From the course: Data Science Foundations: Data Mining in R

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ARIMA

ARIMA

From the course: Data Science Foundations: Data Mining in R

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ARIMA

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- [Instructor] When you have time series data with a strong pattern over time, you can use a purely descriptive visual method like decomposition, which I had showed you elsewhere, but one of the most useful methods is called ARIMA which is a portmanteau for Auto Regressive Integrated Moving Average. And it's able to make very good predictions with this kind of seasonal variations or changes over time. Now to do this, we're going to load a few new packages we're going to load forecast, which is used for time series analysis, ggfortify, which allows us to do some kinds of graphs. So I'm going to load all those packages, and set the random seed. That's something you're going to need here, that makes it so things can be more repeatable over time. We'll use the air passengers data. Again, we can get some information, it's monthly airline flights from 1949 to 1960 in thousands. We can save the data to DF and see the data down…

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