Sun, 15 Sep 2024

Package gdverse updated to version 1.0-1 with previous version 1.0.0 dated 2024-09-09

Title: Analysis of Spatial Stratified Heterogeneity
Description: Analyzing spatial factors and exploring spatial associations based on the concept of spatial stratified heterogeneity, and also takes into account local spatial dependencies, spatial interpretability, potential spatial interactions, and robust spatial stratification. Additionally, it supports geographical detector models established in academic literature.
Author: Wenbo Lv [aut, cre, cph] , Yangyang Lei [aut] , Yongze Song [aut] , Wufan Zhao [aut] , Jianwu Yan [aut]
Maintainer: Wenbo Lv <lyu.geosocial@gmail.com>

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Package glmm.hp updated to version 0.1-5 with previous version 0.1-4 dated 2024-08-24

Title: Hierarchical Partitioning of Marginal R2 for Generalized Mixed-Effect Models
Description: Conducts hierarchical partitioning to calculate individual contributions of each predictor (fixed effects) towards marginal R2 for generalized linear mixed-effect model (including lm, glm and glmm) based on output of r.squaredGLMM() in 'MuMIn', applying the algorithm of Lai J.,Zou Y., Zhang S.,Zhang X.,Mao L.(2022)glmm.hp: an R package for computing individual effect of predictors in generalized linear mixed models.Journal of Plant Ecology,15(6)1302-1307<doi:10.1093/jpe/rtac096>.
Author: Jiangshan Lai [aut, cre] , Kim Nimon [aut]
Maintainer: Jiangshan Lai <lai@njfu.edu.cn>

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Package timeordered updated to version 1.0.1 with previous version 1.0.0 dated 2023-08-20

Title: Time-Ordered and Time-Aggregated Network Analyses
Description: Approaches for incorporating time into network analysis. Methods include: construction of time-ordered networks (temporal graphs); shortest-time and shortest-path-length analyses; resource spread calculations; data resampling and rarefaction for null model construction; reduction to time-aggregated networks with variable window sizes; application of common descriptive statistics to these networks; vector clock latencies; and plotting functionalities. The package supports <doi:10.1371/journal.pone.0020298>.
Author: Benjamin Wong Blonder [aut, cre]
Maintainer: Benjamin Wong Blonder <benjamin.blonder@berkeley.edu>

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Package RcppFastAD updated to version 0.0.3 with previous version 0.0.2 dated 2023-03-06

Title: 'Rcpp' Bindings to 'FastAD' Auto-Differentiation
Description: The header-only 'C++' template library 'FastAD' for automatic differentiation <https://github.com/JamesYang007/FastAD> is provided by this package, along with a few illustrative examples that can all be called from R.
Author: Dirk Eddelbuettel [aut, cre] , James Yang [aut]
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package LMest updated to version 3.2.2 with previous version 3.2.1 dated 2024-09-09

Title: Generalized Latent Markov Models
Description: Latent Markov models for longitudinal continuous and categorical data. See Bartolucci, Pandolfi, Pennoni (2017)<doi:10.18637/jss.v081.i04>.
Author: Francesco Bartolucci [aut, cre], Silvia Pandolfi [aut], Fulvia Pennoni [aut], Alessio Farcomeni [ctb], Alessio Serafini [ctb]
Maintainer: Francesco Bartolucci <francesco.bartolucci@unipg.it>

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Package epiR updated to version 2.0.76 with previous version 2.0.75 dated 2024-06-17

Title: Tools for the Analysis of Epidemiological Data
Description: Tools for the analysis of epidemiological and surveillance data. Contains functions for directly and indirectly adjusting measures of disease frequency, quantifying measures of association on the basis of single or multiple strata of count data presented in a contingency table, computation of confidence intervals around incidence risk and incidence rate estimates and sample size calculations for cross-sectional, case-control and cohort studies. Surveillance tools include functions to calculate an appropriate sample size for 1- and 2-stage representative freedom surveys, functions to estimate surveillance system sensitivity and functions to support scenario tree modelling analyses.
Author: Mark Stevenson [aut, cre] , Evan Sergeant [aut], Cord Heuer [ctb], Telmo Nunes [ctb], Cord Heuer [ctb], Jonathon Marshall [ctb], Javier Sanchez [ctb], Ron Thornton [ctb], Jeno Reiczigel [ctb], Jim Robison-Cox [ctb], Paola Sebastiani [ctb], Peter Soly [...truncated...]
Maintainer: Mark Stevenson <mark.stevenson1@unimelb.edu.au>

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Package sandwich updated to version 3.1-1 with previous version 3.1-0 dated 2023-12-11

Title: Robust Covariance Matrix Estimators
Description: Object-oriented software for model-robust covariance matrix estimators. Starting out from the basic robust Eicker-Huber-White sandwich covariance methods include: heteroscedasticity-consistent (HC) covariances for cross-section data; heteroscedasticity- and autocorrelation-consistent (HAC) covariances for time series data (such as Andrews' kernel HAC, Newey-West, and WEAVE estimators); clustered covariances (one-way and multi-way); panel and panel-corrected covariances; outer-product-of-gradients covariances; and (clustered) bootstrap covariances. All methods are applicable to (generalized) linear model objects fitted by lm() and glm() but can also be adapted to other classes through S3 methods. Details can be found in Zeileis et al. (2020) <doi:10.18637/jss.v095.i01>, Zeileis (2004) <doi:10.18637/jss.v011.i10> and Zeileis (2006) <doi:10.18637/jss.v016.i09>.
Author: Achim Zeileis [aut, cre] , Thomas Lumley [aut] , Nathaniel Graham [ctb] , Susanne Koell [ctb]
Maintainer: Achim Zeileis <Achim.Zeileis@R-project.org>

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Package locuszoomr updated to version 0.3.5 with previous version 0.3.4 dated 2024-09-06

Title: Gene Locus Plot with Gene Annotations
Description: Publication-ready regional gene locus plots similar to those produced by the web interface 'LocusZoom' <https://my.locuszoom.org>, but running locally in R. Genetic or genomic data with gene annotation tracks are plotted via R base graphics, 'ggplot2' or 'plotly', allowing flexibility and easy customisation including laying out multiple locus plots on the same page. It uses the 'LDlink' API <https://ldlink.nih.gov/?tab=apiaccess> to query linkage disequilibrium data from the 1000 Genomes Project and can overlay this on plots.
Author: Myles Lewis [aut, cre]
Maintainer: Myles Lewis <myles.lewis@qmul.ac.uk>

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New package TLIC with initial version 0.1
Package: TLIC
Title: The LIC for T Distribution Regression Analysis
Version: 0.1
Date: 2024-08-30
Description: This comprehensive toolkit for T-distribution regression, known as the analysis of "TLIC" (T-distribution Linear regression Integrated Corrector), adopts ordinary least squares method and assumes that errors follow a T-distribution. This approach gives it an advantage when dealing with small samples or non-normal error distributions, and can provide more robust parameter estimation and hypothesis testing results.The philosophy of the package is described in Guo G. (2020) <doi:10.1080/02664763.2022.2053949>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: stats
NeedsCompilation: no
Packaged: 2024-09-11 01:32:24 UTC; A
Author: Guangbao Guo [aut, cre] , Guofu Jing [aut]
Maintainer: Guangbao Guo <ggb11111111@163.com>
Repository: CRAN
Date/Publication: 2024-09-15 20:10:02 UTC

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New package spectralAnomaly with initial version 0.1.1
Package: spectralAnomaly
Title: Detect Anomalies Using the Spectral Residual Algorithm
Version: 0.1.1
Description: Apply the spectral residual algorithm to data, such as a time series, to detect anomalies. Anomaly scores can be used to determine outliers based upon a threshold or fed into more sophisticated prediction models. Methods are based upon "Time-Series Anomaly Detection Service at Microsoft", Ren, H., Xu, B., Wang, Y., et al., (2019) <doi:10.48550/arXiv.1906.03821>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: stats, utils
Suggests: testthat (>= 3.0.0)
URL: https://al-obrien.github.io/spectralAnomaly/, https://github.com/al-obrien/spectralAnomaly
BugReports: https://github.com/al-obrien/spectralAnomaly/issues
NeedsCompilation: no
Packaged: 2024-09-12 21:32:26 UTC; allen
Author: Allen OBrien [aut, cre, cph]
Maintainer: Allen OBrien <allen.g.obrien@gmail.com>
Repository: CRAN
Date/Publication: 2024-09-15 21:00:02 UTC

