Modeltime unlocks time series forecast models and machine learning in one framework

R package to accompany Time Series Analysis and Its Applications: With R Examples -and- Time Series: A Data Analysis Approach Using R

R Shiny app to compare the relative performance of cryptos and equities.

{mvgam} R 📦 to fit Dynamic Bayesian Generalized Additive Models for multivariate modeling and forecasting

TSrepr: R package for time series representations

A framework to infer causality on a pair of time series of real numbers based on Variable-lag Granger causality and transfer entropy.

Forecasting with H2O AutoML. Use the H2O Automatic Machine Learning algorithm as a backend for Modeltime Time Series Forecasting.

Code for the paper "Estimating Transfer Entropy via Copula Entropy"

Field observation quick analysis toolkit

An R package for clustering longitudinal datasets in a standardized way, providing interfaces to various R packages for longitudinal clustering, and facilitating the rapid implementation and evaluation of new methods

COVID-19 spread shiny dashboard with a forecasting model, countries' trajectories graphs, and cluster analysis tools

CRAN Task View: Time Series Analysis

A time-series companion package to healthyR

Course Material: Business Analytics and Decision Support with R

A tool for analyzing and visualizing discrete temporal events

códigos e arquivos do livro Análise de Séries Temporais em R: um curso introdutório.

ForeCA: Forecastable Component Analysis in R

Solutions to the problems in Time Series Analysis with Applications in R

StAtistical Models for the UnsupeRvised segmentAion of tIme-Series

Analyzing the safety (311) dataset published by Azure Open Datasets for Chicago, Boston and New York City using SparkR, SParkSQL, Azure Databricks, visualization using ggplot2 and leaflet. Focus is on descriptive analytics, visualization, clustering, time series forecasting and anomaly detection.