Wed, 17 Jul 2024

Package sparseR updated to version 0.3.1 with previous version 0.3.0 dated 2024-06-26

Title: Variable Selection under Ranked Sparsity Principles for Interactions and Polynomials
Description: An implementation of ranked sparsity methods, including penalized regression methods such as the sparsity-ranked lasso, its non-convex alternatives, and elastic net, as well as the sparsity-ranked Bayesian Information Criterion. As described in Peterson and Cavanaugh (2022) <doi:10.1007/s10182-021-00431-7>, ranked sparsity is a philosophy with methods primarily useful for variable selection in the presence of prior informational asymmetry, which occurs in the context of trying to perform variable selection in the presence of interactions and/or polynomials. Ultimately, this package attempts to facilitate dealing with cumbersome interactions and polynomials while not avoiding them entirely. Typically, models selected under ranked sparsity principles will also be more transparent, having fewer falsely selected interactions and polynomials than other methods.
Author: Ryan Andrew Peterson [aut, cre]
Maintainer: Ryan Andrew Peterson <ryan.a.peterson@cuanschutz.edu>

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Package statnetWeb updated to version 0.5.8 with previous version 0.5.6 dated 2020-08-05

Title: A Shiny App for Network Modeling with 'statnet'
Description: A graphical user interface for cross-sectional network modeling with the 'statnet' software suite <https://github.com/statnet>.
Author: Martina Morris [cre, aut], Emily Beylerian [aut], Kirk Li [ctb], Samuel Jenness [ctb], Michal Bojanowski [ctb]
Maintainer: Martina Morris <morrism@uw.edu>

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Package threshr updated to version 1.0.6 with previous version 1.0.5 dated 2023-12-02

Title: Threshold Selection and Uncertainty for Extreme Value Analysis
Description: Provides functions for the selection of thresholds for use in extreme value models, based mainly on the methodology in Northrop, Attalides and Jonathan (2017) <doi:10.1111/rssc.12159>. It also performs predictive inferences about future extreme values, based either on a single threshold or on a weighted average of inferences from multiple thresholds, using the 'revdbayes' package <https://cran.r-project.org/package=revdbayes>. At the moment only the case where the data can be treated as independent identically distributed observations is considered.
Author: Paul J. Northrop [aut, cre, cph], Nicolas Attalides [aut]
Maintainer: Paul J. Northrop <p.northrop@ucl.ac.uk>

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Package see updated to version 0.8.5 with previous version 0.8.4 dated 2024-04-29

Title: Model Visualisation Toolbox for 'easystats' and 'ggplot2'
Description: Provides plotting utilities supporting packages in the 'easystats' ecosystem (<https://github.com/easystats/easystats>) and some extra themes, geoms, and scales for 'ggplot2'. Color scales are based on <https://materialui.co/>. References: Lüdecke et al. (2021) <doi:10.21105/joss.03393>.
Author: Daniel Luedecke [aut, ctb] , Dominique Makowski [aut, inv] , Indrajeet Patil [aut, cre] , Mattan S. Ben-Shachar [aut, ctb] , Brenton M. Wiernik [aut, ctb] , Philip Waggoner [aut, ctb] , Jeffrey R. Stevens [ctb] , Matthew Smith [rev] , Jakob Bossek [re [...truncated...]
Maintainer: Indrajeet Patil <patilindrajeet.science@gmail.com>

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Package bang updated to version 1.0.4 with previous version 1.0.3 dated 2023-12-02

Title: Bayesian Analysis, No Gibbs
Description: Provides functions for the Bayesian analysis of some simple commonly-used models, without using Markov Chain Monte Carlo (MCMC) methods such as Gibbs sampling. The 'rust' package <https://cran.r-project.org/package=rust> is used to simulate a random sample from the required posterior distribution, using the generalized ratio-of-uniforms method. See Wakefield, Gelfand and Smith (1991) <DOI:10.1007/BF01889987> for details. At the moment three conjugate hierarchical models are available: beta-binomial, gamma-Poisson and a 1-way analysis of variance (ANOVA).
Author: Paul J. Northrop [aut, cre, cph], Benjamin D. Hall [aut, cph]
Maintainer: Paul J. Northrop <p.northrop@ucl.ac.uk>

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Package lite updated to version 1.1.1 with previous version 1.1.0 dated 2023-01-26

Title: Likelihood-Based Inference for Time Series Extremes
Description: Performs likelihood-based inference for stationary time series extremes. The general approach follows Fawcett and Walshaw (2012) <doi:10.1002/env.2133>. Marginal extreme value inferences are adjusted for cluster dependence in the data using the methodology in Chandler and Bate (2007) <doi:10.1093/biomet/asm015>, producing an adjusted log-likelihood for the model parameters. A log-likelihood for the extremal index is produced using the K-gaps model of Suveges and Davison (2010) <doi:10.1214/09-AOAS292>. These log-likelihoods are combined to make inferences about extreme values. Both maximum likelihood and Bayesian approaches are available.
Author: Paul J. Northrop [aut, cre, cph]
Maintainer: Paul J. Northrop <p.northrop@ucl.ac.uk>

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Package rerddapXtracto updated to version 1.2.1 with previous version 1.2.0 dated 2024-01-12

Title: Extracts Environmental Data from 'ERDDAP™' Web Services
Description: Contains three functions that access environmental data from any 'ERDDAP™' data web service. The rxtracto() function extracts data along a trajectory for a given "radius" around the point. The rxtracto_3D() function extracts data in a box. The rxtractogon() function extracts data in a polygon. All of those three function use the 'rerddap' package to extract the data, and should work with any 'ERDDAP™' server. There are also two functions, plotBBox() and plotTrack() that use the 'plotdap' package to simplify the creation of maps of the data.
Author: Roy Mendelssohn [aut, cre], Marie Auger-Methe [ctb], Sunny Bak-Hospital [ctb]
Maintainer: Roy Mendelssohn <roy.mendelssohn@noaa.gov>

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Package SparseM updated to version 1.84-2 with previous version 1.84 dated 2024-06-25

Title: Sparse Linear Algebra
Description: Some basic linear algebra functionality for sparse matrices is provided: including Cholesky decomposition and backsolving as well as standard R subsetting and Kronecker products.
Author: Roger Koenker [cre, aut], Pin Tian Ng [ctb] , Yousef Saad [ctb] , Ben Shaby [ctb] , Martin Maechler [ctb] tweaks; S4, <https://orcid.org/0000-0002-8685-9910>)
Maintainer: Roger Koenker <rkoenker@uiuc.edu>

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Package revdbayes updated to version 1.5.4 with previous version 1.5.3 dated 2023-12-01