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New package RandomWalker with initial version 0.1.0
Package: RandomWalker
Title: Generate Random Walks Compatible with the 'tidyverse'
Version: 0.1.0
Description: Generates random walks of various types by providing a set of functions that are compatible with the 'tidyverse'. The functions provided in the package make it simple to create random walks with a variety of properties, such as how many simulations to run, how many steps to take, and the distribution of random walk itself.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://www.spsanderson.com/RandomWalker/, https://github.com/spsanderson/RandomWalker
BugReports: https://github.com/spsanderson/RandomWalker/issues
Depends: R (>= 4.1.0)
Imports: dplyr, tidyr, purrr, rlang, patchwork, NNS
Suggests: knitr, rmarkdown, stats, ggplot2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-09-12 12:53:51 UTC; ssanders
Author: Steven Sanderson [aut, cre, cph] , Antti Rask [aut, cph]
Maintainer: Steven Sanderson <spsanderson@gmail.com>
Repository: CRAN
Date/Publication: 2024-09-15 20:30:24 UTC

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New package PytrendsLongitudinalR with initial version 0.1.3
Package: PytrendsLongitudinalR
Title: Create Longitudinal Google Trends Data
Version: 0.1.3
Description: 'Google Trends' provides cross-sectional and time-series data on searches, but lacks readily available longitudinal data. Researchers, who want to create longitudinal 'Google Trends' on their own, face practical challenges, such as normalized counts that make it difficult to combine cross-sectional and time-series data and limitations in data formats and timelines that limit data granularity over extended time periods. This package addresses these issues and enables researchers to generate longitudinal 'Google Trends' data. This package is built on 'pytrends', a Python library that acts as the unofficial 'Google Trends API' to collect 'Google Trends' data. As long as the 'Google Trends API', 'pytrends' and all their dependencies are working, this package will work. During testing, we noticed that for the same input (keyword, topic, data_format, timeline), the output index can vary from time to time. Besides, if the keyword is not very popular, then the resulting dataset will contain a [...truncated...]
Encoding: UTF-8
Imports: lubridate, jsonlite, reticulate, utils
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
License: MIT + file LICENSE
NeedsCompilation: no
Packaged: 2024-09-12 09:11:07 UTC; malika
Author: Taeyong Park [cre, cph, aut], Malika Dixit [aut]
Maintainer: Taeyong Park <taeyongp@andrew.cmu.edu>
Repository: CRAN
Date/Publication: 2024-09-15 20:10:05 UTC

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Package pls updated to version 2.8-5 with previous version 2.8-4 dated 2024-08-01

Title: Partial Least Squares and Principal Component Regression
Description: Multivariate regression methods Partial Least Squares Regression (PLSR), Principal Component Regression (PCR) and Canonical Powered Partial Least Squares (CPPLS).
Author: Kristian Hovde Liland [aut, cre], Bjoern-Helge Mevik [aut], Ron Wehrens [aut], Paul Hiemstra [ctb]
Maintainer: Kristian Hovde Liland <kristian.liland@nmbu.no>

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New package mvcor with initial version 1.0
Package: mvcor
Title: Correlation Coefficients for Multivariate Data
Version: 1.0
Date: 2024-09-12
Author: Michail Tsagris [aut, cre]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>
Depends: R (>= 4.0)
Imports: Rfast, stats
Description: Correlation coefficients for multivariate data, namely the squared correlation coefficient and the RV coefficient (multivariate generalization of the squared Pearson correlation coefficient). References include Mardia K.V., Kent J.T. and Bibby J.M. (1979). "Multivariate Analysis". ISBN: 978-0124712522. London: Academic Press.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2024-09-12 11:42:35 UTC; mtsag
Repository: CRAN
Date/Publication: 2024-09-15 20:30:07 UTC

