ONLINE COURSE – Introduction to Time Series Analysis using R and Rstudio (ITSA02)
https://www.prstats.org/course/introduction-to-time-series-analysis-using-r-and-rstudio-itsa02/ Please feel free to share! 6th - 8th February 2024 COURSE DETAILS - In this three-day course, we provide a comprehensive practical and theoretical introduction to time series analysis and forecasting methods using R. Forecasting tools are useful in many areas, such as finance, meteorology, ecology, public policy, and health. We start by introducing the concepts of time series and stationarity, which will help us when studying ARIMA-type models. We will also cover autocorrelation functions and series decomposition methods. Then, we will introduce benchmark forecasting methods, namely the naïve (or random walk) method, mean, drift, and seasonal naïve methods. After that, we will present different exponential smoothing methods (simple, Holt’s linear method, and Holt-Winters seasonal method). Finally, we will cover autoregressive integrated moving-average (or ARIMA) models, with and without seasonality. If time allows, we will introduce regression with ARIMA errors. Please email oliverhoo...@prstatistics.com with any questions. -- Oliver Hooker PhD. PR statistics [[alternative HTML version deleted]] _______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
