Wed, 20 Mar 2024

Package melt updated to version 1.11.2 with previous version 1.11.1 dated 2024-03-01

Title: Multiple Empirical Likelihood Tests
Description: Performs multiple empirical likelihood tests. It offers an easy-to-use interface and flexibility in specifying hypotheses and calibration methods, extending the framework to simultaneous inferences. The core computational routines are implemented using the 'Eigen' 'C++' library and 'RcppEigen' interface, with 'OpenMP' for parallel computation. Details of the testing procedures are provided in Kim, MacEachern, and Peruggia (2023) <doi:10.1080/10485252.2023.2206919>. A companion paper by Kim, MacEachern, and Peruggia (2024) <doi:10.18637/jss.v108.i05> is available for further information. This work was supported by the U.S. National Science Foundation under Grants No. SES-1921523 and DMS-2015552.
Author: Eunseop Kim [aut, cph, cre], Steven MacEachern [ctb, ths], Mario Peruggia [ctb, ths], Pierre Chausse [rev], Alex Stringer [rev]
Maintainer: Eunseop Kim <markean@pm.me>

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Package ggscidca updated to version 0.2.0 with previous version 0.1.9 dated 2024-03-13

Title: Plotting Decision Curve Analysis with Coloured Bars
Description: Decision curve analysis is a method for evaluating and comparing prediction models that incorporates clinical consequences, requires only the data set on which the models are tested, and can be applied to models that have either continuous or dichotomous results. The 'ggscidca' package adds coloured bars of discriminant relevance to the traditional decision curve. Improved practicality and aesthetics. This method was described by Balachandran VP (2015) <doi:10.1016/S1470-2045(14)71116-7>.
Author: Qiang Liu [aut, cre]
Maintainer: Qiang Liu <dege857@163.com>

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Package finetune updated to version 1.2.0 with previous version 1.1.0 dated 2023-04-19

Title: Additional Functions for Model Tuning
Description: The ability to tune models is important. 'finetune' enhances the 'tune' package by providing more specialized methods for finding reasonable values of model tuning parameters. Two racing methods described by Kuhn (2014) <arXiv:1405.6974> are included. An iterative search method using generalized simulated annealing (Bohachevsky, Johnson and Stein, 1986) <doi:10.1080/00401706.1986.10488128> is also included.
Author: Max Kuhn [aut, cre] , Posit Software, PBC [cph, fnd]
Maintainer: Max Kuhn <max@posit.co>

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Package jmBIG updated to version 0.1.2 with previous version 0.1.1 dated 2023-10-29

Title: Joint Longitudinal and Survival Model for Big Data
Description: Provides analysis tools for big data where the sample size is very large. It offers a suite of functions for fitting and predicting joint models, which allow for the simultaneous analysis of longitudinal and time-to-event data. This statistical methodology is particularly useful in medical research where there is often interest in understanding the relationship between a longitudinal biomarker and a clinical outcome, such as survival or disease progression. This can be particularly useful in a clinical setting where it is important to be able to predict how a patient's health status may change over time. Overall, this package provides a comprehensive set of tools for joint modeling of BIG data obtained as survival and longitudinal outcomes with both Bayesian and non-Bayesian approaches. Its versatility and flexibility make it a valuable resource for researchers in many different fields, particularly in the medical and health sciences.
Author: Atanu Bhattacharjee [aut, cre, ctb], Bhrigu Kumar Rajbongshi [aut, ctb], Gajendra K Vishwakarma [aut, ctb]
Maintainer: Atanu Bhattacharjee <atanustat@gmail.com>

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Package geonapi updated to version 0.7-1 with previous version 0.7 dated 2023-07-10

Title: 'GeoNetwork' API R Interface
Description: Provides an R interface to the 'GeoNetwork' API (<https://geonetwork-opensource.org/#api>) allowing to upload and publish metadata in a 'GeoNetwork' web-application and expose it to OGC CSW.
Author: Emmanuel Blondel [aut, cre]
Maintainer: Emmanuel Blondel <emmanuel.blondel1@gmail.com>

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Package BeeBDC updated to version 1.1.0 with previous version 1.0.4 dated 2024-02-13

