Fri, 08 Dec 2023

Package mmrm updated to version 0.3.7 with previous version 0.3.6 dated 2023-11-17

Title: Mixed Models for Repeated Measures
Description: Mixed models for repeated measures (MMRM) are a popular choice for analyzing longitudinal continuous outcomes in randomized clinical trials and beyond; see Cnaan, Laird and Slasor (1997) <doi:10.1002/(SICI)1097-0258(19971030)16:20%3C2349::AID-SIM667%3E3.0.CO;2-E> for a tutorial and Mallinckrodt, Lane, Schnell, Peng and Mancuso (2008) <doi:10.1177/009286150804200402> for a review. This package implements MMRM based on the marginal linear model without random effects using Template Model Builder ('TMB') which enables fast and robust model fitting. Users can specify a variety of covariance matrices, weight observations, fit models with restricted or standard maximum likelihood inference, perform hypothesis testing with Satterthwaite or Kenward-Roger adjustment, and extract least square means estimates by using 'emmeans'.
Author: Daniel Sabanes Bove [aut, cre], Julia Dedic [aut], Doug Kelkhoff [aut], Kevin Kunzmann [aut], Brian Matthew Lang [aut], Liming Li [aut], Christian Stock [aut], Ya Wang [aut], Craig Gower-Page [ctb], Dan James [aut], Jonathan Sidi [aut], Daniel Leibov [...truncated...]
Maintainer: Daniel Sabanes Bove <daniel.sabanes_bove@roche.com>

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Package fastTextR updated to version 2.1.0 with previous version 2.0.1 dated 2022-10-31

Title: An Interface to the 'fastText' Library
Description: An interface to the 'fastText' library <https://github.com/facebookresearch/fastText>. The package can be used for text classification and to learn word vectors. An example how to use 'fastTextR' can be found in the 'README' file.
Author: Florian Schwendinger [aut], Emil Hvitfeldt [aut, cre]
Maintainer: Emil Hvitfeldt <emilhhvitfeldt@gmail.com>

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Package CohortAlgebra updated to version 0.1.0 with previous version 0.0.4 dated 2023-09-13

Title: Use of Interval Algebra to Create New Cohort(s) from Existing Cohorts
Description: This software tool is designed to generate new cohorts utilizing data from previously instantiated cohorts. It employs interval algebra operators such as UNION, INTERSECT, and MINUS to manipulate the data within the instantiated cohorts and create new cohorts.
Author: Gowtham Rao [aut, cre], Observational Health Data Science and Informatics [cph]
Maintainer: Gowtham Rao <rao@ohdsi.org>

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Package bbmle updated to version 1.0.25.1 with previous version 1.0.25 dated 2022-05-11

Title: Tools for General Maximum Likelihood Estimation
Description: Methods and functions for fitting maximum likelihood models in R. This package modifies and extends the 'mle' classes in the 'stats4' package.
Author: Ben Bolker [aut, cre] , R Development Core Team [aut], Iago Gine-Vazquez [ctb]
Maintainer: Ben Bolker <bolker@mcmaster.ca>

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Package ebirdst updated to version 3.2022.1 with previous version 3.2022.0 dated 2023-11-15

Title: Access and Analyze eBird Status and Trends Data Products
Description: Tools for accessing and analyzing eBird Status and Trends Data Products (<https://science.ebird.org/en/status-and-trends>). eBird (<https://ebird.org/home>) is a global database of bird observations collected by member of the public. eBird Status and Trends uses these data to model global bird distributions, abundances, and population trends at a high spatial and temporal resolution.
Author: Matthew Strimas-Mackey [aut, cre] , Shawn Ligocki [aut], Tom Auer [aut] , Daniel Fink [aut] , Cornell Lab of Ornithology [cph]
Maintainer: Matthew Strimas-Mackey <mes335@cornell.edu>

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Package BGVAR updated to version 2.5.3 with previous version 2.5.2 dated 2022-10-26

Title: Bayesian Global Vector Autoregressions
Description: Estimation of Bayesian Global Vector Autoregressions (BGVAR) with different prior setups and the possibility to introduce stochastic volatility. Built-in priors include the Minnesota, the stochastic search variable selection and Normal-Gamma (NG) prior. For a reference see also Crespo Cuaresma, J., Feldkircher, M. and F. Huber (2016) "Forecasting with Global Vector Autoregressive Models: a Bayesian Approach", Journal of Applied Econometrics, Vol. 31(7), pp. 1371-1391 <doi:10.1002/jae.2504>. Post-processing functions allow for doing predictions, structurally identify the model with short-run or sign-restrictions and compute impulse response functions, historical decompositions and forecast error variance decompositions. Plotting functions are also available. The package has a companion paper: Boeck, M., Feldkircher, M. and F. Huber (2022) "BGVAR: Bayesian Global Vector Autoregressions with Shrinkage Priors in R", Journal of Statistical Software, Vol. 104(9), pp. 1-28 <doi:10.18 [...truncated...]
Author: Maximilian Boeck [aut, cre] , Martin Feldkircher [aut] , Florian Huber [aut] , Darjus Hosszejni [ctb]
Maintainer: Maximilian Boeck <maximilian.boeck@unibocconi.it>

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Package mlr3pipelines updated to version 0.5.0-2 with previous version 0.5.0 dated 2023-05-22

Title: Preprocessing Operators and Pipelines for 'mlr3'
Description: Dataflow programming toolkit that enriches 'mlr3' with a diverse set of pipelining operators ('PipeOps') that can be composed into graphs. Operations exist for data preprocessing, model fitting, and ensemble learning. Graphs can themselves be treated as 'mlr3' 'Learners' and can therefore be resampled, benchmarked, and tuned.
Author: Martin Binder [aut, cre], Florian Pfisterer [aut] , Lennart Schneider [aut] , Bernd Bischl [aut] , Michel Lang [aut] , Sebastian Fischer [ctb] , Susanne Dandl [aut]
Maintainer: Martin Binder <mlr.developer@mb706.com>

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Package mmap updated to version 0.6-22 with previous version 0.6-21 dated 2023-01-29

Title: Map Pages of Memory
Description: R interface to POSIX mmap and Window's MapViewOfFile.
Author: Jeffrey A. Ryan
Maintainer: Jeffrey A. Ryan <jeff.a.ryan@gmail.com>

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Package ldt updated to version 0.5.1 with previous version 0.5.0 dated 2023-11-07

Title: Automated Uncertainty Analysis
Description: Methods and tools for model selection and multi-model inference (Burnham and Anderson (2002) <doi:10.1007/b97636>, among others). 'SUR' (for parameter estimation), 'logit'/'probit' (for binary classification), and 'VARMA' (for time-series forecasting) are implemented. Evaluations are both in-sample and out-of-sample. It is designed to be efficient in terms of CPU usage and memory consumption.
Author: Ramin Mojab [aut, cre], Stephen Becker [cph] by Ciyou Zhu . L-BFGS-B Version 3.0 is an algorithmic update from 2011, with coding changes by J. L. Morales)
Maintainer: Ramin Mojab <rmojab63@gmail.com>

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Package handwriter updated to version 2.0.3 with previous version 2.0.2 dated 2023-10-13

Title: Handwriting Analysis in R
Description: Perform statistical writership analysis of scanned handwritten documents. Webpage provided at: <https://csafe-isu.github.io/handwriter/index.html>.
Author: Iowa State University of Science and Technology on behalf of its Center for Statistics and Applications in Forensic Evidence [aut, cph, fnd], Nick Berry [aut], Stephanie Reinders [aut, cre], James Taylor [aut], Felix Baez-Santiago [ctb], Jon Gonzalez [...truncated...]
Maintainer: Stephanie Reinders <srein@iastate.edu>

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Package fourierin updated to version 0.2.5 with previous version 0.2.4 dated 2019-04-07

Title: Computes Numeric Fourier Integrals
Description: Computes Fourier integrals of functions of one and two variables using the Fast Fourier transform. The Fourier transforms must be evaluated on a regular grid for fast evaluation.
Author: Guillermo Basulto-Elias
Maintainer: Guillermo Basulto-Elias <guillermobasulto@gmail.com>

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Package empichar updated to version 1.0.1 with previous version 1.0.0 dated 2019-05-08

Title: Evaluates the Empirical Characteristic Function for Multivariate Samples
Description: Evaluates the empirical characteristic function of univariate and multivariate samples. This package uses 'RcppArmadillo' for fast evaluation. It is also possible to export the code to be used in other packages at 'C++' level.
Author: Guillermo Basulto-Elias [aut, cre]
Maintainer: Guillermo Basulto-Elias <guillermobasulto@gmail.com>

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More information about empichar at CRAN
Permanent link

Package httk updated to version 2.3.0 with previous version 2.2.2 dated 2023-02-20

