Package: flowz
Type: Package
Title: Local Latent Flow Forecasting with Empirical Calibration
Version: 0.1.0
Authors@R: c(
    person(
      "Giancarlo", "Vercellino",
      email = "giancarlo.vercellino@gmail.com",
      role = c("aut", "cre")
    )
  )
Description: Fits conditional flow-matching models to univariate time series.
    Combines a selectable exponentially weighted moving average (EWMA),
    autoregressive integrated moving average (ARIMA), autoregressive
    fractionally integrated moving average (ARFIMA), or structural time-series
    baseline with direct multi-step residual paths and a random-feature extreme
    learning machine (ELM) velocity field. Spectral dispersion calibration uses
    a chronological calibration block, with a separate test block for forecast
    scoring. Provides simulated forecast paths and smooth marginal
    distributions. Methodological background is given by Lipman et al. (2023)
    <doi:10.48550/arXiv.2210.02747>, Huang et al. (2006)
    <doi:10.1016/j.neucom.2005.12.126>, Hyndman and Khandakar (2008)
    <doi:10.18637/jss.v027.i03>, and Haslett and Raftery (1989)
    <doi:10.2307/2347679>.
URL: https://rpubs.com/giancarlo_vercellino/flowz
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: forecast, fracdiff, graphics, grDevices, parallel, stats,
        utils
Suggests: testthat (>= 3.0.0), pkgload
Config/testthat/edition: 3
RoxygenNote: 7.3.3
NeedsCompilation: no
Packaged: 2026-10-08 10:23:30 UTC; gianc
Author: Giancarlo Vercellino [aut, cre]
Maintainer: Giancarlo Vercellino <giancarlo.vercellino@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-18 16:20:21 UTC