Title: Occurrence Data Cleaning
Description: Flags and checks occurrence data that are in Darwin Core format. The package includes generic functions and data as well as some that are specific to bees. This package is meant to build upon and be complimentary to other excellent occurrence cleaning packages, including 'bdc' and 'CoordinateCleaner'. This package uses datasets from several sources and particularly from the Discover Life Website, created by Ascher and Pickering (2020). For further information, please see the original publication and package website. Publication - Dorey et al. (2023) <doi:10.1101/2023.06.30.547152> and package website - Dorey et al. (2023) <https://github.com/jbdorey/BeeBDC>.
Author: James B. Dorey [aut, cre, cph] , Robert L. O'Reilly [aut] , Silas Bossert [aut] , Erica E. Fischer [aut]
Maintainer: James B. Dorey <jbdorey@me.com>

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Package tuneRanger updated to version 0.7 with previous version 0.5 dated 2019-04-16

Title: Tune Random Forest of the 'ranger' Package
Description: Tuning random forest with one line. The package is mainly based on the packages 'ranger' and 'mlrMBO'.
Author: Philipp Probst [aut, cre], Simon Klau [ctb]
Maintainer: Philipp Probst <philipp_probst@gmx.de>

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Package survstan updated to version 0.0.7 with previous version 0.0.6.1 dated 2024-02-05

Title: Fitting Survival Regression Models via 'Stan'
Description: Parametric survival regression models under the maximum likelihood approach via 'Stan'. Implemented regression models include accelerated failure time models, proportional hazards models, proportional odds models, accelerated hazard models, Yang and Prentice models, and extended hazard models. Available baseline survival distributions include exponential, Weibull, log-normal, log-logistic, gamma, generalized gamma, rayleigh, Gompertz and fatigue (Birnbaum-Saunders) distributions. References: Lawless (2002) <ISBN:9780471372158>; Bennett (1982) <doi:10.1002/sim.4780020223>; Chen and Wang(2000) <doi:10.1080/01621459.2000.10474236>; Demarqui and Mayrink (2021) <doi:10.1214/20-BJPS471>.
Author: Fabio Demarqui [aut, cre, cph] , Andrew Johnson [ctb]
Maintainer: Fabio Demarqui <fndemarqui@est.ufmg.br>

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Package RVerbalExpressions updated to version 0.1.1 with previous version 0.1.0 dated 2019-11-06

Title: Create Regular Expressions Easily
Description: Build regular expressions using grammar and functionality inspired by <https://github.com/VerbalExpressions>. Usage of the %>% is encouraged to build expressions in a chain-like fashion.
Author: Tyler Littlefield [aut, cre] , Dmytro Perepolkin [ctb]
Maintainer: Tyler Littlefield <tylurp1@gmail.com>

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Package rliger updated to version 2.0.0 with previous version 1.0.1 dated 2023-11-08

Title: Linked Inference of Genomic Experimental Relationships
Description: Uses an extension of nonnegative matrix factorization to identify shared and dataset-specific factors. See Welch J, Kozareva V, et al (2019) <doi:10.1016/j.cell.2019.05.006>, and Liu J, Gao C, Sodicoff J, et al (2020) <doi:10.1038/s41596-020-0391-8> for more details.
Author: Joshua Welch [aut], Yichen Wang [aut, cre], Chao Gao [aut], Jialin Liu [aut], Joshua Sodicoff [aut, ctb], Velina Kozareva [aut, ctb], Evan Macosko [aut, ctb], Paul Hoffman [ctb], Ilya Korsunsky [ctb], Robert Lee [ctb], Andrew Robbins [ctb]
Maintainer: Yichen Wang <wayichen@umich.edu>

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Package EBMAforecast updated to version 1.0.32 with previous version 1.0.31 dated 2023-11-10

Title: Estimate Ensemble Bayesian Model Averaging Forecasts using Gibbs Sampling or EM-Algorithms
Description: Create forecasts from multiple predictions using ensemble Bayesian model averaging (EBMA). EBMA models can be estimated using an expectation maximization (EM) algorithm or as fully Bayesian models via Gibbs sampling. The methods in this package are Montgomery, Hollenbach, and Ward (2015) <doi:10.1016/j.ijforecast.2014.08.001> and Montgomery, Hollenbach, and Ward (2012) <doi:10.1093/pan/mps002>.
Author: Florian M. Hollenbach [aut, cre] , Jacob M. Montgomery [aut], Michael D. Ward [aut]
Maintainer: Florian M. Hollenbach <fho.egb@cbs.dk>