Title: High-Throughput Toxicokinetics
Description: Pre-made models that can be rapidly tailored to various chemicals and species using chemical-specific in vitro data and physiological information. These tools allow incorporation of chemical toxicokinetics ("TK") and in vitro-in vivo extrapolation ("IVIVE") into bioinformatics, as described by Pearce et al. (2017) (<doi:10.18637/jss.v079.i04>). Chemical-specific in vitro data characterizing toxicokinetics have been obtained from relatively high-throughput experiments. The chemical-independent ("generic") physiologically-based ("PBTK") and empirical (for example, one compartment) "TK" models included here can be parameterized with in vitro data or in silico predictions which are provided for thousands of chemicals, multiple exposure routes, and various species. High throughput toxicokinetics ("HTTK") is the combination of in vitro data and generic models. We establish the expected accuracy of HTTK for chemicals without in vivo data through statistical evaluation of HTTK predicti [...truncated...]
Author: John Wambaugh [aut, cre] , Sarah Davidson-Fritz [aut] , Robert Pearce [aut] , Caroline Ring [aut] , Greg Honda [aut] , Mark Sfeir [aut], Matt Linakis [aut] , Dustin Kapraun [aut] , Nathan Pollesch [ctb] , Miyuki Breen [ctb] , Shannon Bell [ctb] , Xia [...truncated...]
Maintainer: John Wambaugh <wambaugh.john@epa.gov>

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Package blatent updated to version 0.1.2 with previous version 0.1.1 dated 2020-12-15

Title: Bayesian Latent Variable Models
Description: Estimation of latent variable models using Bayesian methods. Currently estimates the loglinear cognitive diagnosis model of Henson, Templin, and Willse (2009) <doi:10.1007/s11336-008-9089-5>.
Author: Jonathan Templin [aut, cre]
Maintainer: Jonathan Templin <jonathan-templin@uiowa.edu>

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Package admisc updated to version 0.34 with previous version 0.33 dated 2023-06-30

Title: Adrian Dusa's Miscellaneous
Description: Contains functions used across packages 'DDIwR', 'QCA' and 'venn'. Interprets and translates, factorizes and negates SOP - Sum of Products expressions, for both binary and multi-value crisp sets, and extracts information (set names, set values) from those expressions. Other functions perform various other checks if possibly numeric (even if all numbers reside in a character vector) and coerce to numeric, or check if the numbers are whole. It also offers, among many others, a highly versatile recoding routine and some more flexible alternatives to the base functions 'with()' and 'within()'. SOP simplification functions in this package use related minimization from package 'QCA', which is recommended to be installed despite not being listed in the Imports field, due to circular dependency issues.
Author: Adrian Dusa [aut, cre, cph]
Maintainer: Adrian Dusa <dusa.adrian@unibuc.ro>

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Package pfr updated to version 1.0.1 with previous version 1.0.0 dated 2023-08-15

Title: Interface to the 'C++' Library 'Pf'
Description: Builds and runs 'c++' code for classes that encapsulate state space model, particle filtering algorithm pairs. Algorithms include the Bootstrap Filter from Gordon et al. (1993) <doi:10.1049/ip-f-2.1993.0015>, the generic SISR filter, the Auxiliary Particle Filter from Pitt et al (1999) <doi:10.2307/2670179>, and a variety of Rao-Blackwellized particle filters inspired by Andrieu et al. (2002) <doi:10.1111/1467-9868.00363>. For more details on the 'c++' library 'pf', see Brown (2020) <doi:10.21105/joss.02599>.
Author: Taylor Brown [aut, cre]
Maintainer: Taylor Brown <trb5me@virginia.edu>

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Package GABB updated to version 0.3.7 with previous version 0.3.5 dated 2023-11-27

Title: Facilitation of Data Preparation and Plotting Procedures for RDA and PCA Analyses
Description: Help to the occasional R user for synthesis and enhanced graphical visualization of redundancy analysis (RDA) and principal component analysis (PCA) methods and objects. Inputs are : data frame, RDA (package 'vegan') and PCA (package 'FactoMineR') objects. Outputs are : synthesized results of RDA, displayed in console and saved in tables ; displayed and saved objects of PCA graphic visualization of individuals and variables projections with multiple graphic parameters.
Author: Gregoire Bianchetti [aut, cre]
Maintainer: Gregoire Bianchetti <auguste.blam@gmail.com>

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Package tern updated to version 0.9.3 with previous version 0.9.0 dated 2023-09-01

Title: Create Common TLGs Used in Clinical Trials
Description: Table, Listings, and Graphs (TLG) library for common outputs used in clinical trials.
Author: Joe Zhu [aut, cre], Daniel Sabanes Bove [aut], Jana Stoilova [aut], Heng Wang [aut], Francois Collin [aut], Adrian Waddell [aut], Pawel Rucki [aut], Chendi Liao [aut], Jennifer Li [aut], F. Hoffmann-La Roche AG [cph, fnd]
Maintainer: Joe Zhu <joe.zhu@roche.com>

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Package svglite updated to version 2.1.3 with previous version 2.1.2 dated 2023-10-11

Title: An 'SVG' Graphics Device
Description: A graphics device for R that produces 'Scalable Vector Graphics'. 'svglite' is a fork of the older 'RSvgDevice' package.
Author: Hadley Wickham [aut], Lionel Henry [aut], Thomas Lin Pedersen [cre, aut] , T Jake Luciani [aut], Matthieu Decorde [aut], Vaudor Lise [aut], Tony Plate [ctb] , David Gohel [ctb] , Yixuan Qiu [ctb] , Hakon Malmedal [ctb] , Posit, PBC [cph, fnd]
Maintainer: Thomas Lin Pedersen <thomas.pedersen@posit.co>

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Package spacyr updated to version 1.3.0 with previous version 1.2.1 dated 2020-03-04

Title: Wrapper to the 'spaCy' 'NLP' Library
Description: An R wrapper to the 'Python' 'spaCy' 'NLP' library, from <https://spacy.io>.
Author: Kenneth Benoit [cre, aut, cph] , Akitaka Matsuo [aut] , Johannes Gruber [ctb] , European Research Council [fnd]
Maintainer: Kenneth Benoit <kbenoit@lse.ac.uk>

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Package dataset updated to version 0.2.7 with previous version 0.2.1 dated 2023-03-18

Title: Create Data Frames that are Easier to Exchange and Reuse
Description: The aim of the 'dataset' package is to make tidy datasets easier to release, exchange and reuse. It organizes and formats data frame 'R' objects into well-referenced, well-described, interoperable datasets into release and reuse ready form. A subjective interpretation of the W3C DataSet recommendation and the datacube model <https://www.w3.org/TR/vocab-data-cube/>, which is also used in the global Statistical Data and Metadata eXchange standards, the application of the connected Dublin Core <https://www.dublincore.org/specifications/dublin-core/dcmi-terms/> and DataCite <https://support.datacite.org/docs/datacite-metadata-schema-44/> standards preferred by European open science repositories to improve the findability, accessibility, interoperability and reusability of the datasets.
Author: Daniel Antal [aut, cre] , Marcelo Perlin [rev]
Maintainer: Daniel Antal <daniel.antal@dataobservatory.eu>

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Package stan4bart updated to version 0.0-7 with previous version 0.0-6 dated 2023-02-03

Title: Bayesian Additive Regression Trees with Stan-Sampled Parametric Extensions
Description: Fits semiparametric linear and multilevel models with non-parametric additive Bayesian additive regression tree (BART; Chipman, George, and McCulloch (2010) <doi:10.1214/09-AOAS285>) components and Stan (Stan Development Team (2021) <https://mc-stan.org/>) sampled parametric ones. Multilevel models can be expressed using 'lme4' syntax (Bates, Maechler, Bolker, and Walker (2015) <doi:10.18637/jss.v067.i01>).
Author: Vincent Dorie [aut, cre] , Ben Goodrich [ctb] , Jonah Gabry [ctb] , Imad Ali [ctb] , Sam Brilleman [ctb] , Paul-Christian Burkner [ctb] , Joshua Pritikin [ctb] , Andrew Gelman [ctb] , Bob Carpenter [ctb] , Matt Hoffman [ctb] , Daniel Lee [ctb] , Mich [...truncated...]
Maintainer: Vincent Dorie <vdorie@gmail.com>

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Package seqinr updated to version 4.2-36 with previous version 4.2-30 dated 2023-04-05

Title: Biological Sequences Retrieval and Analysis
Description: Exploratory data analysis and data visualization for biological sequence (DNA and protein) data. Seqinr includes utilities for sequence data management under the ACNUC system described in Gouy, M. et al. (1984) Nucleic Acids Res. 12:121-127 <doi:10.1093/nar/12.1Part1.121>.
Author: Delphine Charif [aut], Olivier Clerc [ctb], Carolin Frank [ctb], Jean R. Lobry [aut, cph], Anamaria Necsulea [ctb], Leonor Palmeira [ctb], Simon Penel [cre], Guy Perriere [ctb]
Maintainer: Simon Penel <simon.penel@univ-lyon1.fr>

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Package r2sundials updated to version 6.5.0-4 with previous version 6.5.0-3 dated 2023-03-24