Title: Ratio-of-Uniforms Sampling for Bayesian Extreme Value Analysis
Description: Provides functions for the Bayesian analysis of extreme value models. The 'rust' package <https://cran.r-project.org/package=rust> is used to simulate a random sample from the required posterior distribution. The functionality of 'revdbayes' is similar to the 'evdbayes' package <https://cran.r-project.org/package=evdbayes>, which uses Markov Chain Monte Carlo ('MCMC') methods for posterior simulation. In addition, there are functions for making inferences about the extremal index, using the models for threshold inter-exceedance times of Suveges and Davison (2010) <doi:10.1214/09-AOAS292> and Holesovsky and Fusek (2020) <doi:10.1007/s10687-020-00374-3>. Also provided are d,p,q,r functions for the Generalised Extreme Value ('GEV') and Generalised Pareto ('GP') distributions that deal appropriately with cases where the shape parameter is very close to zero.
Author: Paul J. Northrop [aut, cre, cph], Scott D. Grimshaw [ctb]
Maintainer: Paul J. Northrop <p.northrop@ucl.ac.uk>

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Package ProbBreed updated to version 1.0.4.0 with previous version 1.0.3.2 dated 2024-04-05

Title: Probability Theory for Selecting Candidates in Plant Breeding
Description: Use probability theory under the Bayesian framework for calculating the risk of selecting candidates in a multi-environment context [Dias et al. (2022) <doi:10.1007/s00122-022-04041-y>]. Contained are functions used to fit a Bayesian multi-environment model (based on the available presets), extract posterior values and maximum posterior values, compute the variance components, check the model’s convergence, and calculate the probabilities. For both across and within-environments scopes, the package computes the probability of superior performance and the pairwise probability of superior performance. Furthermore, the probability of superior stability and the pairwise probability of superior stability across environments is estimated. A joint probability of superior performance and stability is also provided.
Author: Saulo Chaves [aut, cre] , Kaio Dias [aut, cph] , Matheus Krause [aut]
Maintainer: Saulo Chaves <saulo.chaves@ufv.br>

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Package cthist updated to version 2.1.11 with previous version 2.1.10 dated 2024-07-09

Title: Clinical Trial Registry History
Description: Retrieves historical versions of clinical trial registry entries from <https://ClinicalTrials.gov>. Package functionality and implementation for v 1.0.0 is documented in Carlisle (2022) <DOI:10.1371/journal.pone.0270909>.
Author: Benjamin Gregory Carlisle [aut, cre]
Maintainer: Benjamin Gregory Carlisle <murph@bgcarlisle.com>

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Package admtools updated to version 0.3.0 with previous version 0.2.0 dated 2024-03-01

Title: Estimate and Manipulate Age-Depth Models
Description: Estimate age-depth models from stratigraphic and sedimentological data, and transform data between the time and stratigraphic domain.
Author: Niklas Hohmann [aut, cre]
Maintainer: Niklas Hohmann <N.H.Hohmann@uu.nl>

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Package erer (with last version 3.1) was removed from CRAN

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

2022-04-18 3.1
2020-05-01 3.0
2016-02-25 2.5
2015-08-31 2.4
2014-11-27 2.3
2014-08-11 2.2
2014-06-03 2.1
2014-01-10 2.0
2013-01-01 1.4
2012-09-18 1.3
2012-08-19 1.2
2012-03-30 1.1
2011-02-04 1.0

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Package apt (with last version 3.0) was removed from CRAN

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

2020-05-01 3.0
2016-02-25 2.5
2015-08-31 2.4
2014-11-27 2.3
2014-08-11 2.2
2014-06-03 2.1
2014-01-10 2.0
2013-01-01 1.3
2012-09-20 1.2
2012-03-31 1.1
2011-02-05 1.0

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Package slam updated to version 0.1-51 with previous version 0.1-50 dated 2022-01-08

Title: Sparse Lightweight Arrays and Matrices
Description: Data structures and algorithms for sparse arrays and matrices, based on index arrays and simple triplet representations, respectively.
Author: Kurt Hornik [aut, cre] , David Meyer [aut], Christian Buchta [aut]
Maintainer: Kurt Hornik <Kurt.Hornik@R-project.org>

Diff between slam versions 0.1-50 dated 2022-01-08 and 0.1-51 dated 2024-07-17

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Package sgof updated to version 2.3.5 with previous version 2.3.4 dated 2023-09-05

Title: Multiple Hypothesis Testing
Description: Seven different methods for multiple testing problems. The SGoF-type methods (see for example, Carvajal Rodríguez et al., 2009 <doi:10.1186/1471-2105-10-209>; de Uña Álvarez, 2012 <doi:10.1515/1544-6115.1812>; Castro Conde et al., 2015 <doi:10.1177/0962280215597580>) and the BH and BY false discovery rate controlling procedures.
Author: Irene Castro Conde and Jacobo de Una Alvarez
Maintainer: Irene Castro Conde <irene.castro@uvigo.es>

Diff between sgof versions 2.3.4 dated 2023-09-05 and 2.3.5 dated 2024-07-17

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Package Rcpp updated to version 1.0.13 with previous version 1.0.12 dated 2024-01-09

Title: Seamless R and C++ Integration
Description: The 'Rcpp' package provides R functions as well as C++ classes which offer a seamless integration of R and C++. Many R data types and objects can be mapped back and forth to C++ equivalents which facilitates both writing of new code as well as easier integration of third-party libraries. Documentation about 'Rcpp' is provided by several vignettes included in this package, via the 'Rcpp Gallery' site at <https://gallery.rcpp.org>, the paper by Eddelbuettel and Francois (2011, <doi:10.18637/jss.v040.i08>), the book by Eddelbuettel (2013, <doi:10.1007/978-1-4614-6868-4>) and the paper by Eddelbuettel and Balamuta (2018, <doi:10.1080/00031305.2017.1375990>); see 'citation("Rcpp")' for details.
Author: Dirk Eddelbuettel, Romain Francois, JJ Allaire, Kevin Ushey, Qiang Kou, Nathan Russell, Inaki Ucar, Douglas Bates and John Chambers
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between Rcpp versions 1.0.12 dated 2024-01-09 and 1.0.13 dated 2024-07-17

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Package permutations updated to version 1.1-5 with previous version 1.1-2 dated 2023-02-21

Title: The Symmetric Group: Permutations of a Finite Set
Description: Manipulates invertible functions from a finite set to itself. Can transform from word form to cycle form and back. To cite the package in publications please use Hankin (2020) "Introducing the permutations R package", SoftwareX, volume 11 <doi:10.1016/j.softx.2020.100453>.
Author: Robin K. S. Hankin [aut, cre] , Paul Egeler [ctb]
Maintainer: Robin K. S. Hankin <hankin.robin@gmail.com>

