A Julia package for fitting (statistical) mixed-effects models
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Updated
Aug 2, 2024 - Julia
A Julia package for fitting (statistical) mixed-effects models
Bayesian network analysis in R
RCall support for MixedModels.jl and lme4
Combining tree-boosting with Gaussian process and mixed effects models
A meta-analysis package for R
Featured Nonlinear Mixed effects Models
CRAN Task View: Mixed, Multilevel, and Hierarchical Models in R
Julia package for fitting mixed-effects models with flexible random/repeated covariance structure.
Python package customizing nested cross validation for tabular data.
Multivariate Time series interpolation using hierarchical mixed effects models.
PSM - Population Stochastic Modelling
Tools for multiple imputation in multilevel modeling
R package for Bayesian measurement invariance assessment using mixed effects and shrinkage.
R Package for fitting latent multivariate mixed effects location scale models.
Hierarchical modeling in TensorFlow layers
R package providing utilities for INLA
Generic curve fitting package with nonlinear mixed effects model
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