Title: Wrapper for 'SUNDIALS' Solving ODE and Sensitivity Problem
Description: Wrapper for widely used 'SUNDIALS' software (SUite of Nonlinear and DIfferential/ALgebraic Equation Solvers) and more precisely to its 'CVODES' solver. It is aiming to solve ordinary differential equations (ODE) and optionally pending forward sensitivity problem. The wrapper is made 'R' friendly by allowing to pass custom parameters to user's callback functions. Such functions can be both written in 'R' and in 'C++' ('RcppArmadillo' flavor). In case of 'C++', performance is greatly improved so this option is highly advisable when performance matters. If provided, Jacobian matrix can be calculated either in dense or sparse format. In the latter case 'rmumps' package is used to solve corresponding linear systems. Root finding and pending event management are optional and can be specified as 'R' or 'C++' functions too. This makes them a very flexible tool for controlling the ODE system during the time course simulation. 'SUNDIALS' library was published in Hindmarsh et al. (2005) <doi:1 [...truncated...]
Author: Serguei Sokol [cre, aut], Carol S. Woodward [ctb], Daniel R. Reynolds [ctb], Alan C. Hindmarsh [ctb], David J. Gardner [ctb], Cody J. Balos [ctb], Radu Serban [ctb], Scott D. Cohen [ctb], Peter N. Brown [ctb], George Byrne [ctb], Allan G. Taylor [ctb [...truncated...]
Maintainer: Serguei Sokol <sokol@insa-toulouse.fr>

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Package psbcSpeedUp updated to version 2.0.5 with previous version 2.0.4 dated 2023-10-12

Title: Penalized Semiparametric Bayesian Cox Models
Description: Algorithms to speed up the Bayesian Lasso Cox model (Lee et al., Int J Biostat, 2011 <doi:10.2202/1557-4679.1301>) and the Bayesian Lasso Cox with mandatory variables (Zucknick et al. Biometrical J, 2015 <doi:10.1002/bimj.201400160>).
Author: Zhi Zhao [aut, cre], Manuela Zucknick [aut], Maral Saadati [aut], Axel Benner [aut]
Maintainer: Zhi Zhao <zhi.zhao@medisin.uio.no>

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Package oeli updated to version 0.3.1 with previous version 0.3.0 dated 2023-12-02

Title: My Utilities for Developing Data Science Software
Description: Some general utilities (helper functions) that I and maybe others find useful when developing data science software. Functionality includes argument validation, density calculation, sampling, matrix printing, user interaction, storage helpers and more. The vignettes illustrate use cases.
Author: Lennart Oelschlaeger [aut, cre]
Maintainer: Lennart Oelschlaeger <oelschlaeger.lennart@gmail.com>

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Package mrgsim.sa updated to version 0.2.0 with previous version 0.1.0 dated 2020-11-30

Title: Sensitivity Analysis with 'mrgsolve'
Description: Perform sensitivity analysis on ordinary differential equation based models, including ad-hoc graphical analyses based on structured sequences of parameters as well as local sensitivity analysis. Functions are provided for creating inputs, simulating scenarios and plotting outputs.
Author: Kyle Baron [aut, cre]
Maintainer: Kyle Baron <kylebtwin@imap.cc>

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Package ichimoku updated to version 1.4.11 with previous version 1.4.10 dated 2023-10-28

Title: Visualization and Tools for Ichimoku Kinko Hyo Strategies
Description: An implementation of 'Ichimoku Kinko Hyo', also commonly known as 'cloud charts'. Static and interactive visualizations with tools for creating, backtesting and development of quantitative 'ichimoku' strategies. As described in Sasaki (1996, ISBN:4925152009), the technique is a refinement on candlestick charting, originating from Japan and now in widespread use in technical analysis worldwide. Translating as 'one-glance equilibrium chart', it allows the price action and market structure of financial securities to be determined 'at-a-glance'. Incorporates an interface with the OANDA fxTrade API <https://developer.oanda.com/> for retrieving historical and live streaming price data for major currencies, metals, commodities, government bonds and stock indices.
Author: Charlie Gao [aut, cre] , Hibiki AI Limited [cph]
Maintainer: Charlie Gao <charlie.gao@shikokuchuo.net>

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Package HEtools updated to version 1.0.0 with previous version 0.2.0 dated 2023-11-11

Title: Homomorphic Encryption Polynomials
Description: Homomorphic encryption (Brakerski and Vaikuntanathan (2014) <doi:10.1137/120868669>) using Ring Learning with Errors (Lyubashevsky et al. (2012) <https://eprint.iacr.org/2012/230>) is a form of Learning with Errors (Regev (2005) <doi:10.1145/1060590.1060603>) using polynomial rings over finite fields. Functions to generate the required polynomials (using 'polynom'), with various distributions of coefficients are provided. Additionally, functions to generate and take coefficient modulo are provided.
Author: Bastiaan Quast [aut, cre]
Maintainer: Bastiaan Quast <bquast@gmail.com>

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Package bayescount updated to version 0.9.99-9 with previous version 0.9.99-8 dated 2022-05-07

Title: Power Calculations and Bayesian Analysis of Count Distributions and FECRT Data using MCMC
Description: A set of functions to allow analysis of count data (such as faecal egg count data) using Bayesian MCMC methods. Returns information on the possible values for mean count, coefficient of variation and zero inflation (true prevalence) present in the data. A complete faecal egg count reduction test (FECRT) model is implemented, which returns inference on the true efficacy of the drug from the pre- and post-treatment data provided, using non-parametric bootstrapping as well as using Bayesian MCMC. Functions to perform power analyses for faecal egg counts (including FECRT) are also provided.
Author: Matthew Denwood [aut, cre]
Maintainer: Matthew Denwood <md@sund.ku.dk>

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Package mizer updated to version 2.5.0 with previous version 2.4.1 dated 2023-04-26

Title: Dynamic Multi-Species Size Spectrum Modelling
Description: A set of classes and methods to set up and run multi-species, trait based and community size spectrum ecological models, focused on the marine environment.
Author: Gustav Delius [cre, aut, cph] , Finlay Scott [aut, cph], Julia Blanchard [aut, cph] , Ken Andersen [aut, cph] , Richard Southwell [ctb, cph]
Maintainer: Gustav Delius <gustav.delius@york.ac.uk>

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 mizer-2.5.0/mizer/NAMESPACE                                |    8 
 mizer-2.5.0/mizer/NEWS.md                                  |   59 ++
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 mizer-2.5.0/mizer/R/age_mat.R                              |    2 
 mizer-2.5.0/mizer/R/manipulate_species.R                   |   26 -
 mizer-2.5.0/mizer/R/newMultispeciesParams.R                |   22 
 mizer-2.5.0/mizer/R/project.R                              |   15 
 mizer-2.5.0/mizer/R/project_methods.R                      |    4 
 mizer-2.5.0/mizer/R/setBevertonHolt.R                      |    8 
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 mizer-2.5.0/mizer/R/setFishing.R                           |    6 
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 mizer-2.5.0/mizer/R/setReproduction.R                      |    1 
 mizer-2.5.0/mizer/R/setSearchVolume.R                      |    3 
 mizer-2.5.0/mizer/R/species_params.R                       |  311 +++++++++----
 mizer-2.5.0/mizer/R/upgrade.R                              |   20 
 mizer-2.5.0/mizer/README.md                                |    2 
 mizer-2.5.0/mizer/data/NS_params.rda                       |binary
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 mizer-2.5.0/mizer/man/setMaxIntakeRate.Rd                  |    1 
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 mizer-2.5.0/mizer/man/setParams.Rd                         |   11 
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 mizer-2.5.0/mizer/man/setSearchVolume.Rd                   |    1 
 mizer-2.5.0/mizer/man/species_params.Rd                    |   73 +--
 mizer-2.5.0/mizer/man/validSpeciesParams.Rd                |   13 
 mizer-2.5.0/mizer/tests/testthat/test-manipulate_species.R |    2 
 mizer-2.5.0/mizer/tests/testthat/test-project_methods.R    |    8 
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 mizer-2.5.0/mizer/tests/testthat/test-setFishing.R         |    2 
 mizer-2.5.0/mizer/tests/testthat/test-setPredKernel.R      |    9 
 mizer-2.5.0/mizer/tests/testthat/test-species_params.R     |   70 ++
 49 files changed, 633 insertions(+), 245 deletions(-)

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Package lpridge updated to version 1.1-0 with previous version 1.0-8 dated 2018-06-12

Title: Local Polynomial (Ridge) Regression
Description: Local Polynomial Regression with Ridging.
Author: Burkhardt Seifert <seifert@ifspm.unizh.ch> ; Packaged for R by Martin Maechler
Maintainer: Martin Maechler <maechler@stat.math.ethz.ch>

Diff between lpridge versions 1.0-8 dated 2018-06-12 and 1.1-0 dated 2023-12-08

 ChangeLog      |   25 +++++++++++++++++++++++++
 DESCRIPTION    |   13 +++++++++----
 MD5            |    8 ++++----
 man/lpepa.Rd   |   16 +++++++++-------
 man/lpridge.Rd |    6 +++---
 5 files changed, 50 insertions(+), 18 deletions(-)