Diff between permutations versions 1.1-2 dated 2023-02-21 and 1.1-5 dated 2024-07-17

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Package mmirestriktor updated to version 0.3.1 with previous version 0.3.0 dated 2024-06-23

Title: Informative Hypothesis Testing Web Applications
Description: Offering enhanced statistical power compared to traditional hypothesis testing methods, informative hypothesis testing allows researchers to explicitly model their expectations regarding the relationships among parameters. An important software tool for this framework is 'restriktor'. The 'mmirestriktor' package provides 'shiny' web applications to implement some of the basic functionality of 'restriktor'. The mmirestriktor() function launches a 'shiny' application for fitting and analyzing models with constraints. The FbarCards() function launches a card game application which can help build intuition about informative hypothesis testing. The iht_interpreter() helps interpret informative hypothesis testing results based on guidelines in Vanbrabant and Rosseel (2020) <doi:10.4324/9780429273872-14>.
Author: Mackson Ncube [aut, cre], mightymetrika, LLC [cph, fnd]
Maintainer: Mackson Ncube <macksonncube.stats@gmail.com>

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Package manynet updated to version 1.0.1 with previous version 0.4.4 dated 2024-03-15

Title: Many Ways to Make, Modify, Mark, and Map Myriad Networks
Description: Many tools for making, modifying, mapping, marking, measuring, and motifs and memberships of many different types of networks. All functions operate with matrices, edge lists, and 'igraph', 'network', and 'tidygraph' objects, and on one-mode, two-mode (bipartite), and sometimes three-mode networks. The package includes functions for importing and exporting, creating and generating networks, modifying networks and node and tie attributes, and describing and visualizing networks with sensible defaults.
Author: James Hollway [cre, aut, ctb] , Henrique Sposito [ctb]
Maintainer: James Hollway <james.hollway@graduateinstitute.ch>

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Package ipumsr updated to version 0.8.1 with previous version 0.8.0 dated 2024-07-10

Title: An R Interface for Downloading, Reading, and Handling IPUMS Data
Description: An easy way to work with census, survey, and geographic data provided by IPUMS in R. Generate and download data through the IPUMS API and load IPUMS files into R with their associated metadata to make analysis easier. IPUMS data describing 1.4 billion individuals drawn from over 750 censuses and surveys is available free of charge from the IPUMS website <https://www.ipums.org>.
Author: Greg Freedman Ellis [aut], Derek Burk [aut, cre], Finn Roberts [aut], Joe Grover [ctb], Dan Ehrlich [ctb], Renae Rodgers [ctb], Institute for Social Research and Data Innovation [cph]
Maintainer: Derek Burk <ipums+cran@umn.edu>

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Package coda4microbiome updated to version 0.2.4 with previous version 0.2.3 dated 2024-02-21

Title: Compositional Data Analysis for Microbiome Studies
Description: Functions for microbiome data analysis that take into account its compositional nature. Performs variable selection through penalized regression for both, cross-sectional and longitudinal studies, and for binary and continuous outcomes.
Author: Malu Calle [aut] , Toni Susin [aut, cre] , Meritxell Pujolassos [aut]
Maintainer: Toni Susin <toni.susin@upc.edu>

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Package ravetools updated to version 0.1.7 with previous version 0.1.6 dated 2024-06-02

Title: Signal and Image Processing Toolbox for Analyzing Intracranial Electroencephalography Data
Description: Implemented fast and memory-efficient Notch-filter, Welch-periodogram, discrete wavelet spectrogram for minutes of high-resolution signals, fast 3D convolution, image registration, 3D mesh manipulation; providing fundamental toolbox for intracranial Electroencephalography (iEEG) pipelines. Documentation and examples about 'RAVE' project are provided at <https://openwetware.org/wiki/RAVE>, and the paper by John F. Magnotti, Zhengjia Wang, Michael S. Beauchamp (2020) <doi:10.1016/j.neuroimage.2020.117341>; see 'citation("ravetools")' for details.
Author: Zhengjia Wang [aut, cre], John Magnotti [aut], Michael Beauchamp [aut], Trustees of the University of Pennsylvania [cph] , Karim Rahim [cph, ctb] , Thomas Possidente [cph, ctb] , Michael Prerau [cph, ctb] , Marcus Geelnard [ctb, cph] , Stefan Schlage [...truncated...]
Maintainer: Zhengjia Wang <dipterix.wang@gmail.com>

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Package pagenum updated to version 1.3 with previous version 1.2 dated 2021-04-17

Title: Put Page Numbers on Graphics
Description: A simple way to add page numbers to base/ggplot/lattice graphics.
Author: Kevin Wright [aut, cre, cph]
Maintainer: Kevin Wright <kw.stat@gmail.com>

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Package keras3 updated to version 1.1.0 with previous version 1.0.0 dated 2024-05-21

Title: R Interface to 'Keras'
Description: Interface to 'Keras' <https://keras.io>, a high-level neural networks API. 'Keras' was developed with a focus on enabling fast experimentation, supports both convolution based networks and recurrent networks (as well as combinations of the two), and runs seamlessly on both CPU and GPU devices.
Author: Tomasz Kalinowski [aut, cph, cre], Daniel Falbel [ctb, cph], JJ Allaire [aut, cph], Francois Chollet [aut, cph], Posit Software, PBC [cph, fnd], Google [cph, fnd], Yuan Tang [ctb, cph] , Wouter Van Der Bijl [ctb, cph], Martin Studer [ctb, cph], Sigri [...truncated...]
Maintainer: Tomasz Kalinowski <tomasz@posit.co>

