Tue, 14 Jul 2026

Package npRmpi updated to version 0.70-5 with previous version 0.70-4 dated 2026-06-26

Title: Parallel Nonparametric Kernel Smoothing Methods for Mixed Data Types Using 'MPI'
Description: Nonparametric (and semiparametric) kernel methods that seamlessly handle a mix of continuous, unordered, and ordered factor data types. This package is a parallel implementation of the 'np' package based on the 'MPI' specification that incorporates the 'Rmpi' package (Hao Yu <hyu@stats.uwo.ca>) with minor modifications and we are extremely grateful to Hao Yu for his contributions to the 'R' community. We would like to gratefully acknowledge support from the Natural Sciences and Engineering Research Council of Canada (NSERC, <https://www.nserc-crsng.gc.ca/>), the Social Sciences and Humanities Research Council of Canada (SSHRC, <https://www.sshrc-crsh.gc.ca/>), and the Shared Hierarchical Academic Research Computing Network (SHARCNET, <https://sharcnet.ca/>). We would also like to acknowledge the contributions of the 'GNU GSL' authors. In particular, we adapt the 'GNU GSL' B-spline routine 'gsl_bspline.c' adding automated support for quantile knots (in addition t [...truncated...]
Author: Jeffrey S. Racine [aut, cre], Tristen Hayfield [aut], Hao Yu [ctb, cph], The GSL Team [cph], Numerical Recipes Software [cph]
Maintainer: Jeffrey S. Racine <racinej@mcmaster.ca>

Diff between npRmpi versions 0.70-4 dated 2026-06-26 and 0.70-5 dated 2026-07-14

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 DESCRIPTION                                                                      |   10 
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 NAMESPACE                                                                        |    1 
 NEWS.md                                                                          |  182 +
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 268 files changed, 10231 insertions(+), 4908 deletions(-)

More information about npRmpi at CRAN
Permanent link

Package np updated to version 0.70-5 with previous version 0.70-4 dated 2026-06-26

Title: Nonparametric Kernel Smoothing Methods for Mixed Data Types
Description: Nonparametric (and semiparametric) kernel methods that seamlessly handle a mix of continuous, unordered, and ordered factor data types. We would like to gratefully acknowledge support from the Natural Sciences and Engineering Research Council of Canada (NSERC, <https://www.nserc-crsng.gc.ca/>), the Social Sciences and Humanities Research Council of Canada (SSHRC, <https://www.sshrc-crsh.gc.ca/>), and the Shared Hierarchical Academic Research Computing Network (SHARCNET, <https://sharcnet.ca/>). We would also like to acknowledge the contributions of the GNU GSL authors. In particular, we adapt the GNU GSL B-spline routine gsl_bspline.c adding automated support for quantile knots (in addition to uniform knots), providing missing functionality for derivatives, and for extending the splines beyond their endpoints.
Author: Jeffrey S. Racine [aut, cre], Tristen Hayfield [aut]
Maintainer: Jeffrey S. Racine <racinej@mcmaster.ca>

Diff between np versions 0.70-4 dated 2026-06-26 and 0.70-5 dated 2026-07-14

 CHANGELOG                                                                 |  152 ++
 DESCRIPTION                                                               |    8 
 MD5                                                                       |  358 ++--
 NAMESPACE                                                                 |    1 
 NEWS.md                                                                   |  148 +
 R/condensity.R                                                            |   46 
 R/condistribution.R                                                       |   46 
 R/density.R                                                               |   10 
 R/distribution.R                                                          |   10 
 R/lsqregression.R                                                         |   82 -
 R/np.cdhat.helpers.R                                                      |   36 
 R/np.condensity.R                                                         |   95 -
 R/np.condensity.bw.R                                                      |  142 +
 R/np.condensity.proper.R                                                  |  105 +
 R/np.condistribution.R                                                    |   95 -
 R/np.condistribution.bw.R                                                 |   87 -
 R/np.conmode.R                                                            |  156 +-
 R/np.copula.R                                                             |  190 +-
 R/np.density.R                                                            |   34 
 R/np.density.bw.R                                                         |   46 
 R/np.distribution.R                                                       |   22 
 R/np.distribution.bw.R                                                    |  178 +-
 R/np.kernel.R                                                             |   17 
 R/np.lp.degree.search.R                                                   |   91 +
 R/np.lsqregression.R                                                      |  237 ++-
 R/np.plot.engine.conbandwidth.R                                           |   16 
 R/np.plot.engine.condbandwidth.R                                          |   19 
 R/np.plot.engine.plbandwidth.R                                            |   13 
 R/np.plot.engine.rbandwidth.R                                             |   47 
 R/np.plot.engine.scbandwidth.R                                            |   21 
 R/np.plot.engine.sibandwidth.R                                            |   31 
 R/np.plot.helpers.R                                                       |  670 +++++++-
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 R/np.plregression.bw.R                                                    |   32 
 R/np.qregression.R                                                        |  141 +
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 R/np.semihat.R                                                            |   43 
 R/np.sigtest.R                                                            |    2 
 R/np.singleindex.R                                                        |  225 ++
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Package rnnmf updated to version 0.3.1 with previous version 0.3.0 dated 2024-11-04

Title: Regularized Non-Negative Matrix Factorization
Description: A proof of concept implementation of regularized non-negative matrix factorization optimization. A non-negative matrix factorization factors non-negative matrix Y approximately as L R, for non-negative matrices L and R of reduced rank. This package supports such factorizations with weighted objective and regularization penalties. Allowable regularization penalties include L1 and L2 penalties on L and R, as well as non-orthogonality penalties. This package provides multiplicative update algorithms, which are a modification of the algorithm of Lee and Seung (2001) <http://papers.nips.cc/paper/1861-algorithms-for-non-negative-matrix-factorization.pdf>, as well as an additive update derived from that multiplicative update. See also Pav (2024) <doi:10.48550/arXiv.2410.22698>.
Author: Steven E. Pav [aut, cre]
Maintainer: Steven E. Pav <shabbychef@gmail.com>