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New package rgeoboundaries with initial version 1.2.9
Package: rgeoboundaries
Title: A Client to 'geoBoundaries', a Political Administrative Boundaries Dataset
Version: 1.2.9
Description: Client the access data from the 'geoBoundaries' API <https://www.geoboundaries.org/api/current/> who provides country political administrative boundaries dataset.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/wmgeolab/rgeoboundaries
BugReports: https://github.com/wmgeolab/rgeoboundaries/issues
Depends: R (>= 4.1)
Imports: crul (>= 1.4.0), jsonlite, sf (>= 1.0.0), hoardr, glue, memoise, countrycode (>= 1.2.0), lifecycle
Suggests: roxygen2, knitr, rmarkdown, testthat, covr,
NeedsCompilation: no
Packaged: 2023-12-07 19:20:16 UTC; rohith
Author: Ahmadou Dicko [aut, cre], Andy South [ctb], Daniel Runfola [ctb], Rohith Reddy Mandala [ctb]
Maintainer: Ahmadou Dicko <team@geoboundaries.org>
Repository: CRAN
Date/Publication: 2023-12-08 11:20:03 UTC

More information about rgeoboundaries at CRAN
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New package RcppCGAL with initial version 5.6.0
Package: RcppCGAL
Title: 'Rcpp' Integration for 'CGAL'
Version: 5.6.0
Date: 2023-11-13
Author: Eric Dunipace [aut, cre]
Maintainer: Eric Dunipace <edunipace@mail.harvard.edu>
Description: Creates a header only package to link to the 'CGAL' (Computational Geometry Algorithms Library) header files in 'Rcpp'. There are a variety of potential uses for the software such as Hilbert sorting, K-D Tree nearest neighbors, and convex hull algorithms. For more information about how to use the header files, see the 'CGAL' documentation at <https://www.cgal.org>. Currently downloads the 'CGAL' version 5.6 stable release.
License: GPL-3
Imports: Rcpp
Suggests: knitr, rmarkdown, spelling, testthat (>= 3.0.0)
BugReports: https://github.com/ericdunipace/RcppCGAL/issues
NeedsCompilation: no
Encoding: UTF-8
VignetteBuilder: knitr
Biarch: TRUE
Language: en-US
URL: https://github.com/ericdunipace/RcppCGAL
Packaged: 2023-12-07 23:00:05 UTC; eifer
Repository: CRAN
Date/Publication: 2023-12-08 11:20:24 UTC

More information about RcppCGAL at CRAN
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New package PACVr with initial version 1.0.5
Package: PACVr
Version: 1.0.5
Date: 2023-12-07
Title: Plastome Assembly Coverage Visualization
Maintainer: Michael Gruenstaeudl <m_gruenstaeudl@fhsu.edu>
Depends: R (>= 3.3.0)
Imports: Biostrings (>= 2.48.0), dplyr, GenomicAlignments (>= 1.18.1), GenomicRanges, IRanges, logger, read.gb, RCircos (>= 1.2.0)
Description: Visualizes the coverage depth of a complete plastid genome as well as the equality of its inverted repeat regions in relation to the circular, quadripartite genome structure and the location of individual genes. For more information, please see Gruenstaeudl and Jenke (2020) <doi:10.1186/s12859-020-3475-0>.
License: BSD 3-clause License + file LICENSE
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2023-12-08 01:15:50 UTC; mi
Author: Gregory Smith [ctb], Nils Jenke [ctb], Michael Gruenstaeudl [aut, cre]
Repository: CRAN
Date/Publication: 2023-12-08 11:20:28 UTC

More information about PACVr at CRAN
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New package mergen with initial version 0.1.0
Package: mergen
Title: AI-Driven Code Generation, Explanation and Execution for Data Analysis
Version: 0.1.0
Description: Employing artificial intelligence to convert data analysis questions into executable code, explanations, and algorithms. The self-correction feature ensures the generated code is optimized for performance and accuracy. 'mergen' features a user-friendly chat interface, enabling users to interact with the AI agent and extract valuable insights from their data effortlessly.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.5.0),
Imports: openai, rmarkdown, BiocManager, assertthat (>= 0.2.1), httr, jsonlite
Suggests: knitr, readxl, data.table (>= 1.9.6), testthat (>= 3.0.0), purrr (>= 0.3.4),
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2023-12-07 23:03:43 UTC; aakalin
Author: Altuna Akalin [aut, cre] , Jacqueline Anne Jansen [aut]
Maintainer: Altuna Akalin <aakalin@gmail.com>
Repository: CRAN
Date/Publication: 2023-12-08 11:20:05 UTC

More information about mergen at CRAN
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New package MadanTextNetwork with initial version 0.1.0
Package: MadanTextNetwork
Title: Persian Text Mining Tool for Co-Occurrence Network
Version: 0.1.0
Description: Provides an extension to 'MadanText' for creating and analyzing co-occurrence networks in Persian text data. This package mainly makes use of the 'PersianStemmer' (Safshekan, R., et al. (2019). <https://CRAN.R-project.org/package=PersianStemmer>), 'udpipe' (Wijffels, J., et al. (2023). <https://CRAN.R-project.org/package=udpipe>), and 'shiny' (Chang, W., et al. (2023). <https://CRAN.R-project.org/package=shiny>) packages.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: xlsx, glue, lattice, stopwords,textmineR, tidytext, tidyr, udpipe, PersianStemmer, shiny (>= 1.8.0), shinythemes, tm, dplyr, hwordcloud, stringr, stringi, topicmodels, igraph, ngram, visNetwork
NeedsCompilation: no
Packaged: 2023-12-08 03:48:05 UTC; trial
Author: Kido Ishikawa [aut, cre], Hasan Khosravi [aut]
Maintainer: Kido Ishikawa <kido.ishikawa6@gmail.com>
Repository: CRAN
Date/Publication: 2023-12-08 11:30:05 UTC

More information about MadanTextNetwork at CRAN
Permanent link

Package lightgbm updated to version 4.2.0 with previous version 3.3.5 dated 2023-01-16

Title: Light Gradient Boosting Machine
Description: Tree based algorithms can be improved by introducing boosting frameworks. 'LightGBM' is one such framework, based on Ke, Guolin et al. (2017) <https://papers.nips.cc/paper/6907-lightgbm-a-highly-efficient-gradient-boosting-decision>. This package offers an R interface to work with it. It is designed to be distributed and efficient with the following advantages: 1. Faster training speed and higher efficiency. 2. Lower memory usage. 3. Better accuracy. 4. Parallel learning supported. 5. Capable of handling large-scale data. In recognition of these advantages, 'LightGBM' has been widely-used in many winning solutions of machine learning competitions. Comparison experiments on public datasets suggest that 'LightGBM' can outperform existing boosting frameworks on both efficiency and accuracy, with significantly lower memory consumption. In addition, parallel experiments suggest that in certain circumstances, 'LightGBM' can achieve a linear speed-up in training time by using multiple m [...truncated...]
Author: Yu Shi [aut], Guolin Ke [aut], Damien Soukhavong [aut], James Lamb [aut, cre], Qi Meng [aut], Thomas Finley [aut], Taifeng Wang [aut], Wei Chen [aut], Weidong Ma [aut], Qiwei Ye [aut], Tie-Yan Liu [aut], Nikita Titov [aut], Yachen Yan [ctb], Microsof [...truncated...]
Maintainer: James Lamb <jaylamb20@gmail.com>