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 keras3-1.1.0/keras3/man/application_densenet121.Rd                             |    7 
 keras3-1.1.0/keras3/man/application_densenet169.Rd                             |    7 
 keras3-1.1.0/keras3/man/application_densenet201.Rd                             |    7 
 keras3-1.1.0/keras3/man/application_efficientnet_b0.Rd                         |    5 
 keras3-1.1.0/keras3/man/application_efficientnet_b1.Rd                         |    5 
 keras3-1.1.0/keras3/man/application_efficientnet_b2.Rd                         |    5 
 keras3-1.1.0/keras3/man/application_efficientnet_b3.Rd                         |    5 
 keras3-1.1.0/keras3/man/application_efficientnet_b4.Rd                         |    5 
 keras3-1.1.0/keras3/man/application_efficientnet_b5.Rd                         |    5 
 keras3-1.1.0/keras3/man/application_efficientnet_b6.Rd                         |    5 
 keras3-1.1.0/keras3/man/application_efficientnet_b7.Rd                         |    5 
 keras3-1.1.0/keras3/man/application_efficientnet_v2b0.Rd                       |    7 
 keras3-1.1.0/keras3/man/application_efficientnet_v2b1.Rd                       |    7 
 keras3-1.1.0/keras3/man/application_efficientnet_v2b2.Rd                       |    7 
 keras3-1.1.0/keras3/man/application_efficientnet_v2b3.Rd                       |    7 
 keras3-1.1.0/keras3/man/application_efficientnet_v2l.Rd                        |    7 
 keras3-1.1.0/keras3/man/application_efficientnet_v2m.Rd                        |    7 
 keras3-1.1.0/keras3/man/application_efficientnet_v2s.Rd                        |    7 
 keras3-1.1.0/keras3/man/application_inception_resnet_v2.Rd                     |    7 
 keras3-1.1.0/keras3/man/application_inception_v3.Rd                            |    7 
 keras3-1.1.0/keras3/man/application_mobilenet.Rd                               |    7 
 keras3-1.1.0/keras3/man/application_mobilenet_v2.Rd                            |    7 
 keras3-1.1.0/keras3/man/application_mobilenet_v3_large.Rd                      |    7 
 keras3-1.1.0/keras3/man/application_mobilenet_v3_small.Rd                      |    7 
 keras3-1.1.0/keras3/man/application_nasnet_large.Rd                            |only
 keras3-1.1.0/keras3/man/application_nasnet_mobile.Rd                           |only
 keras3-1.1.0/keras3/man/application_resnet101.Rd                               |    7 
 keras3-1.1.0/keras3/man/application_resnet101_v2.Rd                            |    7 
 keras3-1.1.0/keras3/man/application_resnet152.Rd                               |    7 
 keras3-1.1.0/keras3/man/application_resnet152_v2.Rd                            |    7 
 keras3-1.1.0/keras3/man/application_resnet50.Rd                                |    7 
 keras3-1.1.0/keras3/man/application_resnet50_v2.Rd                             |    7 
 keras3-1.1.0/keras3/man/application_vgg16.Rd                                   |    9 
 keras3-1.1.0/keras3/man/application_vgg19.Rd                                   |    7 
 keras3-1.1.0/keras3/man/application_xception.Rd                                |    7 
 keras3-1.1.0/keras3/man/back-compat.Rd                                         |only
 keras3-1.1.0/keras3/man/clone_model.Rd                                         |    2 
 keras3-1.1.0/keras3/man/deserialize_keras_object.Rd                            |    6 
 keras3-1.1.0/keras3/man/export_savedmodel.keras.src.models.model.Model.Rd      |    2 
 keras3-1.1.0/keras3/man/image_array_save.Rd                                    |    2 
 keras3-1.1.0/keras3/man/image_from_array.Rd                                    |    2 
 keras3-1.1.0/keras3/man/image_load.Rd                                          |    2 
 keras3-1.1.0/keras3/man/image_smart_resize.Rd                                  |    2 
 keras3-1.1.0/keras3/man/image_to_array.Rd                                      |    2 
 keras3-1.1.0/keras3/man/keras3-package.Rd                                      |   14 
 keras3-1.1.0/keras3/man/keras_input.Rd                                         |    6 
 keras3-1.1.0/keras3/man/keras_model_sequential.Rd                              |    4 
 keras3-1.1.0/keras3/man/layer_input.Rd                                         |    6 
 keras3-1.1.0/keras3/man/layer_masking.Rd                                       |    2 
 keras3-1.1.0/keras3/man/layer_multi_head_attention.Rd                          |    3 
 keras3-1.1.0/keras3/man/layer_permute.Rd                                       |    2 
 keras3-1.1.0/keras3/man/layer_tfsm.Rd                                          |    4 
 keras3-1.1.0/keras3/man/layer_torch_module_wrapper.Rd                          |    3 
 keras3-1.1.0/keras3/man/layer_unit_normalization.Rd                            |    2 
 keras3-1.1.0/keras3/man/loss_binary_crossentropy.Rd                            |    8 
 keras3-1.1.0/keras3/man/loss_binary_focal_crossentropy.Rd                      |    8 
 keras3-1.1.0/keras3/man/loss_categorical_crossentropy.Rd                       |    8 
 keras3-1.1.0/keras3/man/loss_categorical_focal_crossentropy.Rd                 |    8 
 keras3-1.1.0/keras3/man/loss_categorical_hinge.Rd                              |    8 
 keras3-1.1.0/keras3/man/loss_cosine_similarity.Rd                              |    8 
 keras3-1.1.0/keras3/man/loss_ctc.Rd                                            |   16 
 keras3-1.1.0/keras3/man/loss_dice.Rd                                           |   42 
 keras3-1.1.0/keras3/man/loss_hinge.Rd                                          |    8 
 keras3-1.1.0/keras3/man/loss_huber.Rd                                          |    8 
 keras3-1.1.0/keras3/man/loss_kl_divergence.Rd                                  |    8 
 keras3-1.1.0/keras3/man/loss_log_cosh.Rd                                       |    8 
 keras3-1.1.0/keras3/man/loss_mean_absolute_error.Rd                            |    8 
 keras3-1.1.0/keras3/man/loss_mean_absolute_percentage_error.Rd                 |    8 
 keras3-1.1.0/keras3/man/loss_mean_squared_error.Rd                             |    8 
 keras3-1.1.0/keras3/man/loss_mean_squared_logarithmic_error.Rd                 |    8 
 keras3-1.1.0/keras3/man/loss_poisson.Rd                                        |    8 
 keras3-1.1.0/keras3/man/loss_sparse_categorical_crossentropy.Rd                |    8 
 keras3-1.1.0/keras3/man/loss_squared_hinge.Rd                                  |    8 
 keras3-1.1.0/keras3/man/loss_tversky.Rd                                        |   16 
 keras3-1.1.0/keras3/man/metric_sparse_categorical_crossentropy.Rd              |   16 
 keras3-1.1.0/keras3/man/op_abs.Rd                                              |   10 
 keras3-1.1.0/keras3/man/op_add.Rd                                              |   10 
 keras3-1.1.0/keras3/man/op_all.Rd                                              |   10 
 keras3-1.1.0/keras3/man/op_any.Rd                                              |   10 
 keras3-1.1.0/keras3/man/op_append.Rd                                           |   10 
 keras3-1.1.0/keras3/man/op_arange.Rd                                           |   10 
 keras3-1.1.0/keras3/man/op_arccos.Rd                                           |   10 
 keras3-1.1.0/keras3/man/op_arccosh.Rd                                          |   10 
 keras3-1.1.0/keras3/man/op_arcsin.Rd                                           |   10 
 keras3-1.1.0/keras3/man/op_arcsinh.Rd                                          |   10 
 keras3-1.1.0/keras3/man/op_arctan.Rd                                           |   10 
 keras3-1.1.0/keras3/man/op_arctan2.Rd                                          |   10 
