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Time Series Analysis, Lecture 16: Seasonal ARIMA Models

Cache Lack Math & Stats Lectures

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Time Series Analysis, Lecture 16: Seasonal ARIMA Models

1 519 просмотров · 4 г. назад
Cache Lack Math & Stats Lectures
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1 519 просмотров · 4 г. назад
We introduce seasonality (periodic fluctuations) into our ARIMA model. This type of model is very useful in practice as time series datasets often exhibit seasonality, e.g. every seven days, every 12 months, etc. We also look at what happens to the autocorrelation function for seasonal time series data.