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Package paco readmission to version 0.5.0 with previous version 0.4.2 dated 2020-08-25

Title: Procrustes Application to Cophylogenetic Analysis
Description: Procrustes analyses to infer co-phylogenetic matching between pairs of phylogenetic trees.
Author: Juan Antonio Balbuena [aut, cre], Timothee Poisot [aut], Matthew Hutchinson [aut], Fernando Cagua [aut]
Maintainer: Juan Antonio Balbuena <j.a.balbuena@uv.es>

This is a re-admission after prior archival of version 0.4.2 dated 2020-08-25

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Package fishbc updated to version 0.2.2 with previous version 0.2.1 dated 2021-05-12

Title: Fishes of British Columbia
Description: Provides raw and curated data on the codes, classification and conservation status of freshwater fishes in British Columbia. Marine fishes will be added in a future release.
Author: Evan Amies-Galonski [aut] , Joe Thorley [aut] , Nadine Hussein [aut] , Sarah Lyons [cre] , Bronwen Lewis [ctb], Jesse Patterson [ctb], Gordon Oliphant [ctb], Seb Dalgarno [ctb] , Simon Norris [ctb], Allan Irvine [ctb], Poisson Consulting [cph, fnd], [...truncated...]
Maintainer: Sarah Lyons <sarah@poissonconsulting.ca>

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Package SNPkit updated to version 0.1.2 with previous version 0.1.0 dated 2026-06-26

Title: S4 Tools for Reading and Organizing Genetic Data
Description: Provides an integrated suite of tools for handling single nucleotide polymorphism (SNP) genotype data in large-scale genetic studies. Supports importing and merging genotype files, performing quality control on SNP markers and samples, and preparing data for downstream analyses using popular software such as 'FImpute' and 'PLINK'. Offers S4 classes and methods to efficiently encapsulate SNP data, along with utilities for generating genotype summary statistics and visualization. Additional functionalities include anticlustering approaches for batch effect control, automated script generation for external software, and streamlined workflows for large datasets commonly encountered in animal and plant breeding programs. Designed to facilitate reproducible and scalable SNP data analyses in quantitative and statistical genetics.
Author: Vinicius Junqueira [aut, cre], Roberto Higa [aut], Fernando Flores Cardoso [aut], Marcos Jun Iti Yokoo [aut]
Maintainer: Vinicius Junqueira <junqueiravinicius@hotmail.com>

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Package printify updated to version 1.0.3 with previous version 1.0.2 dated 2026-06-17

Title: Custom Formatted Console Messages with Timing Support
Description: A lightweight message system relying purely on base R. Comes with built-in and pre styled message types and provides an easy way to create custom messages. Supports individually styled and colored text as well as timing information. Designed to make console output more informative and visually organized.
Author: Tim Siebenmorgen [aut, cre, cph]
Maintainer: Tim Siebenmorgen <qol_package@proton.me>

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Package madness updated to version 0.2.9 with previous version 0.2.8 dated 2023-08-21

Title: Automatic Differentiation of Multivariate Operations
Description: An object that supports automatic differentiation of matrix- and multidimensional-valued functions with respect to multidimensional independent variables. Automatic differentiation is via 'forward accumulation'.
Author: Steven E. Pav [aut, cre]
Maintainer: Steven E. Pav <shabbychef@gmail.com>

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Package ctsmTMB updated to version 1.1.1 with previous version 1.0.1 dated 2025-08-27

Title: Continuous Time Stochastic Modelling using Template Model Builder
Description: Perform state and parameter inference, and forecasting, in stochastic state-space systems using the 'ctsmTMB' R6 class. This class provides a user-friendly interface for working with stochastic state space models. Inference is based on maximum likelihood estimation, with derivatives efficiently computed through automatic differentiation enabled by the 'TMB'/'RTMB' packages (Kristensen et al., 2016) <doi:10.18637/jss.v070.i05>. The available inference methods include Kalman filters, in addition to a Laplace approximation-based smoothing method. For further details of these methods refer to the documentation of the 'CTSMR' package <https://ctsm.info/ctsmr-reference.pdf> and Thygesen (2025) <doi:10.48550/arXiv.2503.21358>. Forecasting capabilities include moment predictions and stochastic path simulations implemented in 'C++' using 'Rcpp' (Eddelbuettel et al., 2018) <doi:10.1080/00031305.2017.1375990> for computational efficiency.
Author: Phillip Vetter [aut, cre, cph], Jan Moeller [ctb], Uffe Thygesen [ctb], Peder Bacher [ctb], Henrik Madsen [ctb]
Maintainer: Phillip Vetter <pbrve@dtu.dk>

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Package LOST updated to version 2.1.4 with previous version 2.1.3 dated 2026-03-13

Title: Missing Morphometric Data Simulation and Estimation
Description: Functions for simulating missing morphometric data randomly, with taxonomic bias and with anatomical bias. LOST also includes functions for estimating linear and geometric morphometric data.
Author: J. Arbour [aut, cre], C. Brown [aut]
Maintainer: J. Arbour <jessica.arbour@mtsu.edu>

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Package ggChinaFlag updated to version 0.3.0 with previous version 0.2.0 dated 2026-07-04

