Package: ORIONZ.G 1.0.1

David Navarro-Gonzalez

ORIONZ.G: EAP Scoring in Exploratory FA Solutions with Correlated Residuals

Obtaining Bayes Expected A Posteriori (EAP) individual score estimates based on linear and non-linear extended Exploratoy Factor Analysis solutions that include a correlated-residual structure.

Authors:David Navarro-Gonzalez [aut, cre], Urbano Lorenzo-Seva [aut], Pere J. Ferrando [aut]

ORIONZ.G_1.0.1.tar.gz
ORIONZ.G_1.0.1.tar.gz(r-4.5-noble)ORIONZ.G_1.0.1.tar.gz(r-4.4-noble)
ORIONZ.G_1.0.1.tgz(r-4.4-emscripten)ORIONZ.G_1.0.1.tgz(r-4.3-emscripten)
ORIONZ.G.pdf |ORIONZ.G.html✨
ORIONZ.G/json (API)

# Install 'ORIONZ.G' in R:
install.packages('ORIONZ.G', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:

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

    11 exports 0.00 score 0 dependencies 371 downloads

    Last updated 2 months agofrom:8a14fc53c9. Checks:OK: 2. Indexed: yes.

    TargetResultDate
    Doc / VignettesOKAug 27 2024
    R-4.5-linuxOKAug 27 2024

    Exports:discreBeap_grad_oblieapcondefNserieskordnormultiORIONzpgradreap_grad_oblirelicorrecsizetranspose

    Dependencies: