Package: jmSurface
Title: Semi-Parametric Association Surfaces for Joint
        Longitudinal-Survival Models
Version: 0.1.0
Authors@R: person("Atanu", "Bhattacharjee", 
                  email = "atanustat@gmail.com",
                  role = c("aut", "cre"),
                  comment = c(ORCID = "0000-0002-5757-5513"))
Description: Implements interpretable multi-biomarker fusion in joint 
    longitudinal-survival models via semi-parametric association surfaces.
    Provides a two-stage estimation framework where Stage 1 fits mixed-effects 
    longitudinal models and extracts Best Linear Unbiased Predictors ('BLUP's), 
    and Stage 2 fits transition-specific penalized Cox models with 
    tensor-product spline surfaces linking latent biomarker summaries to 
    transition hazards. Supports multi-state disease processes with 
    transition-specific surfaces, Restricted Maximum Likelihood ('REML') 
    smoothing parameter selection, effective degrees of freedom ('EDF') 
    diagnostics, dynamic prediction of transition probabilities, and three 
    interpretability visualizations (surface plots, contour heatmaps, 
    marginal effect slices).
    Methods are described in Bhattacharjee (2025, under review).
License: GPL (>= 3)
Encoding: UTF-8
RoxygenNote: 7.3.3
Depends: R (>= 4.0.0)
Imports: nlme, survival, mgcv, stats, utils, graphics, grDevices
Suggests: lme4, ggplot2, viridis, plotly, shiny, shinydashboard, dplyr,
        tidyr, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-02-20 15:08:08 UTC; atanu
Author: Atanu Bhattacharjee [aut, cre] (ORCID:
    <https://orcid.org/0000-0002-5757-5513>)
Maintainer: Atanu Bhattacharjee <atanustat@gmail.com>
Repository: CRAN
Date/Publication: 2026-02-25 10:20:02 UTC
Built: R 4.6.0; ; 2026-04-26 03:59:39 UTC; unix
