Package: timesift
Title: Learn Predictive Representations of Time-Varying Data
Version: 0.3.0
Authors@R:
    person("Gilles", "Colling", email = "gilles.colling051@gmail.com",
           role = c("aut", "cre", "cph"),
           comment = c(ORCID = "0000-0003-3070-6066"))
Description: Fits and compares representations of time-varying data against a
    prediction target. Given a table of targets and a table of time-stamped
    series belonging to them, it builds each candidate representation, from the
    record unreduced through a calendar grain such as a week or a month to a
    lookback anchored on each target, fits the requested learners on
    each, scores every candidate on one set of held-out folds, and stacks the
    out-of-fold predictions into an ensemble. Calendar-aware binning keeps a bin
    a real week or month rather than a fixed block of hours. Learners, response
    heads and metrics are registered rather than hard-coded, so adding one is a
    registration and not a fork of the fitting code. The shipped default is
    presence-absence with a joint multi-label head scored by the true skill
    statistic, the setting used for species distribution modelling from
    microclimate loggers.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-GB
Roxygen: list(markdown = TRUE)
URL: https://gillescolling.com/timesift/, https://github.com/gcol33/timesift
BugReports: https://github.com/gcol33/timesift/issues
Depends: R (>= 4.1)
LinkingTo:
    cpp11
Imports:
    grDevices,
    graphics,
    rlang,
    stats,
    tidyselect (>= 1.2.0),
    tools,
    utils
Suggests:
    testthat (>= 3.0.0),
    torch,
    glmnet,
    ranger,
    lme4,
    lmerTest,
    emmeans,
    knitr,
    rmarkdown,
    spelling,
    withr
VignetteBuilder: knitr
Config/testthat/edition: 3
Config/roxygen2/version: 8.1.0
