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Time Series Analysis

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Create an autoregressive model to predict the dataset aapl.csv. After, print the results and the model error.

  1. Read the aapl.csv dataset.
  2. Create an autoregressive model (AutoReg) with 3 lags for the X data and assign it to the model variable.
  3. Fit model to the data and assign it to the model_fit variable.
  4. Predict the first 30 values.
  5. Visualize the results: display the first 30 values of X within the first call of the print() function, and first 30 values of the predictions within the second call.
  6. Calculate the RMSE (square root of the mean squared error) and display it.

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Sektion 4. Kapitel 5
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Opgave

Swipe to start coding

Create an autoregressive model to predict the dataset aapl.csv. After, print the results and the model error.

  1. Read the aapl.csv dataset.
  2. Create an autoregressive model (AutoReg) with 3 lags for the X data and assign it to the model variable.
  3. Fit model to the data and assign it to the model_fit variable.
  4. Predict the first 30 values.
  5. Visualize the results: display the first 30 values of X within the first call of the print() function, and first 30 values of the predictions within the second call.
  6. Calculate the RMSE (square root of the mean squared error) and display it.

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Var alt klart?

Hvordan kan vi forbedre det?

Tak for dine kommentarer!

close

Awesome!

Completion rate improved to 3.85
Sektion 4. Kapitel 5
single

single

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