Multivariate Time Series Plot

A function for plotting multivariate time series data.

Time Series Costationarity Determination

Contains functions that can determine whether a time series is second-order stationary or not (and hence evidence for locally stationarity). Given two non-stationary series (i.e. locally stationary series) this package can then discover time-varying linear combinations that are second-order stationary. Cardinali, A. and Nason, G.P. (2013) .

Time Series Analysis 'OpenBudgets.eu'

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.

From Time Series to Networks

Transforming one or multiple time series into networks. This package is useful for complex systems modeling, time series data mining, or time series analysis using networks. An introduction to the topic and the descriptions of the methods implemented in this package can be found in Mitchell (2006) , Silva and Zhao (2016) , and Silva et al. (2021) .

Brazilian Economic Time Series

It provides access to and information about the most important Brazilian economic time series - from the Getulio Vargas Foundation < http://portal.fgv.br/en>, the Central Bank of Brazil < http://www.bcb.gov.br> and the Brazilian Institute of Geography and Statistics < http://www.ibge.gov.br>. It also presents tools for managing, analysing (e.g. generating dynamic reports with a complete analysis of a series) and exporting these time series.

Interactive Time Series Visualizations

Create interactive time series visualizations. 'linevis' includes an extensive API to manipulate time series after creation, and supports getting data out of the visualization. Based on the 'timevis' package and the 'vis.js' Timeline 'JavaScript' library < https://visjs.github.io/vis-timeline/docs/graph2d/>.

Ordinal Time Series Analysis

An implementation of several functions for feature extraction in ordinal time series datasets. Specifically, some of the features proposed by Weiss (2019) can be computed. These features can be used to perform inferential tasks or to feed machine learning algorithms for ordinal time series, among others. The package also includes some interesting datasets containing financial time series. Practitioners from a broad variety of fields could benefit from the general framework provided by 'otsfeatures'.

Time Series, Analysis and Application

Accompanies the book Rainer Schlittgen and Cristina Sattarhoff (2020) < https://www.degruyter.com/view/title/575978> "Angewandte Zeitreihenanalyse mit R, 4. Auflage" . The package contains the time series and functions used therein. It was developed over many years teaching courses about time series analysis.

Probabilistic Time Series Forecasting

Probabilistic time series forecasting via Natural Gradient Boosting for Probabilistic Prediction.

Hydro-Meteorology Time-Series

Functions for the management and treatment of hydrology and meteorology time-series stored in a 'Sqlite' data base.