rd                       |   30 -
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 man/peru.df.Rd                        |   10 
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 man/plotTslmTimeResiduals.Rd          |only
 man/predict20x.Rd                     |   47 +
 man/predictCount.Rd                   |   36 -
 man/predictGLM.Rd                     |   35 -
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 man/propslsd.new.Rd                   |    3 
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 man/residPlot.Rd                      |    6 
 man/resolveCaseStudyDestinationDir.Rd |only
 man/resolveCaseStudyOutputArgs.Rd     |only
 man/rowdistr.Rd                       |   16 
 man/rr.Rd                             |    2 
 man/s20x-package.Rd                   |   18 
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 man/saveGraphicsParameters.Rd         |only
 man/seeds.df.Rd                       |    6 
 man/sentenceCase.Rd                   |only
 man/sheep.df.Rd                       |    9 
 man/skewness.Rd                       |    4 
 man/skulls.df.Rd                      |    4 
 man/snapper.df.Rd                     |    9 
 man/soyabean.df.Rd                    |    6 
 man/stripqq.Rd                        |   35 -
 man/summary1way.Rd                    |   31 -
 man/summary2way.Rd                    |   41 -
 man/summaryStats.Rd                   |   60 +-
 man/teach.df.Rd                       |    6 
 man/technitron.df.Rd                  |   16 
 man/thyroid.df.Rd                     |    8 
 man/toothpaste.df.Rd                  |    4 
 man/trendscatter.Rd                   |    7 
 man/tslm.Rd                           |only
 man/zoo.df.Rd                         |   12 
 tests                                 |only
 174 files changed, 6011 insertions(+), 4209 deletions(-)

More information about s20x at CRAN
Permanent link

Package HDiR (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:

2022-11-16 1.1.3
2022-08-06 1.1.2
2021-03-31 1.1.1
2021-01-28 1.1
2020-12-07 1.0

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