 keras3-1.1.0/keras3/man/op_arctanh.Rd                                          |   10 
 keras3-1.1.0/keras3/man/op_argmax.Rd                                           |   10 
 keras3-1.1.0/keras3/man/op_argmin.Rd                                           |   10 
 keras3-1.1.0/keras3/man/op_argpartition.Rd                                     |only
 keras3-1.1.0/keras3/man/op_argsort.Rd                                          |   10 
 keras3-1.1.0/keras3/man/op_array.Rd                                            |   10 
 keras3-1.1.0/keras3/man/op_average.Rd                                          |   10 
 keras3-1.1.0/keras3/man/op_average_pool.Rd                                     |    8 
 keras3-1.1.0/keras3/man/op_batch_normalization.Rd                              |    8 
 keras3-1.1.0/keras3/man/op_binary_crossentropy.Rd                              |    8 
 keras3-1.1.0/keras3/man/op_bincount.Rd                                         |   10 
 keras3-1.1.0/keras3/man/op_broadcast_to.Rd                                     |   10 
 keras3-1.1.0/keras3/man/op_cast.Rd                                             |   12 
 keras3-1.1.0/keras3/man/op_categorical_crossentropy.Rd                         |    8 
 keras3-1.1.0/keras3/man/op_ceil.Rd                                             |   10 
 keras3-1.1.0/keras3/man/op_cholesky.Rd                                         |    9 
 keras3-1.1.0/keras3/man/op_clip.Rd                                             |   10 
 keras3-1.1.0/keras3/man/op_concatenate.Rd                                      |   10 
 keras3-1.1.0/keras3/man/op_cond.Rd                                             |   12 
 keras3-1.1.0/keras3/man/op_conj.Rd                                             |   10 
 keras3-1.1.0/keras3/man/op_conv.Rd                                             |    8 
 keras3-1.1.0/keras3/man/op_conv_transpose.Rd                                   |    8 
 keras3-1.1.0/keras3/man/op_convert_to_numpy.Rd                                 |   12 
 keras3-1.1.0/keras3/man/op_convert_to_tensor.Rd                                |   12 
 keras3-1.1.0/keras3/man/op_copy.Rd                                             |   10 
 keras3-1.1.0/keras3/man/op_correlate.Rd                                        |   10 
 keras3-1.1.0/keras3/man/op_cos.Rd                                              |   10 
 keras3-1.1.0/keras3/man/op_cosh.Rd                                             |   10 
 keras3-1.1.0/keras3/man/op_count_nonzero.Rd                                    |   10 
 keras3-1.1.0/keras3/man/op_cross.Rd                                            |   10 
 keras3-1.1.0/keras3/man/op_ctc_decode.Rd                                       |   16 
 keras3-1.1.0/keras3/man/op_ctc_loss.Rd                                         |    8 
 keras3-1.1.0/keras3/man/op_cumprod.Rd                                          |   10 
 keras3-1.1.0/keras3/man/op_cumsum.Rd                                           |   10 
 keras3-1.1.0/keras3/man/op_custom_gradient.Rd                                  |   12 
 keras3-1.1.0/keras3/man/op_depthwise_conv.Rd                                   |    8 
 keras3-1.1.0/keras3/man/op_det.Rd                                              |    9 
 keras3-1.1.0/keras3/man/op_diag.Rd                                             |   10 
 keras3-1.1.0/keras3/man/op_diagonal.Rd                                         |   10 
 keras3-1.1.0/keras3/man/op_diff.Rd                                             |   10 
 keras3-1.1.0/keras3/man/op_digitize.Rd                                         |   10 
 keras3-1.1.0/keras3/man/op_divide.Rd                                           |   10 
 keras3-1.1.0/keras3/man/op_divide_no_nan.Rd                                    |   10 
 keras3-1.1.0/keras3/man/op_dot.Rd                                              |   10 
 keras3-1.1.0/keras3/man/op_dtype.Rd                                            |only
 keras3-1.1.0/keras3/man/op_eig.Rd                                              |    9 
 keras3-1.1.0/keras3/man/op_eigh.Rd                                             |    9 
 keras3-1.1.0/keras3/man/op_einsum.Rd                                           |   10 
 keras3-1.1.0/keras3/man/op_elu.Rd                                              |    8 
 keras3-1.1.0/keras3/man/op_empty.Rd                                            |   10 
 keras3-1.1.0/keras3/man/op_equal.Rd                                            |   10 
 keras3-1.1.0/keras3/man/op_erf.Rd                                              |    8 
 keras3-1.1.0/keras3/man/op_erfinv.Rd                                           |    8 
 keras3-1.1.0/keras3/man/op_exp.Rd                                              |   10 
 keras3-1.1.0/keras3/man/op_expand_dims.Rd                                      |   10 
 keras3-1.1.0/keras3/man/op_expm1.Rd                                            |   10 
 keras3-1.1.0/keras3/man/op_extract_sequences.Rd                                |    8 
 keras3-1.1.0/keras3/man/op_eye.Rd                                              |   10 
 keras3-1.1.0/keras3/man/op_fft.Rd                                              |    8 
 keras3-1.1.0/keras3/man/op_fft2.Rd                                             |    8 
 keras3-1.1.0/keras3/man/op_flip.Rd                                             |   10 
 keras3-1.1.0/keras3/man/op_floor.Rd                                            |   10 
 keras3-1.1.0/keras3/man/op_floor_divide.Rd                                     |   10 
 keras3-1.1.0/keras3/man/op_fori_loop.Rd                                        |   12 
 keras3-1.1.0/keras3/man/op_full.Rd                                             |   10 
 keras3-1.1.0/keras3/man/op_full_like.Rd                                        |   10 
 keras3-1.1.0/keras3/man/op_gelu.Rd                                             |    8 
 keras3-1.1.0/keras3/man/op_get_item.Rd                                         |   10 
 keras3-1.1.0/keras3/man/op_greater.Rd                                          |   10 
 keras3-1.1.0/keras3/man/op_greater_equal.Rd                                    |   10 
 keras3-1.1.0/keras3/man/op_hard_sigmoid.Rd                                     |    8 
 keras3-1.1.0/keras3/man/op_hard_silu.Rd                                        |    8 
 keras3-1.1.0/keras3/man/op_hstack.Rd                                           |   10 
 keras3-1.1.0/keras3/man/op_identity.Rd                                         |   10 
 keras3-1.1.0/keras3/man/op_imag.Rd                                             |   10 
 keras3-1.1.0/keras3/man/op_image_affine_transform.Rd                           |   34 
 keras3-1.1.0/keras3/man/op_image_crop.Rd                                       |   39 
 keras3-1.1.0/keras3/man/op_image_extract_patches.Rd                            |   31 
 keras3-1.1.0/keras3/man/op_image_hsv_to_rgb.Rd                                 |only
 keras3-1.1.0/keras3/man/op_image_map_coordinates.Rd                            |   38 
 keras3-1.1.0/keras3/man/op_image_pad.Rd                                        |   41 
 keras3-1.1.0/keras3/man/op_image_resize.Rd                                     |   33 
 keras3-1.1.0/keras3/man/op_image_rgb_to_grayscale.Rd                           |   21 
 keras3-1.1.0/keras3/man/op_image_rgb_to_hsv.Rd                                 |only
 keras3-1.1.0/keras3/man/op_in_top_k.Rd                                         |    8 
 keras3-1.1.0/keras3/man/op_inv.Rd                                              |    9 
 keras3-1.1.0/keras3/man/op_irfft.Rd                                            |    8 
 keras3-1.1.0/keras3/man/op_is_tensor.Rd                                        |   12 
 keras3-1.1.0/keras3/man/op_isclose.Rd                                          |   18 
