Package: sparseSEM 4.1

Anhui Huang

sparseSEM: Elastic Net Penalized Maximum Likelihood for Structural Equation Models with Network GPT Framework

Provides elastic net penalized maximum likelihood estimator for structural equation models (SEM). The package implements `lasso` and `elastic net` (l1/l2) penalized SEM and estimates the model parameters with an efficient block coordinate ascent algorithm that maximizes the penalized likelihood of the SEM. Hyperparameters are inferred from cross-validation (CV). A Stability Selection (STS) function is also available to provide accurate causal effect selection. The software achieves high accuracy performance through a `Network Generative Pre-trained Transformer` (Network GPT) Framework with two steps: 1) pre-trains the model to generate a complete (fully connected) graph; and 2) uses the complete graph as the initial state to fit the `elastic net` penalized SEM.

Authors:Anhui Huang [aut, ctb, cre]

sparseSEM_4.1.tar.gz
sparseSEM_4.1.tar.gz(r-4.7-arm64)sparseSEM_4.1.tar.gz(r-4.7-x86_64)sparseSEM_4.1.tar.gz(r-4.6-arm64)sparseSEM_4.1.tar.gz(r-4.6-x86_64)
sparseSEM_4.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
sparseSEM/json (API)

# Install 'sparseSEM' in R:
install.packages('sparseSEM', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS
Datasets:
  • B - True network edges
  • Missing - Missing Network Node dependent variable data
  • X - Genotype matrix
  • X - Genotype matrix
  • Y - Gene expression matrix
  • Y - Gene expression matrix

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblas

3.30 score 20 scripts 620 downloads 7 exports 0 dependencies

Last updated from:d46e74d47a. Checks:4 WARNING, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64WARNING117
linux-devel-x86_64WARNING150
source / vignettesOK186
linux-release-arm64WARNING131
linux-release-x86_64WARNING114
wasm-releaseOK96

Exports:elasticNetSEMelasticNetSEMcvelasticNetSEMpointenSEM_stability_selectionenSEM_stability_selection_parallelenSEM_STSlassoSEM

Dependencies:

Elastic Net Enabled Sparse-Aware Maximum Likelihood for Structural Equation Models in Inferring Gene Regulatory Networks
Summary | Key Words: | Introduction | Methods | Sparse SEM model for gene regulatory networks | Structural equation models with adaptive elastic net penalty (SEM-EN) | Software implementation | Simulation study and real data analysis | Results | Simulation study | Inference of the yeast GRN | Discussion | References
Rendered fromsparseSEM.Rmdusingknitr::rmarkdown

Last update: 2023-08-09
Started: 2023-04-21

Elastic Net Penalized Structural Equation Models
Introduction | simulated network | Yeast Gene Regulatory Network (GRN) | Quick Start | Cross Validation (CV) | Stability Selection (STS) | Yeast GRN | References
Rendered fromNetwork-Inference-via-sparseSEM.Rmdusingknitr::rmarkdown

Last update: 2023-08-09
Started: 2023-06-11