Diff between lightgbm versions 3.3.5 dated 2023-01-16 and 4.2.0 dated 2023-12-08

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 lightgbm-4.2.0/lightgbm/DESCRIPTION                                                             |   45 
 lightgbm-4.2.0/lightgbm/MD5                                                                     |  736 -
 lightgbm-4.2.0/lightgbm/NAMESPACE                                                               |   21 
 lightgbm-4.2.0/lightgbm/R/aliases.R                                                             |  172 
 lightgbm-4.2.0/lightgbm/R/callback.R                                                            |  133 
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 lightgbm-4.2.0/lightgbm/R/lgb.Dataset.R                                                         |  432 
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 lightgbm-4.2.0/lightgbm/R/lgb.cv.R                                                              |  155 
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 lightgbm-4.2.0/lightgbm/R/lgb.importance.R                                                      |    5 
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 lightgbm-4.2.0/lightgbm/R/lgb.model.dt.tree.R                                                   |   10 
 lightgbm-4.2.0/lightgbm/R/lgb.plot.importance.R                                                 |    5 
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 lightgbm-4.2.0/lightgbm/R/lgb.train.R                                                           |  110 
 lightgbm-4.2.0/lightgbm/R/lightgbm.R                                                            |  145 
 lightgbm-4.2.0/lightgbm/R/multithreading.R                                                      |only
 lightgbm-4.2.0/lightgbm/R/readRDS.lgb.Booster.R                                                 |   36 
 lightgbm-4.2.0/lightgbm/R/saveRDS.lgb.Booster.R                                                 |   57 
 lightgbm-4.2.0/lightgbm/R/utils.R                                                               |  151 
 lightgbm-4.2.0/lightgbm/README.md                                                               |  102 
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 lightgbm-4.2.0/lightgbm/configure                                                               |  738 -
 lightgbm-4.2.0/lightgbm/configure.ac                                                            |   12 
 lightgbm-4.2.0/lightgbm/configure.win                                                           |   38 
 lightgbm-4.2.0/lightgbm/demo/basic_walkthrough.R                                                |    1 
 lightgbm-4.2.0/lightgbm/demo/boost_from_prediction.R                                            |    5 
 lightgbm-4.2.0/lightgbm/demo/early_stopping.R                                                   |    1 
 lightgbm-4.2.0/lightgbm/demo/leaf_stability.R                                                   |    6 
 lightgbm-4.2.0/lightgbm/demo/multiclass.R                                                       |   14 
 lightgbm-4.2.0/lightgbm/demo/multiclass_custom_objective.R                                      |    4 
 lightgbm-4.2.0/lightgbm/demo/weight_param.R                                                     |   25 
 lightgbm-4.2.0/lightgbm/inst                                                                    |only
 lightgbm-4.2.0/lightgbm/man/dim.Rd                                                              |    6 
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 lightgbm-4.2.0/lightgbm/man/get_field.Rd                                                        |    2 
 lightgbm-4.2.0/lightgbm/man/lgb.Dataset.Rd                                                      |   12 
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 lightgbm-4.2.0/lightgbm/man/lgb.Dataset.create.valid.Rd                                         |   13 
 lightgbm-4.2.0/lightgbm/man/lgb.Dataset.save.Rd                                                 |    2 
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 lightgbm-4.2.0/lightgbm/man/lgb.importance.Rd                                                   |    3 
 lightgbm-4.2.0/lightgbm/man/lgb.interprete.Rd                                                   |    3 
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 lightgbm-4.2.0/lightgbm/man/lgb.save.Rd                                                         |    3 
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 lightgbm-4.2.0/lightgbm/man/lightgbm.Rd                                                         |   78 
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 lightgbm-4.2.0/lightgbm/man/set_field.Rd                                                        |    2 
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 lightgbm-4.2.0/lightgbm/src/Makevars.in                                                         |    6 
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 lightgbm-4.2.0/lightgbm/src/boosting/goss.hpp                                                   |  168 
 lightgbm-4.2.0/lightgbm/src/boosting/rf.hpp                                                     |   45 
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 lightgbm-4.2.0/lightgbm/src/include/Eigen/Cholesky                                              |    1 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/Core                                                  |   19 
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 lightgbm-4.2.0/lightgbm/src/include/Eigen/Geometry                                              |    5 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/Householder                                           |    1 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/Jacobi                                                |    1 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/LU                                                    |    7 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/QR                                                    |    1 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/SVD                                                   |    1 
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 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Cholesky/LLT.h                                    |    6 
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 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/BandMatrix.h                                 |   32 
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 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/CwiseNullaryOp.h                             |   89 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/CwiseUnaryOp.h                               |   12 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/CwiseUnaryView.h                             |   20 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/DenseBase.h                                  |   82 
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 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Dot.h                                        |    4 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/EigenBase.h                                  |   16 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/ForceAlignedAccess.h                         |   12 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/GeneralProduct.h                             |    6 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/GenericPacketMath.h                          |  629 -
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/GlobalFunctions.h                            |    5 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Inverse.h                                    |   16 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Map.h                                        |    8 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/MapBase.h                                    |    8 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/MathFunctions.h                              |  477 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/MathFunctionsImpl.h                          |   98 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Matrix.h                                     |   36 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/NestByValue.h                                |    4 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/NumTraits.h                                  |   94 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/PartialReduxEvaluator.h                      |    2 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/PlainObjectBase.h                            |   61 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Product.h                                    |   44 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/ProductEvaluators.h                          |  167 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Random.h                                     |   36 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Redux.h                                      |   22 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Ref.h                                        |  137 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Replicate.h                                  |   12 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Reshaped.h                                   |    7 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/ReturnByValue.h                              |   10 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Reverse.h                                    |   14 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Select.h                                     |   14 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/SelfAdjointView.h                            |   36 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Solve.h                                      |   24 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/SolveTriangular.h                            |   24 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/StableNorm.h                                 |   57 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/StlIterators.h                               |   19 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Stride.h                                     |   13 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Transpose.h                                  |   12 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Transpositions.h                             |   32 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/TriangularMatrix.h                           |  112 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/VectorwiseOp.h                               |   26 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/Visitor.h                                    |  150 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/AVX/Complex.h                           |  102 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/AVX/MathFunctions.h                     |   79 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/AVX/PacketMath.h                        |  390 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/AVX/TypeCasting.h                       |   48 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/AVX512/Complex.h                        |   70 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/AVX512/MathFunctions.h                  |  237 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/AVX512/PacketMath.h                     |  401 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/AVX512/TypeCasting.h                    |   16 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/AltiVec/Complex.h                       |  235 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/AltiVec/MatrixProduct.h                 | 3080 ++++-
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/AltiVec/MatrixProductCommon.h           |only
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/AltiVec/MatrixProductMMA.h              |only
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/AltiVec/PacketMath.h                    |  484 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/CUDA/Complex.h                          |  315 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/Default/BFloat16.h                      |  150 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/Default/ConjHelper.h                    |  116 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/Default/GenericPacketMathFunctions.h    | 1140 +
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/Default/GenericPacketMathFunctionsFwd.h |   51 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/Default/Half.h                          |  510 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/GPU/PacketMath.h                        |  459 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/MSA/Complex.h                           |   72 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/MSA/PacketMath.h                        |    4 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/NEON/Complex.h                          |  109 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/NEON/GeneralBlockPanelKernel.h          |only
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/NEON/MathFunctions.h                    |   24 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/NEON/PacketMath.h                       | 1758 ++
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/NEON/TypeCasting.h                      |    8 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/SSE/Complex.h                           |  178 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/SSE/MathFunctions.h                     |   33 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/SSE/PacketMath.h                        |  389 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/SSE/TypeCasting.h                       |    7 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/SVE                                     |only