 keras3-1.1.0/keras3/man/op_isfinite.Rd                                         |   10 
 keras3-1.1.0/keras3/man/op_isinf.Rd                                            |   10 
 keras3-1.1.0/keras3/man/op_isnan.Rd                                            |   10 
 keras3-1.1.0/keras3/man/op_istft.Rd                                            |    8 
 keras3-1.1.0/keras3/man/op_leaky_relu.Rd                                       |    8 
 keras3-1.1.0/keras3/man/op_less.Rd                                             |   10 
 keras3-1.1.0/keras3/man/op_less_equal.Rd                                       |   10 
 keras3-1.1.0/keras3/man/op_linspace.Rd                                         |   10 
 keras3-1.1.0/keras3/man/op_log.Rd                                              |   10 
 keras3-1.1.0/keras3/man/op_log10.Rd                                            |   10 
 keras3-1.1.0/keras3/man/op_log1p.Rd                                            |   10 
 keras3-1.1.0/keras3/man/op_log2.Rd                                             |   10 
 keras3-1.1.0/keras3/man/op_log_sigmoid.Rd                                      |    8 
 keras3-1.1.0/keras3/man/op_log_softmax.Rd                                      |    8 
 keras3-1.1.0/keras3/man/op_logaddexp.Rd                                        |   10 
 keras3-1.1.0/keras3/man/op_logical_and.Rd                                      |   10 
 keras3-1.1.0/keras3/man/op_logical_not.Rd                                      |   10 
 keras3-1.1.0/keras3/man/op_logical_or.Rd                                       |   10 
 keras3-1.1.0/keras3/man/op_logical_xor.Rd                                      |   10 
 keras3-1.1.0/keras3/man/op_logspace.Rd                                         |   10 
 keras3-1.1.0/keras3/man/op_logsumexp.Rd                                        |    8 
 keras3-1.1.0/keras3/man/op_lstsq.Rd                                            |only
 keras3-1.1.0/keras3/man/op_lu_factor.Rd                                        |    9 
 keras3-1.1.0/keras3/man/op_map.Rd                                              |only
 keras3-1.1.0/keras3/man/op_matmul.Rd                                           |   10 
 keras3-1.1.0/keras3/man/op_max.Rd                                              |   10 
 keras3-1.1.0/keras3/man/op_max_pool.Rd                                         |    8 
 keras3-1.1.0/keras3/man/op_maximum.Rd                                          |   10 
 keras3-1.1.0/keras3/man/op_mean.Rd                                             |   10 
 keras3-1.1.0/keras3/man/op_median.Rd                                           |   10 
 keras3-1.1.0/keras3/man/op_meshgrid.Rd                                         |   10 
 keras3-1.1.0/keras3/man/op_min.Rd                                              |   10 
 keras3-1.1.0/keras3/man/op_minimum.Rd                                          |   10 
 keras3-1.1.0/keras3/man/op_mod.Rd                                              |   10 
 keras3-1.1.0/keras3/man/op_moments.Rd                                          |    8 
 keras3-1.1.0/keras3/man/op_moveaxis.Rd                                         |   10 
 keras3-1.1.0/keras3/man/op_multi_hot.Rd                                        |    8 
 keras3-1.1.0/keras3/man/op_multiply.Rd                                         |   10 
 keras3-1.1.0/keras3/man/op_nan_to_num.Rd                                       |   10 
 keras3-1.1.0/keras3/man/op_ndim.Rd                                             |   10 
 keras3-1.1.0/keras3/man/op_negative.Rd                                         |   10 
 keras3-1.1.0/keras3/man/op_nonzero.Rd                                          |   10 
 keras3-1.1.0/keras3/man/op_norm.Rd                                             |    9 
 keras3-1.1.0/keras3/man/op_normalize.Rd                                        |    8 
 keras3-1.1.0/keras3/man/op_not_equal.Rd                                        |   10 
 keras3-1.1.0/keras3/man/op_one_hot.Rd                                          |    8 
 keras3-1.1.0/keras3/man/op_ones.Rd                                             |   10 
 keras3-1.1.0/keras3/man/op_ones_like.Rd                                        |   10 
 keras3-1.1.0/keras3/man/op_outer.Rd                                            |   10 
 keras3-1.1.0/keras3/man/op_pad.Rd                                              |   10 
 keras3-1.1.0/keras3/man/op_power.Rd                                            |   10 
 keras3-1.1.0/keras3/man/op_prod.Rd                                             |   10 
 keras3-1.1.0/keras3/man/op_psnr.Rd                                             |    8 
 keras3-1.1.0/keras3/man/op_qr.Rd                                               |    8 
 keras3-1.1.0/keras3/man/op_quantile.Rd                                         |   10 
 keras3-1.1.0/keras3/man/op_ravel.Rd                                            |   10 
 keras3-1.1.0/keras3/man/op_real.Rd                                             |   10 
 keras3-1.1.0/keras3/man/op_reciprocal.Rd                                       |   10 
 keras3-1.1.0/keras3/man/op_relu.Rd                                             |    8 
 keras3-1.1.0/keras3/man/op_relu6.Rd                                            |    8 
 keras3-1.1.0/keras3/man/op_repeat.Rd                                           |   10 
 keras3-1.1.0/keras3/man/op_reshape.Rd                                          |   10 
 keras3-1.1.0/keras3/man/op_rfft.Rd                                             |    8 
 keras3-1.1.0/keras3/man/op_roll.Rd                                             |   10 
 keras3-1.1.0/keras3/man/op_round.Rd                                            |   10 
 keras3-1.1.0/keras3/man/op_rsqrt.Rd                                            |    8 
 keras3-1.1.0/keras3/man/op_scan.Rd                                             |only
 keras3-1.1.0/keras3/man/op_scatter.Rd                                          |   12 
 keras3-1.1.0/keras3/man/op_scatter_update.Rd                                   |   12 
 keras3-1.1.0/keras3/man/op_segment_max.Rd                                      |    8 
 keras3-1.1.0/keras3/man/op_segment_sum.Rd                                      |    8 
 keras3-1.1.0/keras3/man/op_select.Rd                                           |   10 
 keras3-1.1.0/keras3/man/op_selu.Rd                                             |    8 
 keras3-1.1.0/keras3/man/op_separable_conv.Rd                                   |    8 
 keras3-1.1.0/keras3/man/op_shape.Rd                                            |   12 
 keras3-1.1.0/keras3/man/op_sigmoid.Rd                                          |    8 
 keras3-1.1.0/keras3/man/op_sign.Rd                                             |   10 
 keras3-1.1.0/keras3/man/op_silu.Rd                                             |    8 
 keras3-1.1.0/keras3/man/op_sin.Rd                                              |   10 
 keras3-1.1.0/keras3/man/op_sinh.Rd                                             |   10 
 keras3-1.1.0/keras3/man/op_size.Rd                                             |   10 
 keras3-1.1.0/keras3/man/op_slice.Rd                                            |   12 
 keras3-1.1.0/keras3/man/op_slice_update.Rd                                     |   12 
 keras3-1.1.0/keras3/man/op_slogdet.Rd                                          |    9 
 keras3-1.1.0/keras3/man/op_softmax.Rd                                          |    8 
 keras3-1.1.0/keras3/man/op_softplus.Rd                                         |    8 
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Package filehashSQLite updated to version 0.2-7 with previous version 0.2-6 dated 2022-05-11