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New package ggalign with initial version 0.0.3
Package: ggalign
Title: Align Multiple 'ggplot' Objects
Version: 0.0.3
Description: A 'ggplot2' extension offers various tools for organizing and arranging plots. It is designed to consistently align a specific axis across multiple 'ggplot' objects, making it especially useful for plots requiring data order manipulation. A typical use case includes organizing combinations like a dendrogram and a heatmap.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: ggplot2
Imports: cli, ggh4x, grid, gtable, methods, rlang (>= 1.1.0), stats, tibble, tidyr
ByteCompile: true
URL: https://github.com/Yunuuuu/ggalign, https://yunuuuu.github.io/ggalign/
BugReports: https://github.com/Yunuuuu/ggalign/issues
Suggests: gridGraphics, knitr, patchwork, rmarkdown, scales, testthat (>= 3.0.0), vdiffr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-09-12 11:00:38 UTC; yun
Author: Yun Peng [aut, cre, cph]
Maintainer: Yun Peng <yunyunp96@163.com>
Repository: CRAN
Date/Publication: 2024-09-15 20:30:10 UTC

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New package gammi with initial version 0.1
Package: gammi
Title: Generalized Additive Mixed Model Interface
Version: 0.1
Date: 2024-09-12
Description: An interface for fitting generalized additive models (GAMs) and generalized additive mixed models (GAMMs) using the 'lme4' package as the computational engine, as described in Helwig (2024) <doi:10.3390/stats7010003>. Supports default and formula methods for model specification, additive and tensor product splines for capturing nonlinear effects, and automatic determination of spline type based on the class of each predictor. Includes an S3 plot method for visualizing the (nonlinear) model terms, an S3 predict method for forming predictions from a fit model, and an S3 summary method for conducting significance testing using the Bayesian interpretation of a smoothing spline.
License: GPL (>= 2)
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: lme4, Matrix, methods
NeedsCompilation: no
Packaged: 2024-09-12 14:59:33 UTC; nate
Author: Nathaniel E. Helwig [aut, cre]
Maintainer: Nathaniel E. Helwig <helwig@umn.edu>
Repository: CRAN
Date/Publication: 2024-09-15 20:30:15 UTC

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New package equiBSPD with initial version 0.1.0
Package: equiBSPD
Title: Equivalent Estimation Balanced Split Plot Designs
Version: 0.1.0
Maintainer: Bijoy Chanda <bijoychanda08@gmail.com>
Description: In agricultural, post-harvest and processing, engineering and industrial experiments factors are often differentiated with ease with which they can change from experimental run to experimental run. This is due to the fact that one or more factors may be expensive or time consuming to change i.e. hard-to-change factors. These factors restrict the use of complete randomization as it may make the experiment expensive and time consuming. Split plot designs can be used for such situations. In general model estimation of split plot designs require the use of generalized least squares (GLS). However for some split-plot designs ordinary least squares (OLS) estimates are equivalent to generalized least squares (GLS) estimates. These types of designs are known in literature as equivalent-estimation split-plot design. For method details see, Macharia, H. and Goos, P.(2010) <doi:10.1080/00224065.2010.11917833>.Balanced split plot designs are designs which have an equal number of subplots wit [...truncated...]
License: GPL-3
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2024-09-12 14:10:22 UTC; ICAR-CAFRI
Author: Bijoy Chanda [aut, cre, ctb], Arpan Bhowmik [aut, ctb], Cini Varghese [aut], Seema Jaggi [aut, ctb], Eldho Varghese [aut, ctb], BN Mandal [ctb], Anindita Datta [ctb], Soumen Pal [ctb], Dibyendu Deb [ctb]
Repository: CRAN
Date/Publication: 2024-09-15 20:30:18 UTC