Title: Drawing Chinese National and Historical Flags with 'ggplot2'
Description: Provides programmatic implementations for drawing Chinese national and historical flags using analytic geometry and 'ggplot2'-based vector graphics. Flag designs are constructed entirely from geometric primitives such as polygons and rectangles, without relying on external image files. The package is intended for educational demonstration, reproducible visualization, and procedural graphics in R.
Author: Zhaoshuo Liu [aut, cre]
Maintainer: Zhaoshuo Liu <liuzhaoshuo1997@outlook.com>

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Package cdcanthro updated to version 0.2.1 with previous version 0.2.0 dated 2026-05-22

Title: Sex- and Age-Standardized Metrics from the Centers for Disease Control and Prevention (CDC) Growth Charts
Description: Calculation of sex- and age-standardized growth metrics based on the 2000 CDC growth charts. Provides functions to generate z-scores and percentiles for weight, height, and body mass index (BMI) using the LMS method (lambda-mu-sigma). Includes extended BMI z-scores for values above the 95th percentile to more accurately characterize the sex- and age-standardized BMI of children with very high BMIs.
Author: David Freedman [aut, cre]
Maintainer: David Freedman <DavidSFreedman@gmail.com>

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Package easyRasch2 updated to version 1.1.0 with previous version 1.0.0 dated 2026-07-05

Title: Psychometric Analysis with Rasch Measurement Theory
Description: Streamlines reproducible Rasch measurement theory analyses for ordinal item-response data, combining estimation routines from 'eRm', 'psychotools', 'mirt', 'iarm', and 'lavaan' with consistent diagnostic, plotting, and reporting layers. Covers the four basic psychometric criteria summarised by Christensen et al. (2021) <doi:10.1111/sms.13908> -- unidimensionality, local independence, ordered response category thresholds, and invariance across subgroups -- together with item fit, targeting, reliability, category functioning, and descriptive item-response plots. A distinguishing feature is the use of simulation-based critical values to replace rule-of-thumb cutoffs for conditional infit mean-square, Yen's Q3 local-dependence statistic, the largest residual-PCA eigenvalue, ordinal CFA fit indices, and partial-gamma DIF and local-dependence coefficients, optionally augmented with multiplicity-corrected bootstrap p-values. Outputs are knitr::kable() tables and 'ggplot2' figures suitab [...truncated...]
Author: Magnus Johansson [aut, cre] , Nicklas Korsell [ctb] , Mirka Henninger [ctb] , Jan Radek [ctb]
Maintainer: Magnus Johansson <pgmj@pm.me>

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Package NetWeaver updated to version 1.0.0 with previous version 0.0.6 dated 2019-02-26

Title: Graphic Presentation of Complex Genomic and Network Data Analysis
Description: Implements various simple function utilities and flexible pipelines to generate circular images for visualizing complex genomic and network data analysis features.
Author: Minghui Wang [aut, cre], Bin Zhang [aut]
Maintainer: Minghui Wang <m.h.wang@live.com>

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Package gp3tools updated to version 2.0.1 with previous version 1.0.2 dated 2026-06-30

Title: Import, Inspect, Analyse, and Report Gazepoint GP3 Exports
Description: Tools for importing, inspecting, cleaning, summarising, modelling, and reporting Gazepoint GP3 and Gazepoint Analysis CSV exports. The package supports offline workflows for all-gaze, fixation, pupil, area-of-interest, transition, time-course, quality-audit, and manuscript-reporting analyses. The package methodology is described in the peer-reviewed software paper <doi:10.3390/jemr19040076>.
Author: Stefanos Balaskas [aut, cre]
Maintainer: Stefanos Balaskas <s.balaskas@ac.upatras.gr>

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Package autoMR updated to version 1.2.1 with previous version 1.2.0 dated 2026-06-12

Title: Automated Mendelian Randomization Pipelines and Visualizations
Description: Provides tools to summarize, analyze, and visualize results from Mendelian randomization studies using summarized genetic association data. The package includes functions for generating forest plots and scatter plots at the single-nucleotide polymorphism and Mendelian randomization method levels, and for fitting multiple estimators in a unified pipeline, including inverse-variance weighted estimation, Mendelian randomization Egger regression, the weighted median estimator, the robust adjusted profile score, Mendelian randomization pleiotropy residual sum and outlier, Mendelian randomization with the genotype recoding invariance property, and a Bayesian horseshoe method. Related methods are described by Burgess (2013) <doi:10.1002/gepi.21758>, Bowden (2015) <doi:10.1093/ije/dyv080>, Bowden (2016) <doi:10.1002/gepi.21965>, Zhao (2020) <doi:10.1214/19-AOS1866>, Verbanck (2018) <doi:10.1038/s41588-018-0099-7>, Dudbridge (2025) <doi:10.1371/journal.pgen.1011 [...truncated...]
Author: Kelin Zhong [aut, cre], Chia-Ling Kuo [aut]
Maintainer: Kelin Zhong <kelinzhonguconn@gmail.com>

Diff between autoMR versions 1.2.0 dated 2026-06-12 and 1.2.1 dated 2026-07-14

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Package specmine.datasets readmission to version 0.0.3 with previous version 0.0.2 dated 2021-02-17

Title: Data Sets for 'specmine'
Description: Provides the data sets used to exemplify 'specmine'. These data sets were formerly distributed with 'specmine', but they exceed current CRAN policy for package size.
Author: Christopher Costa [aut], Marcelo Maraschin [aut], Miguel Rocha [aut], Pedro Fontao [aut, cre], Sara Cardoso [aut], Telma Afonso [aut], C. Beleites [cph], Jie Hao [cph], Bruno Pereira [aut]
Maintainer: Pedro Fontao <pedrofontao812004@gmail.com>