Title: Simple Key-Value Database using SQLite
Description: Simple key-value database using SQLite as the backend.
Author: Roger D. Peng <roger.peng@austin.utexas.edu>
Maintainer: Roger D. Peng <roger.peng@austin.utexas.edu>

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Package err (with last version 0.2.0) was removed from CRAN

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

2019-04-25 0.2.0
2018-10-28 0.0.1

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Package shiny.telemetry updated to version 0.3.0 with previous version 0.2.0 dated 2023-11-16

Title: 'Shiny' App Usage Telemetry
Description: Enables instrumentation of 'Shiny' apps for tracking user session events such as input changes, browser type, and session duration. These events can be sent to any of the available storage backends and analyzed using the included 'Shiny' app to gain insights about app usage and adoption.
Author: Andre Verissimo [aut, cre], Kamil Zyla [aut], Krystian Igras [aut], Recle Vibal [aut], Arun Kodati [aut], Wahaduzzaman Khan [aut], Appsilon Sp. z o.o. [cph]
Maintainer: Andre Verissimo <opensource+andre@appsilon.com>

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Package s2 updated to version 1.1.7 with previous version 1.1.6 dated 2023-12-19

Title: Spherical Geometry Operators Using the S2 Geometry Library
Description: Provides R bindings for Google's s2 library for geometric calculations on the sphere. High-performance constructors and exporters provide high compatibility with existing spatial packages, transformers construct new geometries from existing geometries, predicates provide a means to select geometries based on spatial relationships, and accessors extract information about geometries.
Author: Dewey Dunnington [aut] , Edzer Pebesma [aut, cre] , Ege Rubak [aut], Jeroen Ooms [ctb] , Google, Inc. [cph]
Maintainer: Edzer Pebesma <edzer.pebesma@uni-muenster.de>

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Package o2plsda updated to version 0.0.22 with previous version 0.0.18 dated 2022-08-12

Title: Multiomics Data Integration
Description: Provides functions to do 'O2PLS-DA' analysis for multiple omics data integration. The algorithm came from "O2-PLS, a two-block (X±Y) latent variable regression (LVR) method with an integral OSC filter" which published by Johan Trygg and Svante Wold at 2003 <doi:10.1002/cem.775>. 'O2PLS' is a bidirectional multivariate regression method that aims to separate the covariance between two data sets (it was recently extended to multiple data sets) (Löfstedt and Trygg, 2011 <doi:10.1002/cem.1388>; Löfstedt et al., 2012 <doi:10.1016/j.aca.2013.06.026>) from the systematic sources of variance being specific for each data set separately.
Author: Kai Guo [aut, cre], Junguk Hur [aut], Eva Feldman [aut]
Maintainer: Kai Guo <guokai8@gmail.com>

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Package treestats updated to version 1.70.4 with previous version 1.0.5 dated 2024-01-30

Title: Phylogenetic Tree Statistics
Description: Collection of phylogenetic tree statistics, collected throughout the literature. All functions have been written to maximize computation speed. The package includes umbrella functions to calculate all statistics, all balance associated statistics, or all branching time related statistics. Furthermore, the 'treestats' package supports summary statistic calculations on Ltables, provides speed-improved coding of branching times, Ltable conversion and includes algorithms to create intermediately balanced trees. Full description can be found in Janzen (2023) <doi:10.1101/2024.01.24.576848>.
Author: Thijs Janzen [cre, aut]
Maintainer: Thijs Janzen <thijsjanzen@gmail.com>

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More information about treestats at CRAN
Permanent link

Package SticsRFiles updated to version 1.4.0 with previous version 1.3.0 dated 2024-04-11

Title: Read and Modify 'STICS' Input/Output Files
Description: Manipulating input and output files of the 'STICS' crop model. Files are either 'JavaSTICS' XML files or text files used by the model 'fortran' executable. Most basic functionalities are reading or writing parameter names and values in both XML or text input files, and getting data from output files. Advanced functionalities include XML files generation from XML templates and/or spreadsheets, or text files generation from XML files by using 'xslt' transformation.
Author: Patrice Lecharpentier [aut, cre] , Remi Vezy [aut] , Samuel Buis [aut] , Michel Giner [aut] , Timothee Flutre [ctb], Thomas Robine [ctb], Amine Barkaoui [ctb], Patrick Chabrier [ctb], Julie Constantin [rev], Dominique Ripoche [rev], Marie Launay [rev [...truncated...]
Maintainer: Patrice Lecharpentier <patrice.lecharpentier@inrae.fr>

Diff between SticsRFiles versions 1.3.0 dated 2024-04-11 and 1.4.0 dated 2024-07-17

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Permanent link

Package bliss updated to version 1.1.1 with previous version 1.1.0 dated 2024-05-14

Title: Bayesian Functional Linear Regression with Sparse Step Functions
Description: A method for the Bayesian functional linear regression model (scalar-on-function), including two estimators of the coefficient function and an estimator of its support. A representation of the posterior distribution is also available. Grollemund P-M., Abraham C., Baragatti M., Pudlo P. (2019) <doi:10.1214/18-BA1095>.
Author: Paul-Marie Grollemund [aut, cre], Isabelle Sanchez [ctr], Meili Baragatti [ctr]
Maintainer: Paul-Marie Grollemund <paul_marie.grollemund@uca.fr>

