tsForecastR/DESCRIPTION at master · xavierkamp/tsForecastR · GitHub

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Package: tsForecastR
Type: Package
Title: Forecasting with Traditional Time Series and Machine Learning Models
Version: 0.1.0
Author: Xavier Kamphaus
Maintainer: The package maintainer <yourself@somewhere.net>
Description: Functions and tools to facilitate the use of traditional time series
    and machine learning models to generate forecasts on univariate or multvariate
    data. To identify the best performing models, different backtesting scenarios
    are available.
Depends:
    R (>= 3.6.0)
Imports:
    bsts,
    doParallel,
    dplyr,
    foreach,
    forecast,
    h2o,
    imputeTS,
    lubridate,
    magrittr,
    parallel,
    plotly,
    purrr,
    stats,
    stringr,
    tibble,
    timeSeries,
    timetk,
    utils,
    xts,
    zoo
Suggests:
    keras,
    tensorflow,
    testthat (>= 2.1.0),
    covr
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2