This is a re-admission after prior archival of version 0.0.2 dated 2021-02-17

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New package lazymatrix with initial version 0.1.0
Package: lazymatrix
Title: Perform Complex Matrix Operations Symbolically on Sparse Matrices
Version: 0.1.0
Description: Provides a framework for lazy computation on large sparse matrices. Enables lazy evaluation of normalized data matrices, preserving sparsity throughout operations without materializing dense intermediate objects. Implements statistical algorithms including LSQR for sparse least squares as described in Paige and Saunders (1982) <doi:10.1145/355984.355989> and partial singular value decomposition via the augmented implicitly restarted Lanczos bidiagonalization algorithm of Baglama and Reichel (2005) <doi:10.1137/04060593X>.
License: GPL (>= 3)
Encoding: UTF-8
Suggests: bench, dplyr, ggplot2, knitr, rmarkdown, scales, testthat (>= 3.0.0), tidyr
Imports: Matrix, methods, stats, irlba, Rcpp
VignetteBuilder: knitr
LinkingTo: Rcpp, RcppArmadillo
URL: https://vsegersall.github.io/lazymatrix/
NeedsCompilation: yes
Packaged: 2026-07-06 01:06:49 UTC; jola
Author: Viktor Segersall [aut, cre, cph]
Maintainer: Viktor Segersall <viktor.segersall@proton.me>
Repository: CRAN
Date/Publication: 2026-07-14 16:40:07 UTC

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Package IndependenceTests readmission to version 0.7 with previous version 0.5 dated 2020-12-18

Title: Non-Parametric Tests of Independence Between Random Vectors
Description: Non-parametric tests of independence (mutual or serial) between some quantitative random vectors, as described in Bilodeau M. and Lafaye de Micheaux P. (2009) <doi:10.1016/j.jspi.2008.11.006>, in Beran R., Bilodeau M. and Lafaye de Micheaux P. (2007) <doi:10.1016/j.jmva.2007.01.009> and in Fan Y., Lafaye de Micheaux P., Penev S. and Salopek D. (2017) <doi:10.1016/j.jmva.2016.09.014>.
Author: Pierre Lafaye De Micheaux [aut, cre] , Martin Bilodeau [aut], Yanan Fan [aut], Spiridon Penev [aut], Donna Salopek [aut], Cleve Moler [cph] , Jack Dongarra [cph] , Richard Hanson [cph] , Sven Hammarling [cph] , Jeremy Du Croz [cph]
Maintainer: Pierre Lafaye De Micheaux <lafaye@unsw.edu.au>

This is a re-admission after prior archival of version 0.5 dated 2020-12-18

Diff between IndependenceTests versions 0.5 dated 2020-12-18 and 0.7 dated 2026-07-14

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New package glydraw with initial version 0.6.3
Package: glydraw
Title: Draw Beautiful Symbol Nomenclature for Glycans
Version: 0.6.3
Description: A 'ggplot2'-native plotting engine for drawing reproducible beautiful Symbol Nomenclature for Glycans (SNFG) glycan cartoons from glycan structure objects or text notations, with support for batch export, structural highlighting, and deep appearance customization. It follows the SNFG specification described at <https://www.ncbi.nlm.nih.gov/glycans/snfg.html>.
License: MIT + file LICENSE
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), vdiffr
Encoding: UTF-8
URL: https://glycoverse.github.io/glydraw/, https://github.com/glycoverse/glydraw
Imports: glyrepr (>= 0.10.0), rlang, dplyr, ggplot2 (>= 4.0.0), igraph, purrr, png, glyparse, cli, checkmate, scales, fs
VignetteBuilder: knitr
BugReports: https://github.com/glycoverse/glydraw/issues
NeedsCompilation: no
Packaged: 2026-07-06 05:54:29 UTC; fubin
Author: Bin Fu [aut, cre, cph] , Xisong Feng [aut]
Maintainer: Bin Fu <23110220018@m.fudan.edu.cn>
Depends: R (>= 4.1.0)
Repository: CRAN
Date/Publication: 2026-07-14 16:30:02 UTC

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New package DynCount with initial version 0.1.0
Package: DynCount
Title: Bayesian Dynamic Models for Poisson and Binomial Time Series
Version: 0.1.0
Description: Fits Bayesian state-space models for non-Gaussian time series using a latent log-rate (Poisson) or latent logit (binomial) formulation. The latent trajectory follows a first-order random walk or a stationary AR(1) process, sampled by Metropolis-within-Gibbs using the implied Gaussian Markov random field (GMRF) full conditionals. Four innovation structures are supported for the latent increments: constant-variance Gaussian, Student-t, a finite scale mixture of normals, and stochastic volatility. Both families support time-constant zero inflation. The package provides simulation, fitting, forecasting, summary and plotting tools. It implements and extends the methodology of Zens and Bijak (2026) <doi:10.1214/26-AOAS2171>.
License: MIT + file LICENSE
Language: en-GB
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: stats, graphics, grDevices, utils
Suggests: stochvol, testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: no
Packaged: 2026-07-06 10:25:38 UTC; Gregor
Author: Gregor Zens [aut, cre]
Maintainer: Gregor Zens <zens@iiasa.ac.at>
Repository: CRAN
Date/Publication: 2026-07-14 17:00:02 UTC

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Package datey updated to version 0.1.1 with previous version 0.1.0 dated 2026-07-07

Title: Exact Date and Duration Arithmetic on an Annual Grid
Description: Standardised mapping of dates onto a discrete annual grid, together with exact date and duration arithmetic. This matters when the primary unit is years but the input data uses dates. Examples are actuarial mortality experience analysis and valuation of life assurance and annuities, for which mortality rates are defined per year but experience and valuation data are typically defined using dates.
Author: Tim Gordon [aut, cre]
Maintainer: Tim Gordon <tim.gordon@btinternet.com>