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New package CohortGenerator with initial version 0.11.1
Package: CohortGenerator
Title: Cohort Generation for the OMOP Common Data Model
Version: 0.11.1
Date: 2024-09-12
Maintainer: Anthony Sena <sena@ohdsi.org>
Description: Generate cohorts and subsets using an Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) Database. Cohorts are defined using 'CIRCE' (<https://github.com/ohdsi/circe-be>) or SQL compatible with 'SqlRender' (<https://github.com/OHDSI/SqlRender>).
Depends: DatabaseConnector (>= 5.0.0), R (>= 3.6.0), R6
Imports: checkmate, digest, dplyr, lubridate, methods, ParallelLogger (>= 3.0.0), readr (>= 2.1.0), rlang, RJSONIO, jsonlite, ResultModelManager, SqlRender (>= 1.11.1), stringi (>= 1.7.6), tibble
Suggests: CirceR (>= 1.1.1), Eunomia, knitr, rmarkdown, testthat, withr, zip
License: Apache License
VignetteBuilder: knitr
URL: https://ohdsi.github.io/CohortGenerator/, https://github.com/OHDSI/CohortGenerator
BugReports: https://github.com/OHDSI/CohortGenerator/issues
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2024-09-12 21:33:31 UTC; asena5
Author: Anthony Sena [aut, cre], Jamie Gilbert [aut], Gowtham Rao [aut], Martijn Schuemie [aut], Observational Health Data Science and Informatics [cph]
Repository: CRAN
Date/Publication: 2024-09-15 21:00:06 UTC

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New package aftsem with initial version 1.0
Package: aftsem
Title: Semiparametric Accelerated Failure Time Model
Version: 1.0
Date: 2024-09-01
Maintainer: Martin Benedikt <benedma2@cvut.cz>
Description: Implements several basic algorithms for estimating regression parameters for semiparametric accelerated failure time (AFT) model. The main methods are: Jin rank-based method (Jin (2003) <doi:10.1093/biomet/90.2.341>), Heller’s estimating method (Heller (2012) <doi:10.1198/016214506000001257>), Polynomial smoothed Gehan function method (Chung (2013) <doi:10.1007/s11222-012-9333-9>), Buckley-James method (Buckley (1979) <doi:10.2307/2335161>) and Jin`s improved least squares method (Jin (2006) <doi:10.1093/biomet/93.1.147>). This package can be used for modeling right-censored data and for comparing different estimation algorithms.
License: GPL (>= 3)
BugReports: https://github.com/benedma2/aftsem-package/issues
Imports: survival, Rcpp (>= 1.0.10), stats, quantreg, optimx
URL: https://github.com/benedma2/aftsem-package
LinkingTo: Rcpp, RcppArmadillo
Depends: R (>= 4.2.0)
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2024-09-12 12:13:59 UTC; ivan
Author: Martin Benedikt [aut, cre]
Repository: CRAN
Date/Publication: 2024-09-15 20:30:21 UTC

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Package minic updated to version 1.0.1 with previous version 1.0 dated 2024-06-24

Title: Minimization Methods for Ill-Conditioned Problems
Description: Implementation of methods for minimizing ill-conditioned problems. Currently only includes regularized (quasi-)newton optimization (Kanzow and Steck et al. (2023), <doi:10.1007/s12532-023-00238-4>).
Author: Bert van der Veen [aut, cre]
Maintainer: Bert van der Veen <bert_van_der_veen@hotmail.com>

Diff between minic versions 1.0 dated 2024-06-24 and 1.0.1 dated 2024-09-15

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New package lavaan.printer with initial version 0.1.0
Package: lavaan.printer
Title: Helper Functions for Printing 'lavaan' Outputs
Version: 0.1.0
Description: Helpers for customizing selected outputs from 'lavaan' by Rosseel (2012) <doi:10.18637/jss.v048.i02> and print them. The functions are intended to be used by package developers in their packages and so are not designed to be user-friendly. They are designed to be let developers customize the tables by other functions. Currently the parameter estimates tables of a fitted object are supported.
License: GPL (>= 3)
Encoding: UTF-8
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
Imports: utils, methods, lavaan
Depends: R (>= 4.0.0)
URL: https://sfcheung.github.io/lavaan.printer/
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-09-12 00:11:33 UTC; shufa
Author: Shu Fai Cheung [aut, cre]
Maintainer: Shu Fai Cheung <shufai.cheung@gmail.com>
Repository: CRAN
Date/Publication: 2024-09-15 20:00:02 UTC

