Stationarity - First Examples...White Noise and Random Walks

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Skills You'll Learn

Time Series Forecasting, Time Series, Time Series Models

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4.6 (645 ratings)
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RS

Mar 18, 2018

Really great lectures and clearly explaining the concepts and complicated models. In my opinion, a bit of practical applications of these models on Panel Data should be included.

MS

Feb 28, 2018

I have not completed the course yet, working on week 5. If you have some Math background, this course gives a good practical introduction to Time Series Analysis. I recommend it.

From the lesson
Week 3: Stationarity, MA(q) and AR(p) processes
In Week 3, we introduce few important notions in time series analysis: Stationarity, Backward shift operator, Invertibility, and Duality. We begin to explore Autoregressive processes and Yule-Walker equations.

Taught By

  • Tural Sadigov

    Tural Sadigov

    Lecturer
  • William Thistleton

    William Thistleton

    Associate Professor

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