Diff between EBMAforecast versions 1.0.31 dated 2023-11-10 and 1.0.32 dated 2024-03-20

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Package tiledb updated to version 0.25.0 with previous version 0.24.0 dated 2024-02-22

Title: Modern Database Engine for Multi-Modal Data via Sparse and Dense Multidimensional Arrays
Description: The modern database 'TileDB' introduces a powerful on-disk format for multi-modal data based on dimensional arrays. It supports dense and sparse arrays, dataframes and key-values stores, cloud storage ('S3', 'GCS', 'Azure'), chunked arrays, multiple compression, encryption and checksum filters, uses a fully multi-threaded implementation, supports parallel I/O, data versioning ('time travel'), metadata and groups. It is implemented as an embeddable cross-platform C++ library with APIs from several languages, and integrations.
Author: TileDB, Inc. [aut, cph], Dirk Eddelbuettel [cre]
Maintainer: Dirk Eddelbuettel <dirk@tiledb.com>

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Package VisualizeSimon2Stage updated to version 0.1.3 with previous version 0.1.2 dated 2023-10-19

Title: Visualize Simon's Two-Stage Design
Description: To visualize the probabilities of early termination, fail and success of Simon's two-stage design. To evaluate and visualize the operating characteristics of Simon's two-stage design.
Author: Tingting Zhan [aut, cre, cph]
Maintainer: Tingting Zhan <tingtingzhan@gmail.com>

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Package tune updated to version 1.2.0 with previous version 1.1.2 dated 2023-08-23

Title: Tidy Tuning Tools
Description: The ability to tune models is important. 'tune' contains functions and classes to be used in conjunction with other 'tidymodels' packages for finding reasonable values of hyper-parameters in models, pre-processing methods, and post-processing steps.
Author: Max Kuhn [aut, cre] , Posit Software, PBC [cph, fnd]
Maintainer: Max Kuhn <max@posit.co>

Diff between tune versions 1.1.2 dated 2023-08-23 and 1.2.0 dated 2024-03-20

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Package prWarp updated to version 1.0.1 with previous version 1.0.0 dated 2020-11-02

Title: Warping Landmark Configurations
Description: Compute bending energies, principal warps, partial warp scores, and the non-affine component of shape variation for 2D landmark configurations, as well as Mardia-Dryden distributions and self-similar distributions of landmarks, as described in Mitteroecker et al. (2020) <doi:10.1093/sysbio/syaa007>. Working examples to decompose shape variation into small-scale and large-scale components, and to decompose the total shape variation into outline and residual shape components are provided. Two landmark datasets are provided, that quantify skull morphology in humans and papionin primates, respectively from Mitteroecker et al. (2020) <doi:10.5061/dryad.j6q573n8s> and Grunstra et al. (2020) <doi:10.5061/dryad.zkh189373>.
Author: Anne Le Maitre [aut, cre] , Silvester Bartsch [aut], Nicole Grunstra [aut], Philipp Mitteroecker [aut]
Maintainer: Anne Le Maitre <anne.le.maitre@univie.ac.at>

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Package tidycensus updated to version 1.6.3 with previous version 1.6.2 dated 2024-03-05

Title: Load US Census Boundary and Attribute Data as 'tidyverse' and 'sf'-Ready Data Frames
Description: An integrated R interface to several United States Census Bureau APIs (<https://www.census.gov/data/developers/data-sets.html>) and the US Census Bureau's geographic boundary files. Allows R users to return Census and ACS data as tidyverse-ready data frames, and optionally returns a list-column with feature geometry for mapping and spatial analysis.
Author: Kyle Walker [aut, cre], Matt Herman [aut], Kris Eberwein [ctb]
Maintainer: Kyle Walker <kyle@walker-data.com>

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Package statsExpressions updated to version 1.5.4 with previous version 1.5.3 dated 2024-01-13

Title: Tidy Dataframes and Expressions with Statistical Details
Description: Utilities for producing dataframes with rich details for the most common types of statistical approaches and tests: parametric, nonparametric, robust, and Bayesian t-test, one-way ANOVA, correlation analyses, contingency table analyses, and meta-analyses. The functions are pipe-friendly and provide a consistent syntax to work with tidy data. These dataframes additionally contain expressions with statistical details, and can be used in graphing packages. This package also forms the statistical processing backend for 'ggstatsplot'. References: Patil (2021) <doi:10.21105/joss.03236>.
Author: Indrajeet Patil [cre, aut, cph]
Maintainer: Indrajeet Patil <patilindrajeet.science@gmail.com>

