an R package for structural equation modeling and more
-
Updated
May 16, 2024 - R
an R package for structural equation modeling and more
Code that might be useful to others for learning/demonstration purposes, specifically along the lines of modeling and various algorithms. **Superseded by the models-by-example repo**.
An R package for Bayesian structural equation modeling
Market Mix Modelling for an eCommerce firm to estimate the impact of various marketing levers on sales
Descriptive probabilistic marker gene approach to single-cell pseudotime inference
Inference for Gaussian copula factor models and its application to causal discovery.
PCA, Factor Analysis, CCA, Sparse Covariance Matrix Estimation, Imputation, Multiple Hypothesis Testing
Case Study in ranking U.S. cities based on a single linear combination of rating variables. Dimensionality techniques used in the analysis are Principal Component Analysis (PCA), Factor Analysis (FA), Canonical Correlation Analysis (CCA)
Infinite Mixtures of Infinite Factor Analysers
Probabilistic inference of single-cell bifurcations
# kaefa kwangwoon automated exploratory factor analysis for improving research capability to identify unexplained factor structure with complexly cross-classified multilevel structured data in R environment
An R package for Bayesian structural equation models that account for the influence of minor factors
Alternating minimization approach to factor analysis
A lavaan-like syntax for structural equation models with OpenMx
R package for penalized factor analysis via trust-region algorithm and automatic multiple tuning parameter selection
We conduct simulation studies on dynamic factor analysis using maximum-likelihood and principal-component estimators.
An R package providing multiple Imputation of covariance matrices in order to perform factor analysis.
Add a description, image, and links to the factor-analysis topic page so that developers can more easily learn about it.
To associate your repository with the factor-analysis topic, visit your repo's landing page and select "manage topics."