Diff between datey versions 0.1.0 dated 2026-07-07 and 0.1.1 dated 2026-07-14

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New package circularNet with initial version 0.1.0
Package: circularNet
Title: Circular Graphical Model Estimation
Version: 0.1.0
Description: Provides methods for estimating circular graphical models using maximum likelihood estimation (MLE) and circular mean squared error (CMSE) approaches. The package includes tools for model fitting, network construction, network evaluation, and visualization. The CMSE-based methodology is related to Dar (2023) <https://open.metu.edu.tr/handle/11511/102577>. The package supports both simulated circular data and real-world applications, including gene-expression network analysis.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: graphics, igraph, stats
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Depends: R (>= 4.1.0)
NeedsCompilation: no
Packaged: 2026-07-05 19:34:47 UTC; fatemeh
Author: Fatemeh Sarasir [aut, cre] , Vilda Purutcuoglu [aut] , Elif Dogan Dar [aut]
Maintainer: Fatemeh Sarasir <fsarasir@gmail.com>
Repository: CRAN
Date/Publication: 2026-07-14 16:30:09 UTC

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Package sasLM updated to version 1.0.1 with previous version 1.0.0 dated 2026-06-15

Title: 'SAS' Linear Model
Description: This is a core implementation of 'SAS' procedures for linear models - GLM, REG, ANOVA, TTEST, 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 do not necessarily mean incorrectness. However, many want the same results as '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, cre]
Maintainer: Kyun-Seop Bae <k@acr.kr>

Diff between sasLM versions 1.0.0 dated 2026-06-15 and 1.0.1 dated 2026-07-14

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Package pkgdiff updated to version 1.0.4 with previous version 1.0.3 dated 2026-05-10

Title: Identifies Package Differences
Description: Identifies differences between versions of a package. Specifically, the functions help determine if there are breaking changes from one package version to the next. The package also includes a stability assessment, to help you determine the overall stability of a package, or even an entire repository.
Author: David Bosak [aut, cre], Brian Varney [ctb], Kevin Putschko [ctb]
Maintainer: David Bosak <dbosak01@gmail.com>

Diff between pkgdiff versions 1.0.3 dated 2026-05-10 and 1.0.4 dated 2026-07-14

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Package svySE updated to version 0.2.0 with previous version 0.1.0 dated 2026-07-10

Title: Sampling Error Estimation for Complex Surveys
Description: Estimates sampling errors and produces indicator tables for complex survey data. Supports weighted totals, proportions, standard errors, confidence intervals, coefficients of variation, design effects, unweighted frequencies, grouped estimates, domain estimates, optional stratification and clustering variables, and customizable exports to '.xlsx' files. Survey estimation is based on design-based inference using Taylor series linearization implemented in the 'survey' package (Lumley, 2004, <doi:10.18637/jss.v009.i08>; Lumley, 2010, ISBN:9780470284308). The package provides a reproducible workflow for official statistics, household surveys, and applied survey research.
Author: Luis Burgos [aut, cre]
Maintainer: Luis Burgos <lburgoss1996@gmail.com>

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Package lineup2 updated to version 0.8 with previous version 0.6 dated 2021-06-15

Title: Lining Up Two Sets of Measurements
Description: Tools for detecting and correcting sample mix-ups between two sets of measurements, such as between gene expression data on two tissues. This is a revised version of the 'lineup' package, to be more general and not tied to the 'qtl' package.
Author: Karl W Broman [aut, cre]
Maintainer: Karl W Broman <broman@wisc.edu>

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Package autoFC updated to version 1.0.0.1002 with previous version 1.0.0.1001 dated 2026-06-10

Title: Automatic Toolkit for Construction, Optimization, Scoring and Simulation of Forced-Choice Tests
Description: Forced-choice (FC) response has gained increasing popularity and interest for its resistance to faking when well-designed (Cao & Drasgow, 2019 <doi:10.1037/apl0000414>). To established well-designed FC scales, typically each item within a block should measure different trait and have similar level of social desirability (Zhang et al., 2020 <doi:10.1177/1094428119836486>). Recent study also suggests the importance of high inter-item agreement of social desirability between items within a block (Pavlov et al., 2021 <doi:10.31234/osf.io/hmnrc>). In addition to this, FC developers may also need to maximize factor loading differences (Brown & Maydeu-Olivares, 2011 <doi:10.1177/0013164410375112>) or minimize item location differences (Cao & Drasgow, 2019 <doi:10.1037/apl0000414>) depending on scoring models. Decision of which items should be assigned to the same block, also called as item pairing, is thus critical to the quality of an FC test. Becau [...truncated...]
Author: Mengtong Li [cre, aut] , Tianjun Sun [aut] , Bo Zhang [aut]
Maintainer: Mengtong Li <mt_li@fudan.edu.cn>

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Package wcc updated to version 0.4.0 with previous version 0.3.1 dated 2026-04-21

Title: Windowed Cross Correlation
Description: Calculates Windowed Cross Correlation for pairs of time series. Provides support for surrogate analysis for nonparametric test of significance. Calculates aggregate statistics over a range of parameter values. Plots the results as Windowed Cross Correlation plots and heat maps. The software is described in Boker, S. M., Rotondo, J. L., Xu, M., & King, K. (2002). Windowed cross-correlation and peak picking for the analysis of variability in the association between behavioral time series. Psychological Methods, 7(3), 338.
Author: Steven Boker [aut, cre], Minquan Xu [aut], Sareena Chadha [aut], Christopher Welker [aut], Jingyun Wu [aut], Pascal Deboeck [aut], Aaron Peikert [aut], Claude [aut]
Maintainer: Steven Boker <smb3u@virginia.edu>