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Package SqlRender updated to version 1.17.0 with previous version 1.16.1 dated 2023-10-07

Title: Rendering Parameterized SQL and Translation to Dialects
Description: A rendering tool for parameterized SQL that also translates into different SQL dialects. These dialects include 'Microsoft SQL Server', 'Oracle', 'PostgreSql', 'Amazon RedShift', 'Apache Impala', 'IBM Netezza', 'Google BigQuery', 'Microsoft PDW', 'Snowflake', 'Azure Synapse Analytics Dedicated', 'Apache Spark', and 'SQLite'.
Author: Martijn Schuemie [aut, cre], Marc Suchard [aut]
Maintainer: Martijn Schuemie <schuemie@ohdsi.org>

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Package mcmcensemble updated to version 3.1.0 with previous version 3.0.0 dated 2021-04-28

Title: Ensemble Sampler for Affine-Invariant MCMC
Description: Provides ensemble samplers for affine-invariant Monte Carlo Markov Chain, which allow a faster convergence for badly scaled estimation problems. Two samplers are proposed: the 'differential.evolution' sampler from ter Braak and Vrugt (2008) <doi:10.1007/s11222-008-9104-9> and the 'stretch' sampler from Goodman and Weare (2010) <doi:10.2140/camcos.2010.5.65>.
Author: Hugo Gruson [cre, aut, cph] , Sanda Dejanic [aut, cph], Andreas Scheidegger [aut, cph]
Maintainer: Hugo Gruson <hugo.gruson+R@normalesup.org>

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Package glmmTMB updated to version 1.1.9 with previous version 1.1.8 dated 2023-10-07

Title: Generalized Linear Mixed Models using Template Model Builder
Description: Fit linear and generalized linear mixed models with various extensions, including zero-inflation. The models are fitted using maximum likelihood estimation via 'TMB' (Template Model Builder). Random effects are assumed to be Gaussian on the scale of the linear predictor and are integrated out using the Laplace approximation. Gradients are calculated using automatic differentiation.
Author: Mollie Brooks [aut, cre] , Ben Bolker [aut] , Kasper Kristensen [aut], Martin Maechler [aut] , Arni Magnusson [aut] , Maeve McGillycuddy [ctb], Hans Skaug [aut] , Anders Nielsen [aut] , Casper Berg [aut] , Koen van Bentham [aut], Nafis Sadat [ctb] , [...truncated...]
Maintainer: Mollie Brooks <mollieebrooks@gmail.com>

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Package tinytable updated to version 0.2.0 with previous version 0.1.0 dated 2024-03-11

Title: Simple and Configurable Tables in 'HTML', 'LaTeX', 'Markdown', 'Word', 'PNG', 'PDF', and 'Typst' Formats
Description: Create highly customized tables with this simple and dependency-free package. Data frames can be converted to 'HTML', 'LaTeX', 'Markdown', 'Word', 'PNG', 'PDF', or 'Typst' tables. The user interface is minimalist and easy to learn. The syntax concise. 'HTML' tables can be customized using the flexible 'Bootstrap' framework, and 'LaTeX' code with the 'tabularray' package.
Author: Vincent Arel-Bundock [aut, cre]
Maintainer: Vincent Arel-Bundock <vincent.arel-bundock@umontreal.ca>

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Package survey updated to version 4.4-2 with previous version 4.4-1 dated 2024-03-08

Title: Analysis of Complex Survey Samples
Description: Summary statistics, two-sample tests, rank tests, generalised linear models, cumulative link models, Cox models, loglinear models, and general maximum pseudolikelihood estimation for multistage stratified, cluster-sampled, unequally weighted survey samples. Variances by Taylor series linearisation or replicate weights. Post-stratification, calibration, and raking. Two-phase subsampling designs. Graphics. PPS sampling without replacement. Small-area estimation.
Author: Thomas Lumley, Peter Gao, Ben Schneider
Maintainer: "Thomas Lumley" <t.lumley@auckland.ac.nz>

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Package LifemapR updated to version 1.1.1 with previous version 1.0.4 dated 2023-08-24

