The slcm package (CRAN, GitHub) provides an implementation of the exploratory Sparse Latent Class Model (SLCM) for Binary Data described by Chen, Y., Culpepper, S. A., and Liang, F. (2020). The package contains a new implementation of the paper’s proposed model. The original authors’ implementation may be found in the inst/ folder of the package
For more information, please see the full NEWS release below.
slcm news file entry for version 0.
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With the quarto-webr extension, we’re seeking to extend the popular language agnostic document creation tool quarto to take advantage of the online version of R powered by webR. The extension provides the ability to add webR-enabled code cells directly into a Quarto HTML document that allows a fair amount of R code to be run from a web browser without the user setting up any environment.
quarto-webr news file entry for version 0.
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The macrtools (Website) package lowers the barrier of entry for R developers who work on macOS that want to incorporate compiled code on macOS. The package provides an interface in native R to install and configure software libraries required for development on macOS.
That being said, you may be wondering:
Why not a macOS installer package (.pkg) or Apple Disk Image (.dmg) ?
We previously wrote two very successful installer packages ( r-macos-rtools and r-macos-clang).
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The {bibtex} R allows for BibTeX bibliographies to be imported into R.
Within this release, we revive the {bibtex} originally written by Romain François! Previously, the package was orphaned on CRAN when the memory check tests were enabled for the first time. These checks identified various low-level leaks in the package’s use of R’s C API. After a few years, the task of addressing these errors quickly faded. There was a notable effort by Matt Wiese (GitHub) in PR #40.
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The RcppEnsmallen package brings to R a Header-Only C++ Mathematical Optimization Library for Armadillo. In particular, Ensmallen is a templated C++ mathematical optimization library (by the MLPACK team) that provides a simple set of abstractions for writing an objective function to optimize.
In the second update of 2022, the Ensmallen Development Team has focused on adding new optimizers to the underlying package. Newly added optimizers are: AdaBelief, AdaSqrt, Yogi, DemonSGD, and DemonAdam.
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The ohoegdm package (CRAN, GitHub) is home to the implementation of ordinal exploratory Higher-order General Diagnostic Model (OHOEGDM) for Polytomous Data described by Culpepper and Balamuta (In Press). Through a focus on polytomous items with two or more response options, ohoegdm provides a novel method for inferring the latent structure using a higher-order model to describe dependence among the discrete latent attributes.
For more information, please see the full NEWS release below.
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The cIRT package (CRAN, GitHub) is home to the implementation of Choice Item Response Theory (cIRT) described by Culpepper and Balamuta (2015). cIRT jointly models the accuracy of cognitive responses and item choices within a bayesian hierarchical framework.
Wow, when time flies, it really flies! Today, we’re updating cIRT for the first time in almost 2 years. Moreover, it’s been about six years since the package was first listed on CRAN!
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The RcppEnsmallen package brings to R a Header-Only C++ Mathematical Optimization Library for Armadillo. In particular, Ensmallen is a templated C++ mathematical optimization library (by the MLPACK team) that provides a simple set of abstractions for writing an objective function to optimize.
The first update of 2022 for the ensmallen library has been released by the Ensmallen Development Team. The release contains a minor bug fix for displaying timing output and an update to the underlying C++ unit testing framework.
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The RcppEnsmallen package brings to R a Header-Only C++ Mathematical Optimization Library for Armadillo. In particular, Ensmallen is a templated C++ mathematical optimization library (by the MLPACK team) that provides a simple set of abstractions for writing an objective function to optimize.
Potentially the last update of 2021 for the ensmallen library has been released by the Ensmallen Development Team. The main benefit of this patch is fixing CMAES implementation to prevent an infinite loop.
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The RcppEnsmallen package brings to R a Header-Only C++ Mathematical Optimization Library for Armadillo. In particular, Ensmallen is a templated C++ mathematical optimization library (by the MLPACK team) that provides a simple set of abstractions for writing an objective function to optimize.
The fall update of the ensmallen library has been released by the Ensmallen Development Team. Within this release, we see improvements to gradient stability with the inclusion of a gradient clipping and norm scaling callback based on “On the difficulty of training Recurrent Neural Networks” by Razvan Pascanu, Tomas Mikolov, Yoshua Bengio.
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