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Package trend updated to version 1.1.7 with previous version 1.1.6 dated 2023-10-10

Title: Non-Parametric Trend Tests and Change-Point Detection
Description: The analysis of environmental data often requires the detection of trends and change-points. This package includes tests for trend detection (Cox-Stuart Trend Test, Mann-Kendall Trend Test, (correlated) Hirsch-Slack Test, partial Mann-Kendall Trend Test, multivariate (multisite) Mann-Kendall Trend Test, (Seasonal) Sen's slope, partial Pearson and Spearman correlation trend test), change-point detection (Lanzante's test procedures, Pettitt's test, Buishand Range Test, Buishand U Test, Standard Normal Homogeinity Test), detection of non-randomness (Wallis-Moore Phase Frequency Test, Bartels rank von Neumann's ratio test, Wald-Wolfowitz Test) and the two sample Robust Rank-Order Distributional Test.
Author: Thorsten Pohlert [aut, cre]
Maintainer: Thorsten Pohlert <thorsten.pohlert@gmx.de>

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Package IBclust updated to version 1.4 with previous version 1.3 dated 2026-05-11

Title: Information Bottleneck Methods for Clustering Mixed-Type Data
Description: Implements multiple variants of the Information Bottleneck ('IB') method for clustering datasets containing continuous, categorical (nominal/ordinal) and mixed-type variables. The package provides deterministic, agglomerative, generalised, sequential, and standard IB clustering algorithms that preserve relevant information while forming interpretable clusters. The Deterministic Information Bottleneck is described in Costa et al. (2026) <doi:10.1016/j.patcog.2026.113580>. The standard IB method originates from Tishby et al. (2000) <doi:10.48550/arXiv.physics/0004057>, the agglomerative variant from Slonim and Tishby (1999) <https://papers.nips.cc/paper/1651-agglomerative-information-bottleneck>, the generalised IB from Strouse and Schwab (2017) <doi:10.1162/NECO_a_00961>, and the sequential IB from Slonim et al. (2002) <doi:10.1145/564376.564401>.
Author: Angelos Markos [aut, cre], Efthymios Costa [aut], Ioanna Papatsouma [aut]
Maintainer: Angelos Markos <amarkos@gmail.com>

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Package densityratio updated to version 0.2.3 with previous version 0.2.2 dated 2025-07-18

Title: Distribution Comparison Through Density Ratio Estimation
Description: Fast, flexible and user-friendly tools for distribution comparison through direct density ratio estimation. The estimated density ratio can be used for covariate shift adjustment, outlier-detection, change-point detection, classification and evaluation of synthetic data quality. The package implements multiple non-parametric estimation techniques (unconstrained least-squares importance fitting, ulsif(), Kullback-Leibler importance estimation procedure, kliep(), spectral density ratio estimation, spectral(), kernel mean matching, kmm(), and least-squares hetero-distributional subspace search, lhss()). with automatic tuning of hyperparameters. Helper functions are available for two-sample testing and visualizing the density ratios. For an overview on density ratio estimation, see Sugiyama et al. (2012) <doi:10.1017/CBO9781139035613> for a general overview, and the help files for references on the specific estimation techniques.
Author: Thom Volker [aut, cre] , Carlos Gonzalez Poses [ctb], Erik-Jan van Kesteren [ctb]
Maintainer: Thom Volker <thombenjaminvolker@gmail.com>

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Package mlr3spatial updated to version 0.7.0 with previous version 0.6.1 dated 2025-09-14

Title: Support for Spatial Objects Within the 'mlr3' Ecosystem
Description: Extends the 'mlr3' ML framework with methods for spatial objects. Data storage and prediction are supported for packages 'terra', 'raster' and 'stars'.
Author: Marc Becker [aut, cre] , Patrick Schratz [aut]
Maintainer: Marc Becker <marcbecker@posteo.de>

Diff between mlr3spatial versions 0.6.1 dated 2025-09-14 and 0.7.0 dated 2026-07-14

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Permanent link

Package EMC2 updated to version 3.5.0 with previous version 3.4.1 dated 2026-01-12

Title: Bayesian Hierarchical Analysis of Cognitive Models of Choice
Description: Fit Bayesian (hierarchical) cognitive models using a linear modeling language interface using particle Metropolis Markov chain Monte Carlo sampling with Gibbs steps. The diffusion decision model (DDM), linear ballistic accumulator model (LBA), racing diffusion model (RDM), and the lognormal race model (LNR) are supported. Additionally, users can specify their own likelihood function and/or choose for non-hierarchical estimation, as well as for a diagonal, blocked or full multivariate normal group-level distribution to test individual differences. Prior specification is facilitated through methods that visualize the (implied) prior. A wide range of plotting functions assist in assessing model convergence and posterior inference. Models can be easily evaluated using functions that plot posterior predictions or using relative model comparison metrics such as information criteria or Bayes factors. References: Stevenson et al. (2024) <doi:10.31234/osf.io/2e4dq>.
Author: Niek Stevenson [aut, cre] , Michelle Donzallaz [aut], Andrew Heathcote [aut], Steven Miletic [aut], Luke Strickland [ctb], Frank Hezemans [ctb], Raphael Hartmann [ctb], Karl C. Klauer [ctb], Steven G. Johnson [ctb], Jean M. Linhart [ctb], Brian Gough [...truncated...]
Maintainer: Niek Stevenson <niek.stevenson@gmail.com>

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Package qlcal updated to version 0.1.2 with previous version 0.1.1 dated 2026-04-15