Title: Data Visualisation on 'Lifemap' Tree
Description: Allow to visualise data on the NCBI phylogenetic tree as presented in Lifemap '<http://lifemap.univ-lyon1.fr/>'. It takes as input a dataframe with at least a "taxid" column containing NCBI format TaxIds and allows to draw multiple layers with different visualisation tools.
Author: Cassandra Bompard [aut], Damien M. de Vienne [aut], Aurelie Siberchicot [ctb, cre]
Maintainer: Aurelie Siberchicot <aurelie.siberchicot@univ-lyon1.fr>

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Package envalysis updated to version 0.7.0 with previous version 0.6.0 dated 2023-09-20

Title: Miscellaneous Functions for Environmental Analyses
Description: Small toolbox for data analyses in environmental chemistry and ecotoxicology. Provides, for example, calibration() to calculate calibration curves and corresponding limits of detection (LODs) and limits of quantification (LOQs) according to German DIN 32645 (2008). texture() makes it easy to estimate soil particle size distributions from hydrometer measurements (ASTM D422-63, 2007).
Author: Zacharias Steinmetz [aut, cre] , Julius Albert [ctb] , Kilian Kenngott [ctb]
Maintainer: Zacharias Steinmetz <z.steinmetz@rptu.de>

Diff between envalysis versions 0.6.0 dated 2023-09-20 and 0.7.0 dated 2024-03-20

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Package TestGardener updated to version 3.3.3 with previous version 3.3.2 dated 2024-01-17

Title: Information Analysis for Test and Rating Scale Data
Description: Develop, evaluate, and score multiple choice examinations, psychological scales, questionnaires, and similar types of data involving sequences of choices among one or more sets of answers. This version of the package should be considered as brand new. Almost all of the functions have been changed, including their argument list. See the file NEWS.Rd in the Inst folder for more information. Using the package does not require any formal statistical knowledge beyond what would be provided by a first course in statistics in a social science department. There the user would encounter the concept of probability and how it is used to model data and make decisions, and would become familiar with basic mathematical and statistical notation. Most of the output is in graphical form.
Author: James Ramsay [aut, cre], Juan Li [ctb], Marie Wiberg [ctb], Joakim Wallmark [ctb], Spencer Graves [ctb]
Maintainer: James Ramsay <james.ramsay@mcgill.ca>

Diff between TestGardener versions 3.3.2 dated 2024-01-17 and 3.3.3 dated 2024-03-20

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Package sgapi updated to version 1.0.1 with previous version 1.0.0 dated 2024-03-18

Title: Aid Querying 'nomis' and 'Office for National Statistics Open Geography' APIs
Description: Facilitates extraction of geospatial data from the 'Office for National Statistics Open Geography' and 'nomis' Application Programming Interfaces (APIs). Simplifies process of querying 'nomis' datasets <https://www.nomisweb.co.uk/> and extracting desired datasets in dataframe format. Extracts area shapefiles at chosen resolution from 'Office for National Statistics Open Geography' <https://geoportal.statistics.gov.uk/>.
Author: Andrew Christy [aut, cre], James Macpherson [aut], Hadyn Jenkins [aut], Crown Copyright [cph]
Maintainer: Andrew Christy <OR_Hub@defra.gov.uk>

Diff between sgapi versions 1.0.0 dated 2024-03-18 and 1.0.1 dated 2024-03-20

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New package plot4fun with initial version 0.1.1
Package: plot4fun
Title: Just Plot for Fun
Version: 0.1.1
Description: Explore the world of R graphics with fun and interesting plot functions! Use make_LED() to create dynamic LED screens, draw interconnected rings with Olympic_rings(), and make festive Chinese couplets with chunlian(). Unleash your creativity and turn data into exciting visuals!
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: magrittr, ggplot2, stats, utils, grDevices, reshape2, graphics, pcutils, ggforce, plot3D, magick, gifski, showtext, sysfonts
Suggests: wordcloud2, geomtextpath
NeedsCompilation: no
Packaged: 2024-03-20 11:25:19 UTC; asa
Author: Chen Peng [aut, cre]
Maintainer: Chen Peng <pengchen2001@zju.edu.cn>
Repository: CRAN
Date/Publication: 2024-03-20 12:30:05 UTC

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Package instantiate updated to version 0.2.2 with previous version 0.2.1 dated 2024-02-06