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New package cancerR with initial version 0.1.0
Package: cancerR
Title: Classification of Cancer Using Administrative Data
Version: 0.1.0
Description: Classifies the type of cancer using routinely collected data commonly found in cancer registries from pathology reports. The package implements the International Classification of Diseases for Oncology, 3rd Edition site (topography), histology (morphology), and behaviour codes of neoplasms to classify cancer type <https://www.who.int/standards/classifications/other-classifications/international-classification-of-diseases-for-oncology>. Classification in children utilize the International Classification of Childhood Cancer by Steliarova-Foucher et al. (2005) <doi:10.1002/cncr.20910>. Adolescent and young adult cancer classification is based on Barr et al. (2020) <doi:10.1002/cncr.33041>.
License: GPL (>= 2)
URL: https://github.com/giancarlodigi/cancerR
BugReports: https://github.com/giancarlodigi/cancerR/issues
Depends: R (>= 2.10)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2024-09-11 21:13:25 UTC; giancarlo
Author: Giancarlo Di Giuseppe [aut, cre, cph]
Maintainer: Giancarlo Di Giuseppe <digi.giancarlo@proton.me>
Repository: CRAN
Date/Publication: 2024-09-15 19:40:02 UTC

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Package CFtime updated to version 1.4.1 with previous version 1.4.0 dated 2024-06-05

Title: Using CF-Compliant Calendars with Climate Projection Data
Description: Support for all calendars as specified in the Climate and Forecast (CF) Metadata Conventions for climate and forecasting data. The CF Metadata Conventions is widely used for distributing files with climate observations or projections, including the Coupled Model Intercomparison Project (CMIP) data used by climate change scientists and the Intergovernmental Panel on Climate Change (IPCC). This package specifically allows the user to work with any of the CF-compliant calendars (many of which are not compliant with POSIXt). The CF time coordinate is formally defined in the CF Metadata Conventions document available at <https://cfconventions.org/Data/cf-conventions/cf-conventions-1.11/cf-conventions.html#time-coordinate>.
Author: Patrick Van Laake [aut, cre, cph]
Maintainer: Patrick Van Laake <patrick@vanlaake.net>

Diff between CFtime versions 1.4.0 dated 2024-06-05 and 1.4.1 dated 2024-09-15

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Package tinytex updated to version 0.53 with previous version 0.52 dated 2024-07-18

Title: Helper Functions to Install and Maintain TeX Live, and Compile LaTeX Documents
Description: Helper functions to install and maintain the 'LaTeX' distribution named 'TinyTeX' (<https://yihui.org/tinytex/>), a lightweight, cross-platform, portable, and easy-to-maintain version of 'TeX Live'. This package also contains helper functions to compile 'LaTeX' documents, and install missing 'LaTeX' packages automatically.
Author: Yihui Xie [aut, cre, cph] , Posit Software, PBC [cph, fnd], Christophe Dervieux [ctb] , Devon Ryan [ctb] , Ethan Heinzen [ctb], Fernando Cagua [ctb]
Maintainer: Yihui Xie <xie@yihui.name>

Diff between tinytex versions 0.52 dated 2024-07-18 and 0.53 dated 2024-09-15

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Package mixhvg updated to version 1.0.1 with previous version 0.2.1 dated 2024-09-01

Title: Mixture of Multiple Highly Variable Feature Selection Methods
Description: Highly variable gene selection methods, including popular public available methods, and also the mixture of multiple highly variable gene selection methods, <https://github.com/RuzhangZhao/mixhvg>. Reference: <doi:10.1101/2024.08.25.608519>.
Author: Ruzhang Zhao [aut, cre] , Hongkai Ji [aut]
Maintainer: Ruzhang Zhao <ruzhangzhao@gmail.com>

Diff between mixhvg versions 0.2.1 dated 2024-09-01 and 1.0.1 dated 2024-09-15

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Package IsoplotR updated to version 6.3 with previous version 6.2 dated 2024-05-04