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/SYCL/InteropHeaders.h                   |    3 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/SYCL/MathFunctions.h                    |   18 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/ZVector/Complex.h                       |  124 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/ZVector/MathFunctions.h                 |   10 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/arch/ZVector/PacketMath.h                    |   56 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/functors/BinaryFunctors.h                    |  173 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/functors/NullaryFunctors.h                   |    6 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/functors/StlFunctors.h                       |   34 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/functors/UnaryFunctors.h                     |   62 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h           |  201 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/products/GeneralMatrixMatrix.h               |    6 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/products/Parallelizer.h                      |    2 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/products/SelfadjointRank2Update.h            |    4 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/products/TriangularSolverMatrix.h            |    4 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/util/BlasUtil.h                              |  201 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/util/ConfigureVectorization.h                |   62 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/util/Constants.h                             |   21 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/util/DisableStupidWarnings.h                 |    3 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/util/ForwardDeclarations.h                   |    4 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/util/IndexedViewHelper.h                     |   12 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/util/IntegralConstant.h                      |    6 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/util/Macros.h                                |  287 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/util/Memory.h                                |   59 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/util/Meta.h                                  |  255 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/util/StaticAssert.h                          |    5 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/util/SymbolicIndex.h                         |    2 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Core/util/XprHelper.h                             |   50 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Eigenvalues/HessenbergDecomposition.h             |    2 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h              |   97 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Eigenvalues/Tridiagonalization.h                  |   30 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Geometry/AlignedBox.h                             |  102 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Geometry/AngleAxis.h                              |    8 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Geometry/EulerAngles.h                            |    6 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Geometry/Homogeneous.h                            |   26 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Geometry/ParametrizedLine.h                       |    2 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Geometry/Quaternion.h                             |   22 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Geometry/Rotation2D.h                             |    6 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Geometry/Scaling.h                                |    2 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Geometry/Transform.h                              |   82 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Geometry/arch/Geometry_SIMD.h                     |only
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Householder/HouseholderSequence.h                 |   28 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/Jacobi/Jacobi.h                                   |    2 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/LU/FullPivLU.h                                    |    6 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/LU/InverseImpl.h                                  |   31 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/LU/PartialPivLU.h                                 |   13 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/LU/arch/InverseSize4.h                            |only
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/SVD/BDCSVD.h                                      |   34 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/SVD/JacobiSVD.h                                   |   33 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/SVD/SVDBase.h                                     |   42 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/plugins/ArrayCwiseUnaryOps.h                      |   52 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/plugins/BlockMethods.h                            |    3 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/plugins/CommonCwiseUnaryOps.h                     |   43 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/plugins/MatrixCwiseBinaryOps.h                    |    8 
 lightgbm-4.2.0/lightgbm/src/include/Eigen/src/plugins/MatrixCwiseUnaryOps.h                     |   10 
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/arrow.h                                            |only
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/arrow.tpp                                          |only
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/bin.h                                              |  160 
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/boosting.h                                         |    4 
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/c_api.h                                            |  267 
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/config.h                                           |  156 
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/cuda/cuda_algorithms.hpp                           |only
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/cuda/cuda_column_data.hpp                          |only
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/cuda/cuda_metadata.hpp                             |only
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/cuda/cuda_metric.hpp                               |only
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/cuda/cuda_objective_function.hpp                   |only
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/cuda/cuda_random.hpp                               |only
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/cuda/cuda_row_data.hpp                             |only
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/cuda/cuda_split_info.hpp                           |only
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/cuda/cuda_tree.hpp                                 |only
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/cuda/cuda_utils.hu                                 |only
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/cuda/vector_cudahost.h                             |    4 
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/dataset.h                                          |  390 
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/dataset_loader.h                                   |   23 
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/fast_double_parser.h                               |   74 
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/feature_group.h                                    |  175 
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/fmt/args.h                                         |only
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/fmt/chrono.h                                       | 1682 ++
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/fmt/color.h                                        |  273 
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/fmt/compile.h                                      |  731 -
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/fmt/core.h                                         | 2958 +++-
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/fmt/format-inl.h                                   | 3675 ++----
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/fmt/format.h                                       | 6100 +++++-----
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/fmt/os.h                                           |  355 
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/fmt/ostream.h                                      |  240 
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/fmt/printf.h                                       |  642 -
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/fmt/ranges.h                                       |  738 -
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/fmt/std.h                                          |only
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/fmt/xchar.h                                        |only
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/meta.h                                             |    2 
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/metric.h                                           |    5 
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/objective_function.h                               |   20 
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/sample_strategy.h                                  |only
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/train_share_states.h                               |  198 
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/tree.h                                             |   28 
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/tree_learner.h                                     |   13 
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/utils/binary_writer.h                              |only
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/utils/byte_buffer.h                                |only
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/utils/common.h                                     |   38 
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/utils/file_io.h                                    |   30 
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/utils/json11.h                                     |    4 
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/utils/openmp_wrapper.h                             |   39 
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/utils/text_reader.h                                |   11 
 lightgbm-4.2.0/lightgbm/src/include/LightGBM/utils/threading.h                                  |    2 
 lightgbm-4.2.0/lightgbm/src/io/bin.cpp                                                          |  418 
 lightgbm-4.2.0/lightgbm/src/io/config.cpp                                                       |  137 
 lightgbm-4.2.0/lightgbm/src/io/config_auto.cpp                                                  |  316 
 lightgbm-4.2.0/lightgbm/src/io/cuda                                                             |only
 lightgbm-4.2.0/lightgbm/src/io/dataset.cpp                                                      |  751 -
 lightgbm-4.2.0/lightgbm/src/io/dataset_loader.cpp                                               |  501 
 lightgbm-4.2.0/lightgbm/src/io/dense_bin.hpp                                                    |  146 
 lightgbm-4.2.0/lightgbm/src/io/file_io.cpp                                                      |    2 
 lightgbm-4.2.0/lightgbm/src/io/json11.cpp                                                       |    6 
 lightgbm-4.2.0/lightgbm/src/io/metadata.cpp                                                     |  473 
 lightgbm-4.2.0/lightgbm/src/io/multi_val_dense_bin.hpp                                          |  129 
 lightgbm-4.2.0/lightgbm/src/io/multi_val_sparse_bin.hpp                                         |  133 
 lightgbm-4.2.0/lightgbm/src/io/parser.cpp                                                       |   56 
 lightgbm-4.2.0/lightgbm/src/io/sparse_bin.hpp                                                   |  191 
 lightgbm-4.2.0/lightgbm/src/io/train_share_states.cpp                                           |  166 
 lightgbm-4.2.0/lightgbm/src/io/tree.cpp                                                         |   43 
 lightgbm-4.2.0/lightgbm/src/lightgbm_R.cpp                                                      |  519 
 lightgbm-4.2.0/lightgbm/src/lightgbm_R.h                                                        |  286 
 lightgbm-4.2.0/lightgbm/src/metric/binary_metric.hpp                                            |   10 
 lightgbm-4.2.0/lightgbm/src/metric/cuda                                                         |only
 lightgbm-4.2.0/lightgbm/src/metric/map_metric.hpp                                               |    4 
 lightgbm-4.2.0/lightgbm/src/metric/metric.cpp                                                   |  160 
 lightgbm-4.2.0/lightgbm/src/metric/multiclass_metric.hpp                                        |    8 
 lightgbm-4.2.0/lightgbm/src/metric/rank_metric.hpp                                              |    6 
 lightgbm-4.2.0/lightgbm/src/metric/regression_metric.hpp                                        |   10 
 lightgbm-4.2.0/lightgbm/src/metric/xentropy_metric.hpp                                          |   24 
 lightgbm-4.2.0/lightgbm/src/network/linker_topo.cpp                                             |    4 
 lightgbm-4.2.0/lightgbm/src/network/linkers_socket.cpp                                          |    2 
 lightgbm-4.2.0/lightgbm/src/network/socket_wrapper.hpp                                          |    9 
 lightgbm-4.2.0/lightgbm/src/objective/binary_objective.hpp                                      |   18 
 lightgbm-4.2.0/lightgbm/src/objective/cuda                                                      |only
 lightgbm-4.2.0/lightgbm/src/objective/multiclass_objective.hpp                                  |   10 
 lightgbm-4.2.0/lightgbm/src/objective/objective_function.cpp                                    |  123 
 lightgbm-4.2.0/lightgbm/src/objective/rank_objective.hpp                                        |   99 
 lightgbm-4.2.0/lightgbm/src/objective/regression_objective.hpp                                  |  109 
 lightgbm-4.2.0/lightgbm/src/objective/xentropy_objective.hpp                                    |   20 
 lightgbm-4.2.0/lightgbm/src/treelearner/col_sampler.hpp                                         |    6 
 lightgbm-4.2.0/lightgbm/src/treelearner/cost_effective_gradient_boosting.hpp                    |   16 
 lightgbm-4.2.0/lightgbm/src/treelearner/cuda                                                    |only
 lightgbm-4.2.0/lightgbm/src/treelearner/data_parallel_tree_learner.cpp                          |  344 
 lightgbm-4.2.0/lightgbm/src/treelearner/data_partition.hpp                                      |    2 
 lightgbm-4.2.0/lightgbm/src/treelearner/feature_histogram.hpp                                   |  683 +
 lightgbm-4.2.0/lightgbm/src/treelearner/feature_parallel_tree_learner.cpp                       |    1 
 lightgbm-4.2.0/lightgbm/src/treelearner/gpu_tree_learner.cpp                                    |   74 
 lightgbm-4.2.0/lightgbm/src/treelearner/gpu_tree_learner.h                                      |    2 
 lightgbm-4.2.0/lightgbm/src/treelearner/gradient_discretizer.cpp                                |only
 lightgbm-4.2.0/lightgbm/src/treelearner/gradient_discretizer.hpp                                |only
 lightgbm-4.2.0/lightgbm/src/treelearner/leaf_splits.hpp                                         |  107 
 lightgbm-4.2.0/lightgbm/src/treelearner/linear_tree_learner.cpp                                 |   22 
 lightgbm-4.2.0/lightgbm/src/treelearner/linear_tree_learner.h                                   |   10 
 lightgbm-4.2.0/lightgbm/src/treelearner/monotone_constraints.hpp                                |    2 
 lightgbm-4.2.0/lightgbm/src/treelearner/parallel_tree_learner.h                                 |   24 
 lightgbm-4.2.0/lightgbm/src/treelearner/serial_tree_learner.cpp                                 |  436 
 lightgbm-4.2.0/lightgbm/src/treelearner/serial_tree_learner.h                                   |   21 
 lightgbm-4.2.0/lightgbm/src/treelearner/split_info.hpp                                          |   12 
 lightgbm-4.2.0/lightgbm/src/treelearner/tree_learner.cpp                                        |   18 
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 lightgbm-4.2.0/lightgbm/tests/testthat/test_lgb.convert_with_rules.R                            |   10 
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 lightgbm-4.2.0/lightgbm/tests/testthat/test_lgb.interprete.R                                    |    8 
 lightgbm-4.2.0/lightgbm/tests/testthat/test_lgb.plot.importance.R                               |    4 
 lightgbm-4.2.0/lightgbm/tests/testthat/test_lgb.plot.interpretation.R                           |    8 
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Permanent link

