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lvmPlot - Publication-Quality Diagrams for Latent Variable Models

Converts output from latent variable model tools into publication-ready path diagrams and model schematics. 'lavaan' fit objects and parameter tables are supported as a primary workflow, with graph adapters for objects from 'blavaan', 'lavaan.mi', 'semPlot', 'mirt', 'eRm', 'OpenMx', 'psych', 'poLCA', 'mclust', 'flexmix', 'lcmm', 'tidyLPA', and 'MplusAutomation' workflows when those packages are available. Supports structural equation and confirmatory factor analysis diagrams, multilevel structural equation models, growth models, higher-order factor models, latent class and profile models, item response theory models, and common mixture outputs through a unified graph grammar with model-aware defaults, geometry diagnostics, layout quality scoring, automatic layout selection, customizable publication styles, 'RStudio' preview, SVG/PDF/PNG export, 'TikZ' output, and reproducible publication bundles. A local 'Shiny' editor supports mouse dragging of nodes and coefficient labels, synchronized figure downloads, and reusable editing state.

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3.48 score 328 downloads

neuralnetwork - Fast Compact Multilayer Perceptrons

A small multilayer perceptron implementation for 'R'. It supports regression and classification, multiple hidden layers, mini-batch training, adaptive moment estimation, stochastic gradient descent, momentum, Nesterov acceleration, resilient backpropagation and limited-memory quasi-Newton optimization, dropout, squared-weight regularization, early stopping, convergence thresholds, gradient clipping, sample and class weights, callback hooks, target scaling and robust Huber loss for regression, 'Rcpp' forward-pass kernels, formula interfaces, model evaluation with balanced classification metrics, cross-validation, compact tuning, permutation importance, model persistence helpers, and standard prediction methods. Methods follow Rumelhart, Hinton and Williams (1986) <doi:10.1038/323533a0>, with optimizers including Riedmiller and Braun (1993) <doi:10.1109/ICNN.1993.298623>, Nocedal (1980) <doi:10.1090/S0025-5718-1980-0572855-7>, and Kingma and Ba (2014) <doi:10.48550/arXiv.1412.6980>.

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cpp

3.18 score 1 scripts 295 downloads

IJSE - Infinitesimal Jackknife Standard Errors for 'brms' Models

Provides a function to calculate infinite-jackknife-based standard errors for fixed effects parameters in 'brms' models, handling both clustered and independent data. References: Ji et al. (2024) <doi:10.48550/arXiv.2407.09772>; Giordano et al. (2024) <doi:10.48550/arXiv.2305.06466>.

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1.00 score 4 scripts 243 downloads