Title: Pre-Compiled 'CmdStan' Models in R Packages
Description: Similar to 'rstantools' for 'rstan', the 'instantiate' package builds pre-compiled 'CmdStan' models into CRAN-ready statistical modeling R packages. The models compile once during installation, the executables live inside the file systems of their respective packages, and users have the full power and convenience of 'cmdstanr' without any additional compilation after package installation. This approach saves time and helps R package developers migrate from 'rstan' to the more modern 'cmdstanr'. Packages 'rstantools', 'cmdstanr', 'stannis', and 'stanapi' are similar Stan clients with different objectives.
Author: William Michael Landau [aut, cre] , Eli Lilly and Company [cph, fnd]
Maintainer: William Michael Landau <will.landau.oss@gmail.com>

Diff between instantiate versions 0.2.1 dated 2024-02-06 and 0.2.2 dated 2024-03-20

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Package ciw updated to version 0.0.2 with previous version 0.0.1 dated 2024-03-13

Title: Watch the CRAN Incoming Directories
Description: Directory reads and summaries are provided for one or more of the subdirectories of the <https://cran.r-project.org/incoming/> directory, and a compact summary object is returned. The package name is a contraption of 'CRAN Incoming Watcher'.
Author: Dirk Eddelbuettel [aut, cre]
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between ciw versions 0.0.1 dated 2024-03-13 and 0.0.2 dated 2024-03-20

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Package brms updated to version 2.21.0 with previous version 2.20.4 dated 2023-09-25

Title: Bayesian Regression Models using 'Stan'
Description: Fit Bayesian generalized (non-)linear multivariate multilevel models using 'Stan' for full Bayesian inference. A wide range of distributions and link functions are supported, allowing users to fit -- among others -- linear, robust linear, count data, survival, response times, ordinal, zero-inflated, hurdle, and even self-defined mixture models all in a multilevel context. Further modeling options include both theory-driven and data-driven non-linear terms, auto-correlation structures, censoring and truncation, meta-analytic standard errors, and quite a few more. In addition, all parameters of the response distribution can be predicted in order to perform distributional regression. Prior specifications are flexible and explicitly encourage users to apply prior distributions that actually reflect their prior knowledge. Models can easily be evaluated and compared using several methods assessing posterior or prior predictions. References: B├╝rkner (2017) <doi:10.18637/jss.v080.i01>; B [...truncated...]
Author: Paul-Christian Buerkner [aut, cre], Jonah Gabry [ctb], Sebastian Weber [ctb], Andrew Johnson [ctb], Martin Modrak [ctb], Hamada S. Badr [ctb], Frank Weber [ctb], Aki Vehtari [ctb], Mattan S. Ben-Shachar [ctb], Hayden Rabel [ctb], Simon C. Mills [ctb], [...truncated...]
Maintainer: Paul-Christian Buerkner <paul.buerkner@gmail.com>

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Package mexhaz updated to version 2.5 with previous version 2.4 dated 2022-10-31

Title: Mixed Effect Excess Hazard Models
Description: Fit flexible (excess) hazard regression models with the possibility of including non-proportional effects of covariables and of adding a random effect at the cluster level (corresponding to a shared frailty). A detailed description of the package functionalities is provided in Charvat and Belot (2021) <doi: 10.18637/jss.v098.i14>.
Author: Hadrien Charvat, Aurelien Belot
Maintainer: Hadrien Charvat <h.charvat.ef@juntendo.ac.jp>

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Package diseasystore updated to version 0.2.0 with previous version 0.1.1 dated 2024-01-18

Title: Feature Stores for the 'diseasy' Framework
Description: Simple feature stores and tools for creating personalised feature stores. 'diseasystore' powers feature stores which can automatically link and aggregate features to a given stratification level. These feature stores are automatically time-versioned (powered by the 'SCDB' package) and allows you to easily and dynamically compute features as part of your continuous integration.
Author: Rasmus Skytte Randloev [aut, cre] , Marcus Munch Gruenewald [ctb] , Kaare Graesboell [rev] , Kasper Schou Telkamp [rev] , Lasse Engbo Christiansen [rev] , Sofia Myrup Otero [rev], Statens Serum Institut, SSI [cph, fnd]
Maintainer: Rasmus Skytte Randloev <rske@ssi.dk>

Diff between diseasystore versions 0.1.1 dated 2024-01-18 and 0.2.0 dated 2024-03-20