Diff between bliss versions 1.1.0 dated 2024-05-14 and 1.1.1 dated 2024-07-17

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More information about bliss at CRAN
Permanent link

New package rplanes with initial version 0.1.0
Package: rplanes
Title: Plausibility Analysis of Epidemiological Signals
Version: 0.1.0
Description: Provides functionality to prepare data and analyze plausibility of both forecasted and reported epidemiological signals. The functions implement a set of plausibility algorithms that are agnostic to geographic and time resolutions and are calculated independently then presented as a combined score.
License: MIT + file LICENSE
URL: https://signaturescience.github.io/rplanes/
Depends: R (>= 2.10)
Imports: dplyr, dtw, ecp, lubridate, magrittr, purrr, readr, rlang, stringr, tibble, tidyr, utils
Suggests: DT, ggplot2, markdown, knitr, MMWRweek, rmarkdown, shiny, shinyjs, shinyWidgets, shinycssloaders, testthat (>= 3.0.0), tools
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2024-07-15 16:28:47 UTC; vpnagraj
Author: VP Nagraj [aut, cre] , Desiree Williams [aut], Amy Benefield [aut]
Maintainer: VP Nagraj <nagraj@nagraj.net>
Repository: CRAN
Date/Publication: 2024-07-17 10:50:02 UTC

More information about rplanes at CRAN
Permanent link

New package kmeRs with initial version 2.1.0
Package: kmeRs
Title: K-Mers Similarity Score Matrix and HeatMap
Version: 2.1.0
Description: Similarity Score Matrix and HeatMap for nucleic and amino acid k-mers. Similarity score is evaluated by Point Accepted Mutation (PAM) and BLOcks SUbstitution Matrix (BLOSUM). The 30, 40, 70, 120, 250 and 62, 45, 50, 62, 80, 100 matrix versions are available for PAM and BLOSUM, respectively. Alignment is evaluated by local and global alignment.
Depends: R (>= 3.4.0)
License: GPL-3
Encoding: UTF-8
URL: https://github.com/urniaz/kmeRs
BugReports: https://github.com/urniaz/kmeRs/issues
Imports: utils, stats, Biostrings, BiocGenerics, pwalign
Suggests: RColorBrewer, knitr, rmarkdown, unittest, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-07-16 00:04:12 UTC; urniaz
Author: Rafal Urniaz [aut, cre] , Jason Lin [ctb]
Maintainer: Rafal Urniaz <rafal.urniaz@cantab.net>
Repository: CRAN
Date/Publication: 2024-07-17 11:00:02 UTC

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New package charlesschwabapi with initial version 1.0.2
Package: charlesschwabapi
Title: Wrapper Functions Around 'Charles Schwab Individual Trader API'
Version: 1.0.2
Description: For those wishing to interact with the 'Charles Schwab Individual Trader API' (<https://developer.schwab.com/products/trader-api--individual>) with R in a simplified manner, this package offers wrapper functions around authentication and the available API calls to streamline the process.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: httr, lubridate, stringr, purrr, tidyr, anytime, dplyr, openssl
Suggests: testthat (>= 3.0.0), covr
NeedsCompilation: no
Packaged: 2024-07-16 00:43:48 UTC; njbul
Author: Nick Bultman [aut, cre, cph]
Maintainer: Nick Bultman <njbultman74@gmail.com>
Repository: CRAN
Date/Publication: 2024-07-17 11:00:05 UTC

More information about charlesschwabapi at CRAN
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Package LDAcoop updated to version 0.1.2 with previous version 0.1.1 dated 2023-10-09

Title: Analysis of Data from Limiting Dilution Assay (LDA) with or without Cellular Cooperation
Description: Cellular cooperation compromises the established method of calculating clonogenic activity from limiting dilution assay (LDA) data. This tool provides functions that enable robust analysis in presence or absence of cellular cooperation. The implemented method incorporates the same cooperativity module to model the non-linearity associated with cellular cooperation as known from the colony formation assay (Brix et al. (2021) <doi:10.1038/s41596-021-00615-0>: "Analysis of clonogenic growth in vitro." Nature protocols).
Author: Daniel Samaga [cre, aut], Nikko Brix [aut], Benedek Danko [aut], Kirsten Lauber [aut], Horst Zitzelsberger [aut]
Maintainer: Daniel Samaga <daniel.samaga@helmholtz-munich.de>

Diff between LDAcoop versions 0.1.1 dated 2023-10-09 and 0.1.2 dated 2024-07-17

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Package kissmig (with last version 1.0-4) was removed from CRAN

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

2022-06-01 1.0-4
2015-01-30 1.0-3

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Package fdaconcur (with last version 0.1.2) was removed from CRAN

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

2023-11-08 0.1.2
2023-09-06 0.1.1
2022-09-20 0.1.0

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Package sdm updated to version 1.2-46 with previous version 1.2-40 dated 2024-05-01

Title: Species Distribution Modelling
Description: An extensible framework for developing species distribution models using individual and community-based approaches, generate ensembles of models, evaluate the models, and predict species potential distributions in space and time. For more information, please check the following paper: Naimi, B., Araujo, M.B. (2016) <doi:10.1111/ecog.01881>.
Author: Babak Naimi, Miguel B. Araujo
Maintainer: Babak Naimi <naimi.b@gmail.com>

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Package MixSim updated to version 1.1-8 with previous version 1.1-7 dated 2023-09-05

Title: Simulating Data to Study Performance of Clustering Algorithms
Description: The utility of this package is in simulating mixtures of Gaussian distributions with different levels of overlap between mixture components. Pairwise overlap, defined as a sum of two misclassification probabilities, measures the degree of interaction between components and can be readily employed to control the clustering complexity of datasets simulated from mixtures. These datasets can then be used for systematic performance investigation of clustering and finite mixture modeling algorithms. Among other capabilities of 'MixSim', there are computing the exact overlap for Gaussian mixtures, simulating Gaussian and non-Gaussian data, simulating outliers and noise variables, calculating various measures of agreement between two partitionings, and constructing parallel distribution plots for the graphical display of finite mixture models.
Author: Volodymyr Melnykov [aut], Wei-Chen Chen [aut, cre], Ranjan Maitra [aut], Robert Davies [ctb] , Stephen Moshier [ctb] , Rouben Rostamian [ctb]
Maintainer: Wei-Chen Chen <wccsnow@gmail.com>

Diff between MixSim versions 1.1-7 dated 2023-09-05 and 1.1-8 dated 2024-07-17

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