Package: elcf4R
Title: Electricity Load Curves Forecasting at Individual Level
Version: 0.4.2
Date: 2026-05-26
Depends: R (>= 3.5.0)
Imports: stats, utils, mgcv, earth, keras3, Rcpp, tensorflow,
        data.table, wavelets, jsonlite, xml2, DBI, RSQLite
LinkingTo: Rcpp
Suggests: knitr, reticulate, rmarkdown, testthat (>= 3.0.0)
Authors@R: c(
	person(given = "Frederic", family= "Bertrand", role = c("cre", "aut"), email = "frederic.bertrand@lecnam.net", comment = c(ORCID = "0000-0002-0837-8281")),
	person(given = "Fatima", family= "Fahs", role = c("aut"), email = "fatima.fahs@es.fr"),
	person(given = "Myriam", family= "Maumy-Bertrand", role = c("aut"), email = "myriam.maumy@ehesp.fr", comment = c(ORCID = "0000-0002-4615-1512")))
Author: Frederic Bertrand [cre, aut] (ORCID:
    <https://orcid.org/0000-0002-0837-8281>),
  Fatima Fahs [aut],
  Myriam Maumy-Bertrand [aut] (ORCID:
    <https://orcid.org/0000-0002-4615-1512>)
Maintainer: Frederic Bertrand <frederic.bertrand@lecnam.net>
Description: Implements forecasting methods for individual electricity load
    curves, including Kernel Wavelet Functional (KWF), clustered KWF,
    Generalized Additive Models (GAM), Multivariate Adaptive Regression
    Splines (MARS), and Long Short-Term Memory (LSTM) models. Provides
    normalized dataset adapters for iFlex, StoreNet, Smart-Grid Smart-City,
    Low Carbon London, and REFIT; download and read support for IDEAL and GX;
    explicit Python backend selection for TensorFlow-based LSTM fits; helpers
    for daily segmentation and rolling-origin benchmarking; and compact
    shipped example panels and benchmark-result datasets.
LazyLoad: yes
LazyData: yes
VignetteBuilder: knitr
License: GPL-3
Encoding: UTF-8
URL: https://fbertran.github.io/elcf4R/,
        https://github.com/fbertran/elcf4R
BugReports: https://github.com/fbertran/elcf4R/issues
RoxygenNote: 7.3.3
NeedsCompilation: yes
Packaged: 2026-05-26 17:00:18 UTC; bertran7
Repository: CRAN
Date/Publication: 2026-05-26 17:40:02 UTC
Built: R 4.5.3; x86_64-w64-mingw32; 2026-06-27 03:58:39 UTC; windows
Archs: x64
