Package: cusna
Type: Package
Title: Native GPU-Accelerated Simulation and Estimation of Network
        Models
Version: 0.1.0
Authors@R: person("Artem", "Maltsev", email = "MaltsevSNA@proton.me",
    role = c("aut", "cre"))
Author: Artem Maltsev [aut, cre]
Maintainer: Artem Maltsev <MaltsevSNA@proton.me>
Description: A self-contained native engine (a C interface over 'CUDA'
    kernels and C++ host logic) for stochastic actor-oriented models (the
    model family of 'RSiena'), exponential random graph models
    (cross-sectional, temporal, and separable temporal), and models for
    binary actor attributes, callable from R without a Python runtime.
    Modelled on the 'torch' package: the CRAN build is CPU-only from
    source; the GPU path is compiled from source when a 'CUDA' toolkit is
    detected at configure time. The data preparation, host statistics
    ('RSiena' Appendix B conventions), and moment targets are validated
    bit-for-bit against the reference implementation and reproduce 'RSiena'
    targets on public datasets to machine precision; the estimators match
    'RSiena', 'ergm', 'btergm', and 'tergm' on public benchmark models.
License: MIT + file LICENSE
URL: https://github.com/artemmaltsev74-techcom/cusna
BugReports: https://github.com/artemmaltsev74-techcom/cusna/issues
Encoding: UTF-8
SystemRequirements: C++17; optionally a CUDA 12.x toolkit (nvcc) for
        the GPU path
LinkingTo: cpp11
Imports: stats, utils
Suggests: testthat (>= 3.0.0), jsonlite, litedown, RSiena (>= 1.4)
VignetteBuilder: litedown
Config/testthat/edition: 3
NeedsCompilation: yes
Packaged: 2026-07-06 18:18:28 UTC; Artem
Repository: CRAN
Date/Publication: 2026-07-15 18:10:15 UTC
Built: R 4.6.1; x86_64-w64-mingw32; 2026-07-15 23:51:12 UTC; windows
Archs: x64