Title: Statistical Toolbox for Radiometric Geochronology
Description: Plots U-Pb data on Wetherill and Tera-Wasserburg concordia diagrams. Calculates concordia and discordia ages. Performs linear regression of measurements with correlated errors using 'York', 'Titterington', 'Ludwig' and Omnivariant Generalised Least-Squares ('OGLS') approaches. Generates Kernel Density Estimates (KDEs) and Cumulative Age Distributions (CADs). Produces Multidimensional Scaling (MDS) configurations and Shepard plots of multi-sample detrital datasets using the Kolmogorov-Smirnov distance as a dissimilarity measure. Calculates 40Ar/39Ar ages, isochrons, and age spectra. Computes weighted means accounting for overdispersion. Calculates U-Th-He (single grain and central) ages, logratio plots and ternary diagrams. Processes fission track data using the external detector method and LA-ICP-MS, calculates central ages and plots fission track and other data on radial (a.k.a. 'Galbraith') plots. Constructs total Pb-U, Pb-Pb, Th-Pb, K-Ca, Re-Os, Sm-Nd, Lu-Hf, Rb-Sr and 230Th-U isoch [...truncated...]
Author: Pieter Vermeesch [aut, cre]
Maintainer: Pieter Vermeesch <p.vermeesch@ucl.ac.uk>

Diff between IsoplotR versions 6.2 dated 2024-05-04 and 6.3 dated 2024-09-15

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Package xaringanthemer updated to version 0.4.3 with previous version 0.4.2 dated 2022-08-20

Title: Custom 'xaringan' CSS Themes
Description: Create beautifully color-coordinated and customized themes for your 'xaringan' slides, without writing any CSS. Complete your slide theme with 'ggplot2' themes that match the font and colors used in your slides. Customized styles can be created directly in your slides' 'R Markdown' source file or in a separate external script.
Author: Garrick Aden-Buie [aut, cre]
Maintainer: Garrick Aden-Buie <garrick@adenbuie.com>

Diff between xaringanthemer versions 0.4.2 dated 2022-08-20 and 0.4.3 dated 2024-09-15

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 xaringanthemer-0.4.2/xaringanthemer/tests/manual                                                         |only
 xaringanthemer-0.4.3/xaringanthemer/DESCRIPTION                                                          |    8 
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 xaringanthemer-0.4.3/xaringanthemer/NAMESPACE                                                            |    2 
 xaringanthemer-0.4.3/xaringanthemer/NEWS.md                                                              |   44 -
 xaringanthemer-0.4.3/xaringanthemer/R/ggplot2.R                                                          |    1 
 xaringanthemer-0.4.3/xaringanthemer/R/style_extra_css.R                                                  |    2 
 xaringanthemer-0.4.3/xaringanthemer/R/style_font_default.R                                               |    3 
 xaringanthemer-0.4.3/xaringanthemer/R/utils.R                                                            |    3 
 xaringanthemer-0.4.3/xaringanthemer/R/xaringanthemer-package.R                                           |   56 -
 xaringanthemer-0.4.3/xaringanthemer/README.md                                                            |    4 
 xaringanthemer-0.4.3/xaringanthemer/build/vignette.rds                                                   |binary
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Package xgrove updated to version 0.1-12 with previous version 0.1-11 dated 2024-08-23

Title: Explanation Groves
Description: Compute surrogate explanation groves for predictive machine learning models and analyze complexity vs. explanatory power of an explanation according to Szepannek, G. and von Holt, B. (2023) <doi:10.1007/s41237-023-00205-2>.
Author: Gero Szepannek [aut, cre]
Maintainer: Gero Szepannek <gero.szepannek@web.de>

Diff between xgrove versions 0.1-11 dated 2024-08-23 and 0.1-12 dated 2024-09-15

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Package tidybayes updated to version 3.0.7 with previous version 3.0.6 dated 2023-08-12

Title: Tidy Data and 'Geoms' for Bayesian Models
Description: Compose data for and extract, manipulate, and visualize posterior draws from Bayesian models ('JAGS', 'Stan', 'rstanarm', 'brms', 'MCMCglmm', 'coda', ...) in a tidy data format. Functions are provided to help extract tidy data frames of draws from Bayesian models and that generate point summaries and intervals in a tidy format. In addition, 'ggplot2' 'geoms' and 'stats' are provided for common visualization primitives like points with multiple uncertainty intervals, eye plots (intervals plus densities), and fit curves with multiple, arbitrary uncertainty bands.
Author: Matthew Kay [aut, cre], Timothy Mastny [ctb]
Maintainer: Matthew Kay <mjskay@northwestern.edu>

Diff between tidybayes versions 3.0.6 dated 2023-08-12 and 3.0.7 dated 2024-09-15

 DESCRIPTION                                                                          |   18 
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 NAMESPACE                                                                            |  961 -
 NEWS.md                                                                              |  517 
 R/add_draws.R                                                                        |  198 
 R/compare_levels.R                                                                   |  442 
 R/compose_data.R                                                                     |  770 
 R/density_bins.R                                                                     |  194 
 R/deprecated.R                                                                       | 2164 +-
 R/emmeans_comparison.R                                                               |  162 
 R/epred_draws.R                                                                      |  164 
 R/epred_rvars.R                                                                      |  156 
 R/flip_aes.R                                                                         |  101 
 R/gather_draws.R                                                                     |   75 
 R/gather_emmeans_draws.R                                                             |  276 
 R/gather_pairs.R                                                                     |  290 
 R/gather_rvars.R                                                                     |   90 
 R/gather_variables.R                                                                 |  204 
 R/get_variables.R                                                                    |  106 
 R/ggdist-curve_interval.R                                                            |    6 
 R/ggdist-cut_cdf_qi.R                                                                |    6 
 R/ggdist-stat_pointinterval.R                                                        |   14 
 R/linpred_draws.R                                                                    |  216 
 R/linpred_rvars.R                                                                    |  156 
 R/nest_rvars.R                                                                       |  175 
 R/predict_curve.R                                                                    |  258 
 R/predicted_draws.R                                                                  |  800 -
 R/predicted_rvars.R                                                                  |  512 
 R/recover_types.R                                                                    |  364 
 R/residual_draws.R                                                                   |  128 
 R/sample_draws.R                                                                     |  132 
 R/spread_draws.R                                                                     | 1399 -
 R/spread_rvars.R                                                                     |  564 
 R/summarise_draws.R                                                                  |  152 
 R/testthat.R                                                                         |   39 
 R/tidy_draws.R                                                                       |  584 
 R/tidybayes-models.R                                                                 |  158 
 R/tidybayes-package.R                                                                |   73 
 R/ungather_draws.R                                                                   |  146 
 R/unspread_draws.R                                                                   |  230 
 R/util.R                                                                             |  358 
 R/x_at_y.R                                                                           |  174 
 build/partial.rdb                                                                    |binary
 build/vignette.rds                                                                   |binary
 inst/doc/tidy-brms.R                                                                 | 1228 -
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 inst/doc/tidy-brms.html                                                              | 5674 +++----
 inst/doc/tidy-posterior.R                                                            |  926 -
 inst/doc/tidy-posterior.Rmd                                                          | 1632 +-
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Package diathor (with last version 0.1.0) was removed from CRAN

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

2022-03-16 0.1.0

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Package TestFunctions updated to version 0.2.2 with previous version 0.2.1 dated 2024-01-21

Title: Test Functions for Simulation Experiments and Evaluating Optimization and Emulation Algorithms
Description: Test functions are often used to test computer code. They are used in optimization to test algorithms and in metamodeling to evaluate model predictions. This package provides test functions that can be used for any purpose.
Author: Collin Erickson [aut, cre]
Maintainer: Collin Erickson <collinberickson@gmail.com>

Diff between TestFunctions versions 0.2.1 dated 2024-01-21 and 0.2.2 dated 2024-09-15

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Package sdsfun updated to version 0.2.0 with previous version 0.1.1 dated 2024-09-08

Title: Spatial Data Science Complementary Features
Description: Wrapping and supplementing commonly used functions in the R ecosystem related to spatial data science, while serving as a basis for other packages maintained by Wenbo Lv.
Author: Wenbo Lv [aut, cre, cph]
Maintainer: Wenbo Lv <lyu.geosocial@gmail.com>

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Package rvec updated to version 0.0.7 with previous version 0.0.6 dated 2023-11-08

Title: Vector Representing a Random Variable
Description: Random vectors, called rvecs. An rvec holds multiple draws, but tries to behave like a standard R vector, including working well in data frames. Rvecs are useful for working with output from a simulation or a Bayesian analysis.
Author: John Bryant [aut, cre], Bayesian Demography Limited [cph]
Maintainer: John Bryant <john@bayesiandemography.com>

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