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.

Univariate Time Series Forecasting

An engine for univariate time series forecasting using different regression models in an autoregressive way. The engine provides an uniform interface for applying the different models. Furthermore, it is extensible so that users can easily apply their own regression models to univariate time series forecasting and benefit from all the features of the engine, such as preprocessings or estimation of forecast accuracy.

Time Series Cointegrated System

A set of functions to implement Time Series Cointegrated System (TSCS) spatial interpolation and relevant data visualization.

Raster Time Series Visualization

A lightweight 'R' package to visualize large raster time series, building on a fast temporal interpolation core.

A Gui for Simulating Time Series

This gui shows realisations of times series, currently ARMA and GARCH processes. It might be helpful for teaching and studying.