Package: MEMWAS
Type: Package
Title: Mixed-Effects Models with Autocorrelation Structures
Version: 0.9.5
Date: 2026-08-20
Authors@R: c(
    person("Enoch", "Kang", role = c("aut", "cre", "trl"),
           email = "y.enoch.kang@gmail.com",
           comment = c(ORCID = "0000-0002-4903-942X"))
    )
Description: Fits longitudinal mixed-effects models through a registered 'C++' 
    numerical backend. Supported serial covariance structures include first-order
    autoregressive (AR(1)), exponential or Ornstein-Uhlenbeck, higher-order 
    autoregressive (AR(p)), first-order autoregressive moving-average (ARMA(1,1)), 
    compound symmetry, Toeplitz, and unstructured covariance. Serial processes 
    can be unified or attached independently to numeric predictor loadings. 
    Candidate temporal structures can be ranked on a common sample by 
    dependence-component grouped cross-validation, the Akaike information 
    criterion, the Bayesian information criterion, or log-likelihood. Clustered, 
    crossed, and nested random intercepts and slopes are assembled jointly with 
    diagonal or term-specific unstructured covariance. Available approximation 
    methods include Laplace, saddlepoint likelihood with latent Laplace 
    integration, adaptive Gaussian quadrature, full-covariance Gaussian variational
    inference, and penalized quasi-likelihood. Penalized smooth mean terms 
    include ordinary and cyclic P-splines, factor-by and varying-coefficient terms, 
    tensor products, shrinkage smooths, and whole-term selection. Term-specific 
    penalties, grouped fold-local smoothing selection, null-space 
    constraints, and smooth effective degrees of freedom remain separate from 
    elastic-net coefficient shrinkage while the smooth mean and serial covariance 
    are fitted jointly. Bootstrap resampling preserves the declared dependence
    components. The mixed-effects framework is inspired by Laird and Ware (1982)
    <doi:10.2307/2529876>; generalized-model approximations are inspired by 
    Breslow and Clayton (1993) <doi:10.1080/01621459.1993.10594284>; and serial 
    covariance formulations are inspired by Pinheiro and Bates (2000) 
    <doi:10.1007/b98882>. The run-time fitting interface imports no third-party 
    'R' packages.
License: GPL (>= 3)
Depends: R (>= 4.1.0)
Imports: stats, utils
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
NeedsCompilation: yes
Config/roxygen2/version: 8.0.0
VignetteBuilder: knitr, rmarkdown
Config/testthat/edition: 3
Language: en-US
Encoding: UTF-8
Packaged: 2026-08-22 14:51:59 UTC; KYN
Author: Enoch Kang [aut, cre, trl] (ORCID:
    <https://orcid.org/0000-0002-4903-942X>)
Maintainer: Enoch Kang <y.enoch.kang@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-22 15:40:02 UTC
Built: R 4.6.1; aarch64-apple-darwin23; 2026-08-22 18:51:59 UTC; unix
Archs: MEMWAS.so.dSYM