Package grattan updated to version 2023.1.2 with previous version 2023.1.1 dated 2023-09-04

Title: Australian Tax Policy Analysis
Description: Utilities to cost and evaluate Australian tax policy, including fast projections of personal income tax collections, high-performance tax and transfer calculators, and an interface to common indices from the Australian Bureau of Statistics. Written to support Grattan Institute's Australian Perspectives program, and related projects. Access to the Australian Taxation Office's sample files of personal income tax returns is assumed.
Author: Hugh Parsonage [aut, cre], Tim Cameron [aut], Brendan Coates [aut], Matthew Katzen [aut], William Young [aut], Ittima Cherastidtham [dtc], W. Karsten [ctb], M. Enrique Garcia [ctb], Matt Cowgill [aut]
Maintainer: Hugh Parsonage <hugh.parsonage@gmail.com>

Diff between grattan versions 2023.1.1 dated 2023-09-04 and 2023.1.2 dated 2023-12-08

 DESCRIPTION                      |    8 ++++----
 MD5                              |   26 +++++++++++++-------------
 NEWS.md                          |    4 ++++
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 man/income_tax.Rd                |    5 ++++-
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 src/isEquiInt.c                  |    2 +-
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New package fishRman with initial version 1.2.2
Package: fishRman
Title: The Fisheries Scientist's Toolbox
Version: 1.2.2
Description: A bundle of analytics tools for fisheries scientists. Data on fishing effort by 'Global Fishing Watch' can be retrieved via the package's API <https://fishrman.ddnsfree.com/gfw>, as well as data on Exclusive Economic Zones by 'Marine Regions'. A 'shiny' R App is included for a 'no-code' solution for retrieval, analysis, and visualization.
License: AGPL (>= 3)
Depends: R (>= 2.10)
Imports: config (>= 0.3.1), countrycode, dplyr, ggplot2, golem (>= 0.3.3), httr, jsonlite, maps, sf, shiny (>= 1.7.1), shinyBS, shinyjs, shinyWidgets, stats, utils, viridis
Suggests: testthat (>= 3.0.0)
Encoding: UTF-8
Date: 2023-12-07
URL: https://github.com/Shyentist/fish-r-man
BugReports: https://github.com/Shyentist/fish-r-man/issues
NeedsCompilation: no
Packaged: 2023-12-08 08:57:03 UTC; pico
Author: Pasquale Buonomo [cre, aut]
Maintainer: Pasquale Buonomo <pasqualebuonomo@hotmail.it>
Repository: CRAN
Date/Publication: 2023-12-08 11:30:02 UTC

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New package dsem with initial version 1.0.0
Package: dsem
Title: Fit Dynamic Structural Equation Models
Version: 1.0.0
Date: 2023-12-04
Imports: TMB (>= 1.9.7), Matrix (>= 1.6.3), sem, igraph, methods
Depends: R (>= 4.0.0),
Suggests: knitr, AER, phylopath, rmarkdown, reshape, gridExtra, dynlm, MARSS, ggplot2, ggpubr, ggraph, grid, vars, testthat
Enhances: rstan, tmbstan
LinkingTo: TMB, RcppEigen
Description: Applies dynamic structural equation models to time-series data with generic and simplified specification for simultaneous and lagged effects. Methods are described in Thorson et al. (In revision) "Dynamic structural equation models synthesize ecosystem dynamics constrained by ecological mechanisms."
License: GPL-3
Encoding: UTF-8
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: yes
Packaged: 2023-12-08 01:09:20 UTC; James.Thorson
Author: James Thorson [aut, cre]
Maintainer: James Thorson <James.Thorson@noaa.gov>
Repository: CRAN
Date/Publication: 2023-12-08 11:20:08 UTC

More information about dsem at CRAN
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Package data.table updated to version 1.14.10 with previous version 1.14.8 dated 2023-02-17

Title: Extension of `data.frame`
Description: Fast aggregation of large data (e.g. 100GB in RAM), fast ordered joins, fast add/modify/delete of columns by group using no copies at all, list columns, friendly and fast character-separated-value read/write. Offers a natural and flexible syntax, for faster development.
Author: Tyson Barrett [aut, cre], Matt Dowle [aut], Arun Srinivasan [aut], Jan Gorecki [ctb], Michael Chirico [ctb], Pasha Stetsenko [ctb], Tom Short [ctb], Steve Lianoglou [ctb], Eduard Antonyan [ctb], Markus Bonsch [ctb], Hugh Parsonage [ctb], Scott Ritchi [...truncated...]
Maintainer: Tyson Barrett <t.barrett88@gmail.com>

Diff between data.table versions 1.14.8 dated 2023-02-17 and 1.14.10 dated 2023-12-08

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More information about data.table at CRAN
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New package blackmarbler with initial version 0.1.0
Package: blackmarbler
Title: Black Marble Data and Statistics
Version: 0.1.0
Description: Geographically referenced data and statistics of nighttime lights from NASA Black Marble <https://blackmarble.gsfc.nasa.gov/>.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://worldbank.github.io/blackmarbler/
BugReports: https://github.com/worldbank/blackmarbler/issues
Imports: readr, hdf5r, dplyr, purrr, lubridate, raster, sf, exactextractr, stringr, httr
Suggests: geodata, ggplot2, tidyr, knitr
NeedsCompilation: no
Packaged: 2023-12-07 19:17:45 UTC; robmarty
Author: Robert Marty [aut, cre] , Gabriel Stefanini Vicente [aut]
Maintainer: Robert Marty <rmarty@worldbank.org>
Repository: CRAN
Date/Publication: 2023-12-08 11:20:21 UTC

More information about blackmarbler at CRAN
Permanent link

Package symengine updated to version 0.2.3 with previous version 0.2.2 dated 2022-10-23

Title: Interface to the 'SymEngine' Library
Description: Provides an R interface to 'SymEngine' <https://github.com/symengine/>, a standalone 'C++' library for fast symbolic manipulation. The package has functionalities for symbolic computation like calculating exact mathematical expressions, solving systems of linear equations and code generation.
Author: Jialin Ma [cre, aut], Isuru Fernando [aut], Xin Chen [aut]
Maintainer: Jialin Ma <marlin@inventati.org>

Diff between symengine versions 0.2.2 dated 2022-10-23 and 0.2.3 dated 2023-12-08

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More information about symengine at CRAN
Permanent link

Package rtables updated to version 0.6.6 with previous version 0.6.3 dated 2023-08-30

Title: Reporting Tables
Description: Reporting tables often have structure that goes beyond simple rectangular data. The 'rtables' package provides a framework for declaring complex multi-level tabulations and then applying them to data. This framework models both tabulation and the resulting tables as hierarchical, tree-like objects which support sibling sub-tables, arbitrary splitting or grouping of data in row and column dimensions, cells containing multiple values, and the concept of contextual summary computations. A convenient pipe-able interface is provided for declaring table layouts and the corresponding computations, and then applying them to data.
Author: Gabriel Becker [aut] , Adrian Waddell [aut], Daniel Sabanes Bove [ctb], Maximilian Mordig [ctb], Davide Garolini [ctb], Emily de la Rua [ctb], Abinaya Yogasekaram [ctb], Joe Zhu [ctb, cre], F. Hoffmann-La Roche AG [cph, fnd]
Maintainer: Joe Zhu <joe.zhu@roche.com>

Diff between rtables versions 0.6.3 dated 2023-08-30 and 0.6.6 dated 2023-12-08

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Package Rbeast updated to version 1.0.0 with previous version 0.9.9 dated 2023-05-14

Title: Bayesian Change-Point Detection and Time Series Decomposition
Description: Interpretation of time series data is affected by model choices. Different models can give different or even contradicting estimates of patterns, trends, and mechanisms for the same data--a limitation alleviated by the Bayesian estimator of abrupt change,seasonality, and trend (BEAST) of this package. BEAST seeks to improve time series decomposition by forgoing the "single-best-model" concept and embracing all competing models into the inference via a Bayesian model averaging scheme. It is a flexible tool to uncover abrupt changes (i.e., change-points), cyclic variations (e.g., seasonality), and nonlinear trends in time-series observations. BEAST not just tells when changes occur but also quantifies how likely the detected changes are true. It detects not just piecewise linear trends but also arbitrary nonlinear trends. BEAST is applicable to real-valued time series data of all kinds, be it for remote sensing, economics, climate sciences, ecology, and hydrology. Example applications in [...truncated...]
Author: Tongxi Hu [aut], Yang Li [aut], Xuesong Zhang [aut], Kaiguang Zhao [aut, cre], Jack Dongarra [ctb], Cleve Moler [ctb]
Maintainer: Kaiguang Zhao <zhao.1423@osu.edu>

Diff between Rbeast versions 0.9.9 dated 2023-05-14 and 1.0.0 dated 2023-12-08

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Package plugdensity updated to version 0.8-5 with previous version 0.8-4 dated 2022-02-23

Title: Plug-in Kernel Density Estimation
Description: Kernel density estimation with global bandwidth selection via "plug-in".
Author: Eva Herrmann <eherrmann@mathematik.tu-darmstadt.de> ; R interface etc by Martin Maechler
Maintainer: Martin Maechler <maechler@stat.math.ethz.ch>

Diff between plugdensity versions 0.8-4 dated 2022-02-23 and 0.8-5 dated 2023-12-08

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Package GenTwoArmsTrialSize updated to version 0.0.4.4 with previous version 0.0.4.3 dated 2023-12-07

Title: Generalized Two Arms Clinical Trial Sample Size Calculation
Description: Two arms clinical trials required sample size is calculated in the comprehensive parametric context. The calculation is based on the type of endpoints(continuous/binary/time-to-event/ordinal), design (parallel/crossover), hypothesis tests (equality/noninferiority/superiority/equivalence), trial arms noncompliance rates and expected loss of follow-up. Methods are described in: Chow SC, Shao J, Wang H, Lokhnygina Y (2017) <doi:10.1201/9781315183084>, Wittes, J (2002) <doi:10.1093/epirev/24.1.39>, Sato, T (2000) <doi:10.1002/1097-0258(20001015)19:19%3C2689::aid-sim555%3E3.0.co;2-0>, Lachin J M, Foulkes, M A (1986) <doi:10.2307/2531201>, Whitehead J(1993) <doi:10.1002/sim.4780122404>, Julious SA (2023) <doi:10.1201/9780429503658>.
Author: Mohsen Soltanifar [aut] , Chel Hee Lee [cre, aut]
Maintainer: Chel Hee Lee <chelhee.lee@ucalgary.ca>

Diff between GenTwoArmsTrialSize versions 0.0.4.3 dated 2023-12-07 and 0.0.4.4 dated 2023-12-08