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Package rcpptimer updated to version 1.1.0 with previous version 1.0.0 dated 2024-03-05

Title: 'Rcpp' Tic-Toc Timer with 'OpenMP' Support
Description: Provides 'Rcpp' bindings for 'cpptimer', a simple tic-toc timer class for benchmarking 'C++' code <https://github.com/BerriJ/cpptimer>. It's not just simple, it's blazing fast! This sleek tic-toc timer class supports overlapping timers as well as 'OpenMP' parallelism <https://www.openmp.org/>. It boasts a microsecond-level time resolution. We did not find any overhead of the timer itself at this resolution. Results (with summary statistics) are automatically passed back to 'R' as a data frame.
Author: Jonathan Berrisch [aut, cre]
Maintainer: Jonathan Berrisch <Jonathan@Berrisch.biz>

Diff between rcpptimer versions 1.0.0 dated 2024-03-05 and 1.1.0 dated 2024-03-20

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New package FormulR with initial version 1.0.0
Package: FormulR
Title: Comprehensive Tools for Drug Formulation Analysis and Visualization
Version: 1.0.0
Description: This presents a comprehensive set of tools for the analysis and visualization of drug formulation data. It includes functions for statistical analysis, regression modeling, hypothesis testing, and comparative analysis to assess the impact of formulation parameters on drug release and other critical attributes. Additionally, the package offers a variety of data visualization functions, such as scatterplots, histograms, and boxplots, to facilitate the interpretation of formulation data. With its focus on usability and efficiency, this package aims to streamline the drug formulation process and aid researchers in making informed decisions during formulation design and optimization.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: dplyr, ggplot2
Imports: utils, knitr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-03-19 16:32:45 UTC; USER
Author: Oche Ambrose George [aut, cre]
Maintainer: Oche Ambrose George <ocheab1@gmail.com>
Repository: CRAN
Date/Publication: 2024-03-20 09:50:05 UTC
Suggests: rmarkdown

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Package chronicler updated to version 0.2.2 with previous version 0.2.1 dated 2023-02-03

Title: Add Logging to Functions
Description: Decorate functions to make them return enhanced output. The enhanced output consists in an object of type 'chronicle' containing the result of the function applied to its arguments, as well as a log detailing when the function was run, what were its inputs, what were the errors (if the function failed to run) and other useful information. Tools to handle decorated functions are included, such as a forward pipe operator that makes chaining decorated functions possible.
Author: Bruno Rodrigues [aut, cre, cph]
Maintainer: Bruno Rodrigues <bruno@brodrigues.co>

Diff between chronicler versions 0.2.1 dated 2023-02-03 and 0.2.2 dated 2024-03-20

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New package xega with initial version 0.9.0.0
Package: xega
Title: Extended Evolutionary and Genetic Algorithms
Version: 0.9.0.0
Description: Implementation of a scalable, highly configurable, and e(x)tended architecture for (e)volutionary and (g)enetic (a)lgorithms. Multiple representations (binary, real-coded, permutation, and derivation-tree), a rich collection of genetic operators, as well as an extended processing pipeline are provided for genetic algorithms (Goldberg, D. E. (1989, ISBN:0-201-15767-5)), differential evolution (Price, Kenneth V., Storn, Rainer M. and Lampinen, Jouni A. (2005) <doi:10.1007/3-540-31306-0>), simulated annealing (Aarts, E., and Korst, J. (1989, ISBN:0-471-92146-7)), grammar-based genetic programming (Geyer-Schulz (1997, ISBN:978-3-7908-0830-X)), and grammatical evolution (Ryan, C., O'Neill, M., and Collins, J. J. (2018) <doi:10.1007/978-3-319-78717-6>). All algorithms reuse basic adaptive mechanisms for performance optimization. Sequential or parallel execution (on multi-core machines, local clusters, and high performance computing environments) is available for all algorithms. S [...truncated...]
License: MIT + file LICENSE
URL: <https://github.com/ageyerschulz/xega>
Encoding: UTF-8
Depends: R (>= 3.5.0), parallelly
Imports: xegaSelectGene, xegaBNF, xegaDerivationTrees, xegaGaGene, xegaGpGene, xegaGeGene, xegaDfGene, xegaPermGene, xegaPopulation
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2024-03-19 10:25:55 UTC; dj2333
Author: Andreas Geyer-Schulz [aut, cre]
Maintainer: Andreas Geyer-Schulz <Andreas.Geyer-Schulz@kit.edu>
Repository: CRAN
Date/Publication: 2024-03-20 09:00:02 UTC

