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Searching over model order

In this exercise you are faced with a dataset which appears to be an ARMA model. You can see the ACF and PACF in the plot below. In order to choose the best order for this model you are going to have to do a search over lots of potential model orders to find the best set.

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The ARIMA model class and the time series DataFrame df are available in your environment.

Este exercício faz parte do curso

ARIMA Models in Python

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Instruções do exercício

  • Loop over values of p from 0-2.
  • Loop over values of q from 0-2.
  • Train and fit an ARMA(p,q) model.
  • Append a tuple of (p,q, AIC value, BIC value) to order_aic_bic.

Exercício interativo prático

Experimente este exercício completando este código de exemplo.

# Create empty list to store search results
order_aic_bic=[]

# Loop over p values from 0-2
for p in range(____):
  # Loop over q values from 0-2
    for q in range(____):
      	# create and fit ARMA(p,q) model
        model = ARIMA(df, order=____)
        results = model.fit()
        
        # Append order and results tuple
        order_aic_bic.append((____))
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