Title: R Bindings to the Calendaring Functionality of 'QuantLib'
Description: 'QuantLib' bindings are provided for R using 'Rcpp' via an evolved version of the initial header-only 'Quantuccia' project offering an subset of 'QuantLib' (now maintained separately just for the calendaring subset). See the included file 'AUTHORS' for a full list of contributors to 'QuantLib' (and hence also 'Quantuccia').
Author: Dirk Eddelbuettel [aut, cre] , QuantLib Authors [aut]
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between qlcal versions 0.1.1 dated 2026-04-15 and 0.1.2 dated 2026-07-14

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Permanent link

Package admiral.test (with last version 0.7.0) was removed from CRAN

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

2023-09-10 0.7.0
2023-06-07 0.6.0
2023-03-06 0.5.0
2022-11-29 0.4.0
2022-09-01 0.3.0
2022-05-30 0.2.0
2022-02-15 0.1.2

Permanent link
Package tf updated to version 0.5.0 with previous version 0.4.1 dated 2026-04-07

Title: S3 Classes and Methods for Tidy Functional Data
Description: Provides S3 vector types for functional data represented on grids, in spline bases, or via functional principal components. Supports arithmetic and summary methods, plotting, derivation, integration, smoothing, registration, and data import/export for these functional vectors. Includes data-wrangling tools for re-evaluation, subsetting, sub-assignment, zooming into sub-domains, and extracting functional features such as minima, maxima, and their locations. Enables joint analysis of functional and scalar variables by integrating functional vectors into standard data frames.
Author: Fabian Scheipl [aut, cre, cph] , Jeff Goldsmith [aut], Maximilian Muecke [aut] , Julia Wrobel [ctb] , Sebastian Fischer [ctb]
Maintainer: Fabian Scheipl <fabian.scheipl@googlemail.com>

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Package admiralpeds updated to version 0.4.0 with previous version 0.3.0 dated 2026-01-23

Title: Pediatrics Extension Package for ADaM in 'R' Asset Library
Description: A toolbox for programming Clinical Data Standards Interchange Consortium (CDISC) compliant Analysis Data Model (ADaM) datasets in R. ADaM datasets are a mandatory part of any New Drug or Biologics License Application submitted to the United States Food and Drug Administration (FDA). Analysis derivations are implemented in accordance with the "Analysis Data Model Implementation Guide" (CDISC Analysis Data Model Team, 2021, <https://www.cdisc.org/standards/foundational/adam>). The package is an extension package of the 'admiral' package for pediatric clinical trials.
Author: Fanny Gautier [aut, cre] , Ross Farrugia [aut], Zelos Zhu [aut], Sukalpo Saha [aut], Lina Patil [aut], Samia Kabi [aut], Laura Liao [ctb], Remigiusz Kudlacz [ctb], Pierre Wallet [ctb], Amin Sherzad [ctb], David Freedman [ctb], Mahmoud Hamza [ctb], Cy [...truncated...]
Maintainer: Fanny Gautier <fanny.gautier@cytel.com>

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Package directadjusting updated to version 0.7.0 with previous version 0.6.1 dated 2026-02-04

Title: Directly Adjusted Estimates
Description: Compute estimates and confidence intervals of weighted averages quickly and easily. Weighted averages are computed using data.table for speed. Confidence intervals are approximated using the delta method with either using known formulae or via algorithmic or numerical derivation.
Author: Joonas Miettinen [cre, aut]
Maintainer: Joonas Miettinen <joonas.miettinen@cancer.fi>

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Package fbrglm updated to version 0.1.0 with previous version 0.0.1 dated 2026-06-22

Title: Safe Formula-Based Regularized Generalized Linear Models
Description: A formula-based wrapper around 'glmnet' that brings the 'glm()'-compatible modeling workflow to regularized generalized linear models. Training-time 'terms', 'xlevels', and 'contrasts' are stored on the fit object and reused at predict time, so the design matrix is reconstructed consistently across sessions. Complete-case bookkeeping is exposed via 'nobs_info', and linearly dependent columns are detected by a QR pivot and reported as 'NA' in 'coef()' and 'summary()' (the 'stats::glm()' convention), distinguishing "not identifiable" from "shrunk to zero by the penalty". Novel factor levels at predict time raise the same error 'stats::predict.glm()' does by default, with 'on_new_levels = "na"' as a production-style opt-in. Accepts character family strings ('gaussian', 'binomial', 'poisson', 'cox', 'multinomial', 'mgaussian') and any 'glm' family object the underlying 'glmnet' itself accepts, including 'Gamma' and fixed-theta negative binomial via 'MASS::negative.binomial'.
Author: Koki Tsuyuzaki [aut, cre]
Maintainer: Koki Tsuyuzaki <k.t.the-answer@hotmail.co.jp>

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Package tinyVAST updated to version 1.6.2 with previous version 1.6.1 dated 2026-06-30

Title: Multivariate Spatio-Temporal Models using Structural Equations
Description: Fits a wide variety of multivariate spatio-temporal models with simultaneous and lagged interactions among variables (including vector autoregressive spatio-temporal ('VAST') dynamics) for areal, continuous, or network spatial domains. It includes time-variable, space-variable, and space-time-variable interactions using dynamic structural equation models ('DSEM') as expressive interface, and the 'mgcv' package to specify splines via the formula interface. See Thorson et al. (2025) <doi:10.1111/geb.70035> for more details.
Author: James T. Thorson [aut, cre] , Sean C. Anderson [aut]
Maintainer: James T. Thorson <James.Thorson@noaa.gov>

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Package redlistr updated to version 2.1.0 with previous version 1.0.4 dated 2023-10-02

