Webinar on Time Series Econometrics with R: Theory, Application and Computing

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Summary

1st Chapter: The Concept of Time Series

Definition, data type, purpose, plots, trends, and seasonal variation, decomposition of series, models, estimating trends and seasonal effects, smoothing, applications using R.

2nd Chapter: Correlation

Purpose, Expectation and the Ensemble: expected value, the ensemble and stationarity, ergodic series, variance function, autocorrelation, the correlogram: general discussion, and illustrative examples, covariance of sums of random variables, examples in real-life situation. 

3rd Chapter: Forecasting Strategies

Purpose, Leading variables and associated variables, Bass models: exponential smoothing and the Holt-Winters method. Application using R language. 

4th Chapter: Basic Stochastic Models

Purpose, white noise, random walk, fitted models and diagnostic plots, autoregressive models and applications in real-world using R language.