More information about xega at CRAN
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Package gamlss updated to version 5.4-22 with previous version 5.4-20 dated 2023-10-04

Title: Generalized Additive Models for Location Scale and Shape
Description: Functions for fitting the Generalized Additive Models for Location Scale and Shape introduced by Rigby and Stasinopoulos (2005), <doi:10.1111/j.1467-9876.2005.00510.x>. The models use a distributional regression approach where all the parameters of the conditional distribution of the response variable are modelled using explanatory variables.
Author: Mikis Stasinopoulos [aut, cre, cph] , Robert Rigby [aut] , Vlasios Voudouris [ctb], Calliope Akantziliotou [ctb], Marco Enea [ctb], Daniil Kiose [ctb] , Achim Zeileis [ctb]
Maintainer: Mikis Stasinopoulos <d.stasinopoulos@gre.ac.uk>

Diff between gamlss versions 5.4-20 dated 2023-10-04 and 5.4-22 dated 2024-03-20

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Package rarestR updated to version 1.0.0 with previous version 0.1.0 dated 2023-10-06

Title: Rarefaction-Based Species Richness Estimator
Description: Calculate rarefaction-based alpha- and beta-diversity. Offer parametric extrapolation to estimate the total expected species in a single community and the total expected shared species between two communities. Visualize the curve-fitting for these estimators.
Author: Peng Zhao [aut, cre] , Yi Zou [aut]
Maintainer: Peng Zhao <pengzhao20@outlook.com>

Diff between rarestR versions 0.1.0 dated 2023-10-06 and 1.0.0 dated 2024-03-20

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Package lattice updated to version 0.22-6 with previous version 0.22-5 dated 2023-10-24

Title: Trellis Graphics for R
Description: A powerful and elegant high-level data visualization system inspired by Trellis graphics, with an emphasis on multivariate data. Lattice is sufficient for typical graphics needs, and is also flexible enough to handle most nonstandard requirements. See ?Lattice for an introduction.
Author: Deepayan Sarkar [aut, cre] , Felix Andrews [ctb], Kevin Wright [ctb] , Neil Klepeis [ctb], Johan Larsson [ctb] , Zhijian Wen [cph] , Paul Murrell [ctb], Stefan Eng [ctb] , Achim Zeileis [ctb] , Alexandre Courtiol [ctb]
Maintainer: Deepayan Sarkar <deepayan.sarkar@r-project.org>

Diff between lattice versions 0.22-5 dated 2023-10-24 and 0.22-6 dated 2024-03-20

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Package embed updated to version 1.1.4 with previous version 1.1.3 dated 2023-10-28

Title: Extra Recipes for Encoding Predictors
Description: Predictors can be converted to one or more numeric representations using a variety of methods. Effect encodings using simple generalized linear models <arXiv:1611.09477> or nonlinear models <arXiv:1604.06737> can be used. There are also functions for dimension reduction and other approaches.
Author: Emil Hvitfeldt [aut, cre] , Max Kuhn [aut] , Posit Software, PBC [cph, fnd]
Maintainer: Emil Hvitfeldt <emil.hvitfeldt@posit.co>

Diff between embed versions 1.1.3 dated 2023-10-28 and 1.1.4 dated 2024-03-20

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Package NormExpression updated to version 0.1.1 with previous version 0.1.0 dated 2018-03-05

Title: Normalize Gene Expression Data using Evaluated Methods
Description: It provides a framework and a fast and simple way for researchers to evaluate methods (particularly some data-driven methods or their own methods) and then select a best one for data normalization in the gene expression analysis, based on the consistency of metrics and the consistency of datasets. Zhenfeng Wu, Weixiang Liu, Xiufeng Jin, Deshui Yu, Hua Wang, Gustavo Glusman, Max Robinson, Lin Liu, Jishou Ruan and Shan Gao (2018) <doi:10.1101/251140>.
Author: Zhenfeng Wu , Shan Gao
Maintainer: Shan Gao <gao_shan@mail.nankai.edu.cn>

Diff between NormExpression versions 0.1.0 dated 2018-03-05 and 0.1.1 dated 2024-03-20

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