Title: Tools for the IUCN Red List of Ecosystems and Species
Description: A toolbox created by members of the International Union for Conservation of Nature (IUCN) Red List of Ecosystems Committee for Scientific Standards. Primarily, it is a set of tools suitable for calculating the metrics required for making assessments of species and ecosystems against the IUCN Red List of Threatened Species and the IUCN Red List of Ecosystems categories and criteria. See the IUCN website for detailed guidelines, the criteria, publications and other information.
Author: Calvin Lee [aut] , Nicholas Murray [aut] , Aniko Toth [cre, aut] , Jose R. Ferrer-Paris [aut]
Maintainer: Aniko Toth <anikobtoth@gmail.com>

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Package oce updated to version 1.8-4 with previous version 1.8-3 dated 2024-08-17

Title: Analysis of Oceanographic Data
Description: Supports the analysis of Oceanographic data, including 'ADCP' measurements, measurements made with 'argo' floats, 'CTD' measurements, sectional data, sea-level time series, coastline and topographic data, etc. Provides specialized functions for calculating seawater properties such as potential temperature in either the 'UNESCO' or 'TEOS-10' equation of state. Produces graphical displays that conform to the conventions of the Oceanographic literature. This package is discussed extensively by Kelley (2018) "Oceanographic Analysis with R" <doi:10.1007/978-1-4939-8844-0>.
Author: Dan Kelley [aut, cre] , Clark Richards [aut] , Chantelle Layton [ctb] coauthor), British Geological Survey [ctb, cph]
Maintainer: Dan Kelley <Dan.Kelley@Dal.Ca>

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Package nestedcv readmission to version 0.9.0 with previous version 0.8.2 dated 2026-04-10

Title: Nested Cross-Validation with 'glmnet' and 'caret'
Description: Implements nested k*l-fold cross-validation for lasso and elastic-net regularised linear models via the 'glmnet' package and other machine learning models via the 'caret' package <doi:10.1093/bioadv/vbad048>. Cross-validation of 'glmnet' alpha mixing parameter and embedded fast filter functions for feature selection are provided. Described as double cross-validation by Stone (1977) <doi:10.1111/j.2517-6161.1977.tb01603.x>. Also implemented is a method using outer CV to measure unbiased model performance metrics when fitting Bayesian linear and logistic regression shrinkage models using the horseshoe prior over parameters to encourage a sparse model as described by Piironen & Vehtari (2017) <doi:10.1214/17-EJS1337SI>.
Author: Myles Lewis [aut, cre] , Athina Spiliopoulou [aut] , Cankut Cubuk [ctb] , David Rios Santini [ctb], Katriona Goldmann [ctb] , Ryan C. Thompson [ctb]
Maintainer: Myles Lewis <myles.lewis@qmul.ac.uk>

This is a re-admission after prior archival of version 0.8.2 dated 2026-04-10

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Package mvfmr updated to version 0.2.0 with previous version 0.1.0 dated 2026-02-09

Title: Functional Multivariable Mendelian Randomization
Description: Implements Multivariable Functional Mendelian Randomization (MV-FMR) to estimate time-varying causal effects of multiple longitudinal exposures on health outcomes. Extends univariable functional Mendelian Randomisation (MR) (Tian et al., 2024 <doi:10.1002/sim.10222>) to the multivariable setting, enabling joint estimation of multiple time-varying exposures with pleiotropy and mediation scenarios. Key features include: (1) data-driven cross-validation for basis component selection, (2) handling of mediation pathways between exposures, (3) support for both continuous and binary outcomes using Generalized Method of Moments (GMM) and control function approaches, (4) one-sample and two-sample MR designs, (5) bootstrap inference and instrument diagnostics including Q-statistics for overidentification testing. Methods are described in Fontana et al. (2025) <doi:10.48550/arXiv.2512.19064>.
Author: Nicole Fontana [aut, cre], Francesca Ieva [aut, ths], Piercesare Secchi [aut, ths]
Maintainer: Nicole Fontana <nicole.fontana@polimi.it>

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Package HNPclassifier updated to version 0.2.1 with previous version 0.2.0 dated 2026-06-27

Title: Hierarchical Neyman-Pearson Classification for Ordered Classes
Description: The Hierarchical Neyman-Pearson (H-NP) classification framework extends the Neyman-Pearson classification paradigm to multi-class settings where classes have a natural priority ordering. This is particularly useful for classification in unbalanced dataset, for example, disease severity classification, where under-classification errors (misclassifying patients into less severe categories) are more consequential than other misclassifications. The package implements H-NP umbrella algorithms that controls under-classification errors under user specified control levels with high probability. It supports the creation of H-NP classifiers using scoring functions based on built-in classification methods (including logistic regression, support vector machines, and random forests), as well as user-trained scoring functions. The package exports `base_function()` to train these built-in base learners directly for use in the H-NP pipeline.
Author: Che Shen [aut, cre] , Lujia Yang [aut] , Lijia Wang [aut] , Shunan Yao [aut]
Maintainer: Che Shen <chshen3-c@my.cityu.edu.hk>

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Package ume updated to version 1.7.1 with previous version 1.6.1 dated 2026-05-09

Title: Ultrahigh-Resolution Mass Spectrometry Data Evaluation for Complex Organic Matter
Description: Provides tools for assigning molecular formulas from exact masses obtained by ultrahigh-resolution mass spectrometry. The methodology follows the workflow described in Leefmann et al. (2019) <doi:10.1002/rcm.8315>. The package supports the inspection, filtering and visualization of molecular formula data and includes utilities for calculating common molecular parameters (e.g., double bond equivalents, DBE). A graphical user interface is available via the 'shiny'-based 'ume' application.
Author: Boris Koch [aut, cre] , Stephan Frickenhaus [ctb] , Shuxian Gao [ctb] , Oliver Lechtenfeld [ctb] , Tim Leefmann [ctb] , Fabian Moye [ctb]
Maintainer: Boris Koch <boris.koch@awi.de>

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