Authors@R: c(person("Gianluca", "Campanella", role=c("aut", "cre"),
Description: Implements the Time Machine, a simulation approach for
Author: Gianluca Campanella [aut, cre], Marc Chadeau-Hyam [aut], Maria

Description: Implements the Time Machine, a simulation approach for stochastic

Description: Extract useful time components of a date object, such as
day of week, weekend, holiday, day of month, etc, and put it in
a data frame.  This can be used to create many predictor
variables out of a single time variable, which can then be used

in a regression or decision tree.  Also includes function
plotCalendarHeatmap which draws a calendar and overlays a
Suggests: testthat, roxygen2, ggplot2, plyr

Title: Time Series Analysis 'OpenBudgets'
Description: Estimate and return the needed parameters for visualisations designed for 'OpenBudgets' <http://openbudgets.eu/> time series data. Calculate time series model and forecast parameters in Budget time series data of municipalities across Europe, according to the 'OpenBudgets' data model. There are functions for measuring deterministic and stochastic trend of the input time series data, decomposing with local regression models or seasonal trend decomposition, modelling the appropriate auto regressive integrated moving average model and provide forecasts for the input 'OpenBudgets' time series fiscal data. Also, can be used generally to extract visualisation parameters convert them to 'JSON' format and use them as input in a different graphical interface.
person("Kleanthis", "Koupidis", email = "koupidis@okfn.gr", role = c("aut", "cre")),
person("Charalampos", "Bratsas",  email = "charalampos.bratsas@okfn.org", role = "aut")
Imports: forecast, locfit, jsonlite, stats, trend, tseries
Packaged: 2018-01-19 22:44:35 UTC; Kleanthis-Okf

Title: Time Series Analysis 'OpenBudgets.eu'
Description: Estimate and return the needed parameters for visualizations designed for 'OpenBudgets.eu' <http://openbudgets.eu/> time series data. Calculate time series model and forecast parameters in budget time series data of municipalities across Europe, according to the 'OpenBudgets.eu' data model. There are functions for measuring deterministic and stochastic trend of the input time series data with 'ACF', 'PACF', 'Phillips Perron' test, 'Augmented Dickey Fuller (ADF)' test, 'Kwiatkowski-Phillips-Schmidt-Shin (KPSS)' test, 'Mann Kendall' test for monotonic trend and 'Cox and Stuart' trend test, decomposing with local regression models or 'stl' decomposition, fitting the appropriate 'arima' model and provide forecasts for the input 'OpenBudgets.eu' time series fiscal data. Also, can be used generally to extract visualization parameters convert them to 'JSON' format and use them as input in a different graphical interface.
Imports: devtools, forecast, locfit, jsonlite, stats, trend, tseries