 DESCRIPTION |    8 ++++----
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New package civ with initial version 0.1.0
Package: civ
Title: Categorical Instrumental Variables
Version: 0.1.0
Date: 2023-12-07
Description: Implementation of the categorical instrumental variable (CIV) estimator proposed by Wiemann (2023) <arXiv:2311.17021>. CIV allows for optimal instrumental variable estimation in settings with relatively few observations per category. To obtain valid inference in these challenging settings, CIV leverages a regularization assumption that implies existence of a latent categorical variable with fixed finite support achieving the same first stage fit as the observed instrument.
License: GPL (>= 3)
URL: https://github.com/thomaswiemann/civ
BugReports: https://github.com/thomaswiemann/civ/issues
Encoding: UTF-8
Depends: R (>= 3.6)
Imports: stats, AER, kcmeans
Suggests: testthat (>= 3.0.0), covr, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2023-12-07 22:09:29 UTC; thomas
Author: Thomas Wiemann [aut, cre]
Maintainer: Thomas Wiemann <wiemann@uchicago.edu>
Repository: CRAN
Date/Publication: 2023-12-08 11:00:06 UTC

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Package blaise updated to version 1.3.11 with previous version 1.3.10 dated 2023-08-18

Title: Read and Write FWF Files in the 'Blaise' Format
Description: Can be used to read and write a fwf with an accompanying 'Blaise' datamodel. Blaise is the software suite built by Statistics Netherlands (CBS). It is essentially a way to write and collect surveys and perform statistical analysis on the data. It stores its data in fixed width format with an accompanying metadata file, this is the Blaise format. The package automatically interprets this metadata and reads the file into an R dataframe. When supplying a datamodel for writing, the dataframe will be automatically converted to that format and checked for compatibility. Supports dataframes, tibbles and LaF objects. For more information about 'Blaise', see <https://blaise.com/products/general-information>.
Author: Sjoerd Ophof [aut, cre]
Maintainer: Sjoerd Ophof <sjoerd.ophof@gmail.com>

Diff between blaise versions 1.3.10 dated 2023-08-18 and 1.3.11 dated 2023-12-08

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Package collinear updated to version 1.1.1 with previous version 1.1.0 dated 2023-11-30

Title: Seamless Multicollinearity Management
Description: System for seamless management of multicollinearity in data frames with numeric and/or categorical variables for statistical analysis and machine learning modeling. The package combines bivariate correlation (Pearson, Spearman, and Cramer's V) with variance inflation factor analysis, target encoding to transform categorical variables into numeric (Micci-Barreca, D. 2001 <DOI:10.1145/507533.507538>), and a flexible feature prioritization method, to deliver a comprehensive multicollinearity management tool covering a wide range of use cases.
Author: Blas M. Benito [aut, cre, cph]
Maintainer: Blas M. Benito <blasbenito@gmail.com>

Diff between collinear versions 1.1.0 dated 2023-11-30 and 1.1.1 dated 2023-12-08

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Package curl updated to version 5.2.0 with previous version 5.1.0 dated 2023-10-02

Title: A Modern and Flexible Web Client for R
Description: The curl() and curl_download() functions provide highly configurable drop-in replacements for base url() and download.file() with better performance, support for encryption (https, ftps), gzip compression, authentication, and other 'libcurl' goodies. The core of the package implements a framework for performing fully customized requests where data can be processed either in memory, on disk, or streaming via the callback or connection interfaces. Some knowledge of 'libcurl' is recommended; for a more-user-friendly web client see the 'httr' package which builds on this package with http specific tools and logic.
Author: Jeroen Ooms [aut, cre] , Hadley Wickham [ctb], RStudio [cph]
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

Diff between curl versions 5.1.0 dated 2023-10-02 and 5.2.0 dated 2023-12-08

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Package KnockoffTrio updated to version 1.0.2 with previous version 1.0.1 dated 2022-10-17

Title: Trio Data Analysis with Knockoff Statistics for FDR Control
Description: Identification of putative causal variants in genome-wide association studies with the trio design. The package implements the methods in the paper: Yang, Y., Wang, C., Liu, L., Buxbaum, J., He, Z., & Ionita-Laza, I. (2022). KnockoffTrio: A knockoff framework for the identification of putative causal variants in genome-wide association studies with trio design. The American Journal of Human Genetics, 109(10), 1761-1776.
Author: Yi Yang [aut, cre]
Maintainer: Yi Yang <yi.yang@cityu.edu.hk>

Diff between KnockoffTrio versions 1.0.1 dated 2022-10-17 and 1.0.2 dated 2023-12-08

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 R/create_knockoff.R    |    4 ++--
 man/create_knockoff.Rd |    4 ++--
 4 files changed, 10 insertions(+), 10 deletions(-)

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Package GaSP updated to version 1.0.5 with previous version 1.0.4 dated 2023-05-18

Title: Train and Apply a Gaussian Stochastic Process Model
Description: Train a Gaussian stochastic process model of an unknown function, possibly observed with error, via maximum likelihood or maximum a posteriori (MAP) estimation, run model diagnostics, and make predictions, following Sacks, J., Welch, W.J., Mitchell, T.J., and Wynn, H.P. (1989) "Design and Analysis of Computer Experiments", Statistical Science, <doi:10.1214/ss/1177012413>. Perform sensitivity analysis and visualize low-order effects, following Schonlau, M. and Welch, W.J. (2006), "Screening the Input Variables to a Computer Model Via Analysis of Variance and Visualization", <doi:10.1007/0-387-28014-6_14>.
Author: William J. Welch [aut, cre, cph] , Yilin Yang [aut]
Maintainer: William J. Welch <will@stat.ubc.ca>

Diff between GaSP versions 1.0.4 dated 2023-05-18 and 1.0.5 dated 2023-12-08

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 11 files changed, 52 insertions(+), 39 deletions(-)

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Package onbrand updated to version 1.0.4 with previous version 1.0.3 dated 2023-07-16

Title: Templated Reporting Workflows in Word and PowerPoint
Description: Automated reporting in Word and PowerPoint can require customization for each organizational template. This package works around this by adding standard reporting functions and an abstraction layer to facilitate automated reporting workflows that can be replicated across different organizational templates.
Author: John Harrold [aut, cre] , Bryan Smith [aut]
Maintainer: John Harrold <john.m.harrold@gmail.com>

Diff between onbrand versions 1.0.3 dated 2023-07-16 and 1.0.4 dated 2023-12-08

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 onbrand-1.0.4/onbrand/NEWS.md                                           |    4 
 onbrand-1.0.4/onbrand/R/add_pptx_ph_content.R                           |   50 
 onbrand-1.0.4/onbrand/R/report_add_slide.R                              |  124 +-
 onbrand-1.0.4/onbrand/inst/doc/Creating_Templated_Office_Workflows.R    |   36 
 onbrand-1.0.4/onbrand/inst/doc/Creating_Templated_Office_Workflows.Rmd  |   48 
 onbrand-1.0.4/onbrand/inst/doc/Creating_Templated_Office_Workflows.html |  543 +++++-----
 onbrand-1.0.4/onbrand/inst/doc/Custom_Office_Templates.Rmd              |    2 
 onbrand-1.0.4/onbrand/inst/doc/Custom_Office_Templates.html             |    3 
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 onbrand-1.0.4/onbrand/vignettes/Creating_Templated_Office_Workflows.Rmd |   48 
 onbrand-1.0.4/onbrand/vignettes/Custom_Office_Templates.Rmd             |    2 
 onbrand-1.0.4/onbrand/vignettes/ppt_workflow_output.png                 |binary
 16 files changed, 647 insertions(+), 332 deletions(-)

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Package Canek updated to version 0.2.5 with previous version 0.2.4 dated 2023-11-05

Title: Batch Correction of Single Cell Transcriptome Data
Description: Non-linear/linear hybrid method for batch-effect correction that uses Mutual Nearest Neighbors (MNNs) to identify similar cells between datasets. Reference: Loza M. et al. (NAR Genomics and Bioinformatics, 2020) <doi:10.1093/nargab/lqac022>.
Author: Martin Loza [aut, cre] , Diego Diez [aut]
Maintainer: Martin Loza <martin.loza.lopez@gmail.com>

Diff between Canek versions 0.2.4 dated 2023-11-05 and 0.2.5 dated 2023-12-08

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 6 files changed, 20 insertions(+), 14 deletions(-)

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Package ASGS.foyer updated to version 0.3.3 with previous version 0.3.1 dated 2021-03-21

Title: Interface to the Australian Statistical Geography Standard
Description: The Australian Statistical Geography Standard ('ASGS') is a set of shapefiles by the Australian Bureau of Statistics. This package provides an interface to those shapefiles, as well as methods for converting coordinates to shapefiles.
Author: Hugh Parsonage [aut, cre]
Maintainer: Hugh Parsonage <hugh.parsonage@gmail.com>

Diff between ASGS.foyer versions 0.3.1 dated 2021-03-21 and 0.3.3 dated 2023-12-08

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 man/install_ASGS.Rd |    5 ++++-
 6 files changed, 39 insertions(+), 17 deletions(-)

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